Oil & Gas – Predictive Analytics for critical assets
More important than ever before… The pressure to operate at the highest levels of efficiency while increasing productivity & lowering costs has never been higher. For professionals operating in remote environments, this has become challenging to achieve. Real-time visibility to plant operations & process equipment in order to avoid costly unscheduled maintenance and reduce downtime is now the need of the hour across the industry. Over the last decade, the significant increase of IIoT enabled sensors (generating vast amounts of data) & the use of machine learning-based predictive analytics has enabled companies to cut operational expenditure by optimizing maintenance schedules, predicting critical asset replacement & driving up productivity. (We are also hosting a webinar on the same topic on 29th April, 2020. More details at the bottom of the article) Business case for critical assets There are several hundred thousand critical assets (pumps, motors, compressors, turbines, etc.) deployed across the industry. Over 50% of them are not instrumented due to a fair majority being legacy equipment. The current manual reading based predictive maintenance techniques are tedious & are not able to keep up with the ground reality of the health of assets across the field/plant. For assets in remote or hazardous locations, the frequency of inspection is even lower. The cost of a single asset’s failure ranges from a few $100,000 to a few $100million due to production downtime, repair and in the worst-case – accidents due to catastrophic failure. All of this can now be avoided with easy to integrate, reliable & affordable sensors that can wirelessly transmit data to the edge/cloud for machine learning processing, in turn providing plant personal with real time usable information like asset health indices, etc. Predictive analytics for critical assets – Technology & solution providers Our analysis at WhatNext tells us that while there are quite a number of sector agnostic solution providers, the number of predictive analytics technology providers catering to the oil & gas industry & specifically for critical assets is very low. There is immense potential for many other incumbents to enter this space given the vastness of assets to the sensorised and digitalised. Existing solution providers include some of the large established players like BakerHughesC3.ai, OneStim from Schlumberger, GE’s Predix and Prism by Schneider & Aveva. Other companies that have entered this space over the last eight years & made a mark in the industry for the solutions they’ve implemented include Spark Cognition, Flutura, Presenso (now acquired by ZF) & Petasense. Oil field service giants like Halliburton, Aker Solutions, Weatherford, and National Oilwell Varco also offer predictive maintenance technologies to monitor the equipment health and predict the failure in advance. Implementation of predictive analytics for critical assets across the industry In Nov’2019, ADNOC partnered with Honeywell to use Honeywell’s AI-powered asset monitoring and analytics platform to maximize asset efficiency and integrity across ADNOC’s upstream & downstream operations. ExxonMobil partnered with Microsoft in Feb’19, to use its Microsoft Azure cloud computing platform & data analytics tools to deploy predictive maintenance technologies at Permian shale assets in west Texas and south-east New Mexico. Shell has been using AI and machine learning in predictive maintenance to predict asset failures & reduced efficiencies for the past several years. In April 2018, Total partnered with Google Cloud to develop AI-driven software for geophysical data analysis, besides delivering equipment monitoring capabilities. In September 2018, Chevron adopted the cloud-based data analytics approach for predictive equipment failure in its refinery operations. Working with Microsoft, the company aims to install sensors on thousands of pieces of equipment by 2024, enabling them to predict exactly when equipment will need to be serviced. In March 2018, Equinor established an integrated operations support center in Bergen, Norway, to perform remote monitoring and diagnostics of its oil and gas assets in the continental shelf. Repsol uses AI-based analytics and machine learning to enhance equipment health and improve productivity. ConocoPhillips also deployed AI-based predictive analytics technologies to optimize maintenance operations. We have a detailed article on the topic, which we are giving for free to people who register for our next webinar, wherein we will be covering how predictive analytics help define asset-specific health indices, real-time monitoring & triggering of early warning alerts based a variety of analytical models. Our technology ecosystem partners Petasense & Flutura will share their insights, experiences, guidelines & real world implementation cases that answer: Why is it crucial to digitize existing legacy non-digital critical assets? How to identify future asset health issues using software modeling of equipment & asset specific health indices? How to ensure equipment reliability & optimal performance using pattern recognition for early warning alerts? How to avoid asset failure based accidents & safety hazards using predictive models? Click here to register and access your free comprehensive article (Pdf will be emailed to you within 24 hrs) About WhatNext Global (www.whatnextglobal.com) WhatNext is a platform focused on 12 disruptive and exponential digital technologies. It is designed to help clients be in tune with, scout out, adopt the most impactful and exponential technologies globally. Our oil & gas clients use the platform to accelerate innovation cycles, solve R&D challenges, develop new business models and mitigate risks of disruption. WhatNext is a subsidiary of FutureBridge, a global research & advisory and technology commercialization and adoption services business.
When people talk about facial recognition, there are usually two camps. Some people think that facial recognition is a huge human rights violation that should simply not be allowed. Others think it’s a fun and harmless technology that people get too worked up about. Which camp you fall in probably has to do with your personal knowledge of and experience with facial recognition. However, most experts believe that the truth is between the two extremes above and that facial recognition is a promising technology that should be watched closely. Here, we’ll briefly discuss facial recognition. Then, we’ll explore some of its applications and why regulation is so important. What is Facial Recognition? “Facial recognition” comes in two kinds. One is more basic and is not a threat to anyone. The other, however, is more advanced and potentially more frightening. Recognizing Faces Humans are incredibly good at recognizing and focusing on faces. Basic computers have gotten fairly good at it too. For years, cameras have been able to recognize faces to help users take better photos. For an understanding of how basic and non-threatening this kind of facial recognition is, cameras don’t even require the internet to be able to do it. However, to be clear, this isn’t what most people mean when they talk about facial recognition. Breaking Down Faces When those old cameras recognize faces, that’s really all that they’re doing. However, an intermediate kind of facial recognition technology is able to break a face down into a series of patterns. In a vacuum, this technology is also harmless. However, when this information is used with other databases, it can be more powerful and more potentially frightening. Identifying Faces Once a computer has broken down a face into those patterns, it can match those patterns with those of other faces in a database. This technology, the most powerful, the rarest, and the most controversial, allows users to apply facial recognition to crowds to find individuals or people of specific ethnic backgrounds. The worst-case scenario often pointed to by registration advocates are stories from China about the state using facial recognition to locate and detain people from Islamic cultural groups. However, as we’ll see, more common use cases are far more agreeable. Industry Use Case Technology is neither malevolent nor benevolent on its own. How the technology is used determines whether it is a thing to be embraced or feared. Social Media The science of breaking down faces is encountered every day by thousands of people on social media. Companies including Facebook, Snapchat, and Instagram use this technology for their augmented reality face filters. Breaking the face down into patterns is what allows amusing computer “masks” in funny photos. As long as social media companies aren’t compiling databases of users’ faces for nefarious purposes, this technology is nothing to fear. However, social media sites have let us down in the past when it comes to data security. Virtual Reality Gesture control in virtual reality used to be achieved through external cameras mounted in the room. Now, it is often achieved through cameras on a headset that can see the user’s hands. However, having cameras inside the headset that can recognize a user’s face may one day be the norm. At last year’s F8 developers conference, representatives from virtual reality giant Oculus said that this technology may one day be used to create realistic virtual reality avatars that can realistically speak and express emotion in real time. Security and Law Enforcement Vuzix, an American extended reality headset manufacturer, uses facial recognition in their “Blade” headset. This headset, marketed to security and law enforcement, can use facial recognition – and even recognize emotions – in crowds viewed by a camera or drone. This technology is often the kind that is pointed to by legislation hawks as the kind of dystopian technology that should be banned. While it is alarming at first, few would object to this technology being used to identify perpetrators of violent or dangerous crime. Further, in a March 31 blogpost praising recent facial recognition legislation, Microsoft President Brad Smith pointed out that this technology could be used to locate missing or abducted children and elderly if used in conjunction with amber alert and silver alert systems. Regulation and Legislation Until recently, facial regulation was largely undertaken – or not – on a voluntary self-imposed basis by the organizations developing the technology. This is often the case when technology outpaces legislation – which is often the case. So far, there has been talk about limiting facial recognition at the federal level but that’s about it. Local and state governments have been far more productive. A package passed by Washington state last month is the best and most recent example as well as the only example at the state level or federal level in the U.S. “...legislation is required to establish safeguards that will allow state and local government agencies to use facial recognition services in a manner that benefits society while prohibiting uses that threaten our democratic freedoms and put our civil liberties at risk,” reads the new law. The law, which only impacts state and local government use of facial recognition, allows the technology to be used almost exclusively for identifying missing persons and deceased persons. Moving Forward Washington state’s law does more than limit governmental use of facial recognition in Washington State. It also provides a precedent that other states can (and probably will) use in drafting their own legislation. In the meantime, we live in a time of wide and increasing transparency and accountability in the tech sector. It may not be enough to make some of us trust them but until more governments do move in the direction that Washington state is moving in, we have little choice. To deep dive and stay continuously updated about the most recent global innovations and learn more about applications in your industry, test drive WhatNext now!
Blockchain technology is the backbone of cryptocurrencies. The tokenization that turns blockchain into a valuable commodity isn’t a necessary step in the process. Even without this step, blockchain is a way to securely and efficiently record and transfer data. As a result, it’s turning up in a lot of places other than cryptocurrencies. One of the industries where blockchain is just starting to make headway is in the automotive industry. GM and Honda Working on Blockchain Tracking of Energy Usage As vehicle makers explore the future of electric vehicles, energy use is a constant topic. While many are concerned about the cars’ use of electricity, technologists at GM and Honda are reportedly taking a different route. In some cases, future electric cars may be able to return excess energy to the electrical grid. Through a platform currently in development, blockchain would track these exchanges and reimburse motorists accordingly. Using Blockchain to Track Rare Minerals in Production Lines Blockchain is a tool for keeping information safe but it’s also a tool for keeping information accurate. That’s why Ford recently joined a partnership with other big companies including IBM and LG. They’re working on creating a method of using blockchain to ensure that cobalt is ethically mined. Cobalt is a high-demand but rare mineral. The process for mining it is often done in dangerous and exploitative ways. Without having complete ownership over their supply chains, it was difficult for manufacturers to ensure that the cobalt in their products was sourced ethically and sustainably. By using blockchain technology to track cobalt from ore to finished product, companies can be sure that they are using materials that were sourced honestly. The Distributed Ledger: Developing Supply Chains and Building Customer Credit For the last couple of use cases, we’re going to be looking at Daimler. The company behind Mercedes Benz is the most blockchain-focused company that we could find. Some of the solutions coming out of their “Blockchain Factory” are already being implemented while others are still just ideas. One of blockchain’s big claims to fame is the distributed ledger that allows any number of users access to the information simultaneously. Technologists at Daimler are currently looking at ways to take a process similar to the cobalt model above and apply it to their entire supply chain. This could create a multi-faceted and real-time ledger of the company’s resource consumption. Another potential application of this would be information sharing between companies. Daimler probably wouldn’t want competitors to have access to their supply chain as described above. However, Dr. Harry Behrens, the head of the Blockchain Factory, said in a 2019 interview that there is information that could be more widely shared. The example that he gave was information on a consumer’s credit and driving history that would allow them to easily rent vehicles. Microtransactions as Part of a Future Car Renting Platform Renting vehicles brings up another quality of blockchain and cryptocurrencies that Behrens said may come in handy one day. That’s the microtransaction. Between being able to accurately and securely record and transfer data and the ability of cryptocurrencies to be easily and inexpensively transferred in small volumes, the technology may one day be ideal for vehicle renters. Behrens even said that Daimler may one day tokenize in part to launch a blockchain-based car rental platform. BMW, GM, and Ford Look at Blockchain Payments While Daimler is looking at how blockchain could make payments between a renter and the company, other auto groups are reportedly looking at how blockchain can be used to pay everyone else. BMW, GM, and Ford are reportedly part of a consortium looking at using blockchain in cars to automatically facilitate transactions between drivers and third-parties like toll booths. The Technology of the Future Today While some of the blockchain solutions in the automotive industry discussed above are already being implemented, others are still a thing of the future. However, many of the solutions discussed above also encourage collaboration between automotive companies, insurers, payment companies etc. Hopefully, that will also mean faster adoption. To deep dive and stay continuously updated about the most recent global innovations and learn more about applications in your industry, test drive WhatNext now!
Are regulatory challenges impacting the acceleration of Autonomous Vehicle Commercialisation?
The California DMV, one of the prominent regulatory institutions in autonomous vehicle industry has released a year-end disengagement report ‘Disengagement Reports 2019’. Currently more than 60+ companies which include major OEMs, AV startups and AI providers have secured permit to test the fleet of self-driving vehicle in the state of California. The companies with DMV self-driving license have to submit annual test statistics and disengagement report pursuant to California code of regulations. The authority monitors and analyzes the report to tackle the risks and to reform the vehicle laws. California DMV defines disengagements as, deactivation of the autonomous mode when a failure of the autonomous technology is detected or when the safe operation of the vehicle requires that the autonomous vehicle test driver disengage the autonomous mode and take immediate manual control of the vehicle Is the disengagement report engaging? The self-driving pioneers including Waymo, Cruise, Aurora and Zoox have been critical of the disengagement reports. This year Chinese self-driving pioneer, Baidu has a lower disengagement rate than the Google spinoff Waymo and other peers. They also agree that using disengagement rates for comparison across companies is “not that meaningful.” It says the data is better used for examining a company’s performance over time. According to Kyle Vogt, Cruise Co-founder “Disengagement report is really great for giving the public a sense of what’s happening on the roads. Unfortunately, it has also been used by the media and others to compare technology from different AV companies or as a proxy for commercial readiness.” He states the idea that disengagements give a meaningful signal about whether an AV is ready for commercial deployment is a myth. Waymo also doesn’t agree on using California's disengagement data to compare performance, or judge readiness or competency. The disengagement report can’t be considered as a safety benchmark as it does not really tell about the autonomous driving systems. These numbers aren’t too useful in assessing the safety of the vehicles, and they might actually be reducing the proper culture of safety, and that’s not a good combination. California DMV itself advises against treating its annual report as a scoreboard. The DMV spokesman Marty Greenstein, clearly said that the reports are not intended to compare one company with another or reach broad conclusions on technological capabilities. Thee way auto manufacturers and technology firms have been aggressively investing in autonomous vehicles leaves the intense sense they expect Level 4 self-driving cars to be a swiftly accepted and transformational technology. Public acceptance of autonomous vehicles and scaling of the technology relies on the safe and reliable introduction of this technology, whilst at the same time ensuring that the technology is both cost-effective and regulated – no mean feat when operating on cross-national grounds. Regulation, requirements and verification of compliance will differ for different modes of transportation, and autonomous vehicles will not scale before this is in place. Our analysis suggests that regulation/ standardization challenges are slowing down the commercialization of autonomous vehicles. As an emerging technology the regulators face challenge to enact a universal benchmark for assessing the autonomous driving technology due to the complexity of the systems involved. We believe that over-regulating or under regulating the autonomous vehicle may proportionately affect in building confidence and trust in automotive systems. Considerations for regulation: Regulation must consider the robustness of AI to carry out safety critical assessments, which as of now is still unclear. Regulation must also cover cyber threats, which increase with a vehicle’s reliance on software and connectivity. Autonomous systems should comply with component and functional safety standards like ISO26262 et al. Vigorous testing and verification of self-driving systems, Standardized testing methods are still not available Though California DMV’s effort is to build general awareness to the public about autonomous vehicle’s deployment and its safety to monitor and analyze the risks and to reform the vehicle laws. Unfortunately report is being miss-interpreted. We belive that regulators, academia, industry players have to co-operate and jointly develop a universal safety standard considering all techno-commercial-economic challenges of the underlying technology to ensure a proper balance between Innovation & Regulation. To deep dive and stay continuously updated about the most recent global innovations and learn more about applications in your industry, test drive WhatNext now! Image Courtesy: Siemens
AI Accelerator Chips - Not a chip of the old block!!!!
There was a time when computers took up entire rooms. Many of us still think of computers with Artificial Intelligence (AI) as falling into this category. However, artificial intelligence in many devices (and it is in many devices) requires a chip around the size of a fingernail. Here, we’ll discuss AI in general as well as AI chips. We’ll discuss what they can do, the devices that they are found in, and what companies are making them. What Do AI Chips Do? Perhaps one of the reasons that we may think AI requires large amounts of computing space has to do with a misunderstanding regarding AI. A computer that has AI doesn’t necessarily pass the Turing Test, play chess, or compete on Jeopardy. What it does do is quickly search through large amounts of information and process that information. Right now, the two main things that AI is used for are cloud computing and computer-to-computer interactions. We’ll cover these ideas in greater detail in the next section. How AI Chips Are Used and How the Technology Is Growing AI in cloud computing involves processing large amounts of data from multiple sources. This is used in everything from research to facial recognition to targeting advertising online. AI in computer-to-computer interactions is made up of two distinct processes. The first is recognizing a given condition. The second is communicating that condition to another device unprompted. This kind of technology is most commonly used in “smart” devices. These two main uses of AI come together in the oft-cited “Internet of Things” (IoT). This is that most devices will be smart devices communicating with one another on a giant network. Long a popular idea, this concept has received new life with the advent of 5G internet. Another reason that we tend to overestimate the spatial requirements of AI and underestimate its ubiquity has to do with Moore’s Law. Moore’s basically states that computing power doubles and price goes down by half every two years. This results in computers that are always becoming both exponentially more powerful and exponentially less expensive. The Most Common Devices that Contain AI Chips. We’ve already touched down on a number of the devices that commonly include AI chips. Some of these devices are indeed supercomputers maintained by institutions like IBM. However, they are also increasingly found in smaller applications as well. These commonly include more standard computers and smart devices. Major AI Chip Manufacturers Right now, the single largest manufacturer of AI chips is Nvidia. Many encounter this company casually through gaming. However, Nvidia is also heavily involved in the automotive industry including working on self-driving cars – a topic that we will return to toward the end of the article. The Alphabet Corporation is another well-known manufacturer of AI chips. As the parent company of Google, it makes sense that this organization would have an interest in AI. That’s particularly true since Google offers its own cloud services and its search engine runs off of combing through unimaginably vast amounts of data countless times each day. Similarly, Microsoft also makes AI chips. While not known for its search engine, Microsoft also has its own cloud service in addition to its line of computers. Amazon also makes AI chips. As an online retailer, Amazon uses artificial intelligence to do things like suggest purchases and target advertising. It also uses artificial intelligence in its line of smart home assistants. Other notable chip manufacturers include Intel Corporation and Salesforce. The Future of AI Hopefully, this article didn’t leave you disenchanted with AI. Knowing just how simple and ubiquitous some AI technology is shouldn’t take away your respect for this technology. The Internet of Things has already begun to take hold in the form of smart technology anticipating and preemptively acting on our wants and needs. However, IoT is also the basis for more advanced applications like self-driving cars. After all, self-driving cars will need to know the locations of other cars, obstacles, and even people in order to move without accidents. Similarly, the basic AI described above is also the basis for more advanced AI applications. Applications like machine learning that may one day facilitate computers making their own decisions on behalf of humans like the poet Richard Brautigan predicted in his 1967 piece “All Watched Over by Machines of Loving Grace.” To deep dive and stay continuously updated about the most recent global innovations and learn more about applications in your industry, test drive WhatNext now! Image Courtesy: roboticsandautomationnews.com
Immersive Technology adoption in Oil & Gas Industry
Virtual reality and augmented reality are only now coming of age. Meanwhile, oil and gas have been major industries for over a century. At first glance, it can be all too easy to wonder what these literal fossil industries have to gain from immersive technology. However, in many cases, it is the oldest profession that has the most to gain from the newest technologies. Immersive Technology in Training Oil and gas are valuable because they are volatile. Working with them is dangerous for workers and for the environment. As a result, extensive workplace training is important. The power industry is only one high-risk industry that has removed the danger from training by using immersive technology. In order to provide the most accurate training possible, 3D Media specializes in rendering workspaces for virtual reality simulations. The studio works with companies to create tailored solutions for their needs using laser scanning and Photogrammetry. These advanced technologies allow a photorealistic and entirely accurate digital model of the actual work environment. Another immersive technology company in the training field is TaleSpin. Where companies like 3D Media focus on “hard skills,” TaleSpin focuses on “soft skills” like communication. They have applications for things like task orientation but their real talent is in helping employees work with one another and with the public. Immersive Technology in the Field Not all immersive technology in the fuel industry is used for training purposes. A Polish company, Solution4Labs, works with a number of industries – including fuel and heavy industry. Their HoloLens application combines immersive technology with the Internet of Things, giving scientists access to new abilities and layers of information. Printable QR codes placed on objects in the real world give researchers access to information that they can navigate hands-free. Voice commands allow them to move models and do calculations without taking their hands off of their work. They can even use the technology to videocall colleagues within the glasses. Users can even transfer information between lab equipment and the glasses for instantaneous and accurate records. Perhaps most importantly, the software can help them to access information like what to do in the case of a workplace emergency. Virtual Reality and Augmented Reality Hardware Producers Solutions4Labs, TaleSpin, and 3D Media all offer great software solutions. To use these tools, oil and gas companies need to invest in hardware as well. Fortunately, there’s no shortage of options. One option has already been mentioned: HoloLens. The MR headset from Microsoft, is currently in its second iteration and is targeted primarily at enterprise. It’s favored by healthcare but comes with attachments to fit over hardhats as well. Epson’s Moverio, another name that we’ve mentioned, has models that come with similar attachments. They also have a much larger selection of models with different software abilities and hardware options to fit different needs. In terms of factors like field-of-view, Epson isn’t the biggest player in the industry. However, Epson’s smaller and more versatile headsets are a better fit for most industries. The company also specializes in using immersive reality to control and interact with drones. HoloLens and Epson both make Mixed Reality headsets for use in the field. However, there are other options. HTC’s VIVE series is one of the best Virtual Reality headsets on the market. They aren’t much for fieldwork, but in both of the use cases below, they’re favored for on-office research. Industry Use Cases We’ve talked about a number of potential applications for immersive technology in the fuel industry. But, is anyone actually using them? Of course they are. Exxon Mobile has a whole unit dedicated to immersive technology in industry that they call The Digital Garage. An article by Exxon all about how they use immersive technology in safety training shows users implementing advanced immersive technology from HTC VIVE. Specifically, haptic feedback gloves and a harness-and-treadmill systems more closely simulate potential workplace scenarios. BP also has a video linked on its site showing how employees use immersive technology through their APEX program. Within the program, BP technologists create “Digital Twins” of production systems, updated with real information in real-time. Executives can visit these living digital models, which are also used to run simulations to maximize efficiency and minimize risk. Future Potential Immersive technology has huge potential to impact all industries, including the fuel industry. In some corners of the industry, this technology is already being embraced. Virtual Reality is used for training and testing. Augmented Reality is used to present hands-free and in-depth information on the fly. Drones can be used to survey and inspect areas from above in a safer and more efficient manner than on foot. As fuel and immersive technology continue to work together, providers and consumers will both benefit from superior products delivered at lower prices and increased safety. To deep dive and stay continuously updated about the most recent global innovations and learn more about applications in your industry, test drive WhatNext now! Image Courtesy: fsstudio.com , infosys.com
In-Cabin Monitoring Systems in the Automotive Industry
Artificial Intelligence operates across the entire value chain of the automotive industry: from design to sale or rental, through production, to drive the vehicle. Today, a majority of manufacturers (Tesla, GM, Ford, BMW, Toyota, PSA, Renault-Nissan) and companies such as Waymo, Uber, NuTonomy dream of robotic vehicles without any human presence being necessary. It is estimated that in 2025, the installation rate of AI-based systems in new cars should increase by 109% (it was 8% in 2015 according to figures communicated by IHS Markit). Another key focus area that has captured the attention of automakers and safety regulators is improving road safety. In-cabin monitoring has gained wide popularity and has seen significant advancement. In simple terms in-cabin monitoring is the placement of cameras and vision system internally to monitor the driver and other occupants. The Mood Detector in Jaguar Land Rover identifies the smallest variations in the driver's facial expressions and interacts in real-time to optimize the parameters of their comfort. Bosch engineers managed to equip the cameras with artificial intelligence. The cameras with artificial intelligence fitted to vehicles are now able to recognize objects, classify them into several categories (cars, pedestrians, or bikes) and measure their movements. During difficult urban journeys, the camera can quickly detect partially masked or sideways vehicles, pedestrians and cyclists, with reliability. Eyesight Technologies and Grupo Antolin recently announced that the companies have joined hands to provide driver and ownership monitoring solutions to OEMs globally. Grupo Antolin's deftness to integrate third-party solutions into its car interior components and the reinforcement of their control electronics will be complimented by Eyesight Technologies' state-of-the-art in-cabin sensing solutions (Driver Sense and Cabin Sense) to transport smart-integrated internal systems with significant exacerbation. The collaboration will provide car manufacturers with in-cabin sensing solutions tailored to answer regulatory needs and enhance the driving & riding experience, leveraging Eyesight Technologies' computer vision AI and Grupo Antolin's interior component design and integration capabilities. Eyeris Technologies’ in-cabin sensor fusion AI consolidates data from the image, radar, and thermal sensors and conjectures it on the AI processors to meticulously retrieve consummate in-vehicle scene assimilation, from the driver and incumbent monitoring to object detection and surface classification, for the intent of adding intelligence to invulnerability and opulence controls. Equipped with SIM cards and serving as a Wi-Fi hotspot, AI cars now look like smartphones on four wheels. Staying connected, cars have an enormous need for data, which means they have to go through an AI-managed cloud. It is a question of being able to provide a maximum of services to the user, such as the simple fact of unlocking, closing, starting or preheating his vehicle remotely to more complex services such as updating the navigation, geolocating it in the event of theft, breakdown or accident. Finally, AI does not just manage driving aids; it also takes care of preventive maintenance. One of its functions is also the monitoring of a multitude of sensors linked to the functional organs of the vehicle. Thus, by analyzing the return of data from these sensors, the system can predict and anticipate the future failure of a component that may affect the proper functioning of the vehicle. To deep dive and stay continuously updated about the most recent global innovations and learn more about applications in your industry, test drive WhatNext now! Image Courtesy: www.eyeris.ai, www.eyesight-tech.com,
Artificial Intelligence and Oil & Gas Industry – Partnership towards sustainable future
Climate change is a reality and is the biggest threat to mother earth! An estimated 65% of global industrial greenhouse gas emissions over the past two centuries are directly linked to the activities of oil and gas companies. As many see the oil and gas industry as a major source of pollution, the move towards sustainability is becoming the cornerstone of all strategies and plans of oil conglomerates.
Many oil and gas companies have embarked on an environmental management journey to promote environmentally sound industrial development. Abu Dhabi National Oil Company (ADNOC) announced its plan to reduce its greenhouse gas emissions intensity by 25% by 2030. As part of its sustainability initiative, ADNOC agreed to limit the freshwater consumption ratio to below 0.5% of total water use. BP has pledged to eliminate carbon emissions from its operations and reach net-zero carbon emissions by 2050 or sooner. While individuals like Jeff Bezos have pledged $10 billion to combat climate change, oil and gas companies are adopting innovative technologies to improve environmental performance. The interest in technologies such as artificial intelligence and machine learning is steadily increasing among oil and gas companies. Many energy companies are now adopting AI-powered technologies to achieve their business goals while reducing environmental impact.
Many companies are now adopting AI-based data analytics to augment E&P capabilities and discover new exploration opportunities. The other major application areas include: Predictive maintenance Machinery and plant inspection Production planning Field services Quality control Distribution and marketing Oil companies are now integrating AI technologies into their upstream, midstream, and downstream operations.
British Petroleum & AI In January 2020, the oil and gas giant made an investment of USD 3.6 million in Chinese AI energy management tech company R&B to support BP Alternative Energy’s focus on low-carbon power and digital energy
BP also acquired the majority stake in fiber optic innovation company Fotech with an aim to integrate Fotech Fibre optic sensing solutions which are invaluable in protecting pipelines.
In January 2019, it invested USD 5 million in Houston-based AI startup Belmont Technology to use AI for accelerating its exploration activities. Belmont develops a cloud-based geoscience platform, called Sandy, using AI. With the investment, BP is planning to leverage Sandy to interpret geology, geophysics, historic and reservoir project information to create unique “knowledge-graphs.”
Aker BP & AI In March 2019, Aker BP, partnered with AI Company, SparkCognition, to use artificial intelligence for accelerating its predictive capabilities. SparkCognition’s flagship product “Spark Predict” uses artificial intelligence algorithms to protect the health of machine assets, predict downtime, minimize maintenance costs, and optimize schedules.
Aker BP also made a strategic partnership with global industrial artificial intelligence software-as-a-service (SaaS) firm Cognite to explore the potential of robotics in the offshore oil and gas platform. With the acquisition, the companies will together work to use robotics systems to carry out safer, more efficient and sustainable offshore operations.
Baker Hughes & AI In 2019, the US-based Baker Hughes, released its first AI application developed by the Baker Hughes - C3.ai joint venture. The application, called BHC3 Reliability, uses machine learning models to identify anomalous conditions that can upend equipment and processes. The applications alert operators to take action to prevent downtime.
In February 2020, the Baker Hughes and C3.ai joint venture also launched a new AI software to optimize oil and gas production. The product, BHC3 Production Optimization, uses artificial intelligence to allow well operators to view real-time production data and predict future production.
The oil and gas player also entered into a three-way deal with C3.ai and Microsoft Azure to boost the adoption of artificial intelligence technology in the oil and natural gas industry. Under the terms of the agreement, the companies will work together to streamline the adoption of scalable AI solutions for the energy industry. It combines the tech expertise of Baker Hughes, C3.ai’s AI platform and applications, and the Microsoft Azure cloud computing platform to address challenges across the entire value chain,
In late 2019, oilfield services company Schlumberger and software firm Dataiku teamed up to enable the E&P industry to build and deploy their own artificial intelligence solutions across the full breadth of their upstream workflows within the DELFI cognitive E&P environment.
Siemens selected Israel-based AI startup, Presenso, as its strategic partner in AI and machine learning for predictive asset maintenance for operations and maintenance solutions in oil and gas and distributed generation.
In July 2019, Japanese AI company, Preferred Networks, received 1 billion Yen investment from JXTG Holdings and launched a joint research project for optimization and automation in oil refineries.
Similarly, AI startups like OAG Analytics, Novi Labs, Earth Science Analytics, etc have received investment for accelerating AI innovations in oil and gas industry.
AI has already been incorporated into a number of areas within the oil and gas industry. AI could also help oil and gas companies to achieve their sustainability goals by predicting plant emissions in advance.
AI-based analyzers can identify the key variables that cause emissions. It will enable oil and gas companies to take action before violations occur. Swedish multinational corporation, ABB, already implemented such AI-powered emission prediction technology in one of the largest gas processing plants in the world. ABB’s Predictive Emission Monitoring System (PEMS) uses an empirical model to predict emission concentrations based on process data. By acquiring reliable information about emission levels, the system helps plant owners to take control actions to keep emissions inside law-enforced limits.
With the increased number of investments, cross-industry collaborations, and partnerships between AI & oil and gas industry, we can say that AI has real potential to make oil companies smarter in the future. To deep dive and stay continuously updated about the most recent global innovations and learn more about applications in your industry, test drive WhatNext now! Image Courtesy: www.bhge.com, www.bp.com, www.akerbp.com,
Infectious disease surveillance Detection Through Artificial Intelligence
The World Health Organisation on 30th January 2020, declared the Novel Coronavirus epidemic an international public health emergency, exactly 21 days after it released a global notice about the potential outbreak. During this time China has identified over 7,700 confirmed cases and witnessed over 200 fatalities. WHO, officially notified about the Wuhan outbreak on 9th January 2020, while the US Center for Disease Control and Prevention was made aware of the potential outbreak on 6th January 2020. While the agility of all parties working to control, the situation is absolutely commendable, we could probably have covered more ground (approximately a week's worth of time), had we immediately acted on the warnings raised by BlueDot. Artificial Intelligence start-ups have long been working on solutions for the Healthcare industry and once such company is BlueDot, a Canada based digital health company, that predicate the first warning signs of the potential outbreak a week prior to the official notification. The company uses Machine Learning and natural language processing techniques to analyses news reports in websites, government documents, and information on plant and animal disease networks, etc. to predict the outbreak. The company was also able to predict the countries that would be high risk based on global airline ticketing data. The firm was accurately able to forecast Bangkok, Seoul, Taipei, and Tokyo as high-risk countries. Similarly, Hong Kong based SenseTime is supporting officials accurately identify patients with fever in a crowd using its deep learning platform based on face recognition technology The company is one of 416 AI-based start-ups on our WhatNext platform that are working on various solutions for the healthcare industry. Geographical Split of AI Start-Up Focused on Healthcare Sector AI-based companies can not only help in predicting outbreaks but also in: · Quick Diagnosis of Symptoms · Identify High-Risk Patients · AI-Enabled Research for Vaccines and Potential Treatments · Remote Monitoring of Patients and Predicting Risk Level · AI-Based Rapid Response Management etc Snapshot of some of the interesting companies that we have on our platform * Key reason for fatality due to Novel coronavirus is the existence of other health ailments and not just the ailment. Check our platform for more insights on start-ups and technologies disrupting industries globally.
In three years, the electric car will be cheaper than gasoline
The battery of the future: 965 km of autonomy for electric cars Bloomberg advances to 2022 the point of parity between the price of an electric car and the price of a car with an equivalent combustion engine. First, it was 2029 (in 2017), then 2026 (in 2018) and for this year 2029 is the forecast of Bloomberg NEF. It will be in 2022 when electric cars will be cheaper than gasoline cars. Bloomberg NEF analysts base their calculations on the evolution of costs and especially on the price of the battery, the most expensive element of electric cars. The convergence point "will be a crucial moment for the electric vehicle industry" because the price factor will no longer enter the buyer’s equation, according to Bloomberg. The key, the cost of the electric battery Choosing an electric car over a gasoline one will increasingly be a matter of "taste, style, preference" or necessity, "but it will not be for a long time a matter of price" as it is to a large extent now. According to Nathaniel Bullard, an analyst at Bloomberg NEF (New Energy Finance) in 2015, 50% of the cost of an electric car corresponded to the battery. That percentage is currently 33% and will fall to 20% in the middle of this decade. "Achieving parity in the initial cost means that the buying trend is close to leaning in favor of electric vehicles," they say in Think Progress. "And it also means the beginning of decarbonization of much of the transport sector." It also lowers the price of engines and electronics According to the results of the latest BloombergNEF study (BNEF) devoted to the evolution of their prices, lithium-ion traction batteries were traded on average at 156 dollars (140 euros) per kilowatt-hour during this year 2019. -87% since 2010. As a logical consequence of the development of electric mobility, the price of lithium-ion traction batteries has dropped by 87% since 2010. That year, they were billed at around 1,100 dollars (991 euros) per kilowatt-hour. In its projections, BNEF estimates that the unit will approach 100 dollars (90 euros) by 2023. Therefore, electric cars may no longer be more expensive than equivalent gasoline models. Electric vehicles offer numerous advantages over gasoline vehicles, beyond the environmental issue: among others, they have a better performance, are quieter and are costly to maintain by having less mechanical elements and less moving parts susceptible to breakdowns. Although batteries are not exempt from the risk of an increase in price due to demand and the use of finite elements such as lithium, the technicians and technicians of the battery industry should mark a general trend towards cheaper, usual in the technology. In addition to the battery, other key elements of electric cars, such as motors, also record a reduction in costs due to increased production: "during the next decade, key components such as motors and electronics can be reduced by up to 30 %." To deep dive and stay continuously updated about the most recent global innovations in Energy Storage and learn more about applications in your industry, test drive WhatNext now! Image Courtesy:
The stellar growth of counter-drone solutions market
Drones market has been booming and has become an integral part of daily use for consumer applications like photography, drone racing and training. Its commercial applications include aerial surveillance, terrain mapping, law and order, government administration. Drones have also proved their utilization in industrial sectors for aerial imagery of industrial, construction and mining sites. These drones, when integrated with post-processing solutions, provide post-processing business analytics like 3D mapping & twin model creation, industrial gas detection, power line inspections, wind and solar farm surveying and many other applications. Drones have proved to reduce inspection costs and time and perform timely maintenance. Every developed technology has its attractive advantages, but a few mischievous activities have highlighted a few disadvantages. To control unauthorized use and drones and avoid malicious use of drones causing a hazard, counter-drone solutions have been implemented. Why counter-drone solutions? Everyday new set of commercial, consumer and military drones are added to the airspace serve certain applications and the count has reached millions. Introducing drones into the airspace with a higher number have realized certain disadvantages which can put lives at risk. There have been a few instances where drones have breached security and safety. Usage of drones near sensitive areas like airports, military bases and security-sensitive sites has led to ‘shutdown of airports’ and military services have gunned down these drones. The entry of drones in unauthorized areas has led tech-companies to focus on developing counter-drone technology aka counter-UAS or C-UAS technology. These counter-drone solutions are devices which can track or intercept drones. Drones have been visualized as weapons with its design advantage of compact and robust size, low cross-section where they go undetected. Drones flown in sensitive areas which are not authorized are called rogue drones. These drones need to be detected, identified, neutralized/intercepted before they could cause a potential threat. A few instances where drones have caused disruption; Gatwick airport shutdown: The world’s busiest runway was shut down for 33 hours cancelling over 1,000 flights and halting over 150,000 travellers. Saudi Aramco oil facility drone attack, Saudi Arabia. There were other instances of drone attacks but considering these two instances, drones can be a potential threat if misused. Technology companies have developed various counter-drone solutions to detect drones. Their solutions revolve around Detection, Tracking and Identification. These technologies use Radar, Radio-frequency (RF), Electro-optical (EO), Infrared (IR), Acoustic sensors. Military-grade drone detection systems are developed with a combination of multiple sensors for detection. These technology companies have thought afar and have developed multiple platforms for drone detection like fixed mounts, vehicle-mounted and handheld systems. Fixed-mount drones detection systems are standalone systems installed at airports, military bases, and critical infrastructure sites. Here, the installed drone detection systems include features like Detection, Tracking, Identification, Alerting and Mitigation. Solutions developed by Liteye; ADIS, smart-sensor ground surveillance-based remote detection of small UAS, providing situational awareness and uses Advanced EO sensors to track the rogue drones. Other solutions include Aaronia’s RR Drone/radar detection system, Advanced Radar Technologies’ Drone Sentinel and FLIR’s Ranger. Another company, DeDrone has deployed software DroneTracker 4 which detects, localizes, and tracks simultaneous drones. The solution is capable of providing Drone Flight Pattern Recognition which provides airspace analytics to understand patterns in drone activity and ‘Heatmaps’ a Visual hotspot interface will enable a quick overview of unauthorized drone activity. Apart from the standard fixed mount standalone drone detection systems, the companies have developed a variety of drone detection and mitigation. Drone neutralization systems include DroneGuns, man-portable, vehicle mount or drone mount systems. These systems can be used in far sites where the fixed mount drone systems cannot be accessed. How does drone neutralization work? Drones are operated either through constant communication through a link with the operator through a communication link or the flights are pre-planned. For drones with a communication link, RF/GNSS Jammer and spoofing is used to neutralize the drones where the communication link is jammed and the rogue drone is disconnected. For pre-planned flight drones, Lasers, nets, armed projectiles are launched to either confiscate the drone or eliminate the rogue drone threat. Smart drone neutralization systems are developed by companies like Delft Dynamics has developed a drone catcher solution which is a net gun-armed multi-copter solution. For vehicle-mount systems, Silent Archer developed by SRC with detect, track, classify, identify and disrupt small unmanned airborne threats. SRC has secured $108 million contract to deliver vehicle-integrated Silent Archer counter-drone system that uses radar, cameras and jamming technology. Israel based D-Fend solutions; a mass-adopted counter-drone system developer has raised $28 million in funding. It develops autonomous counter-drone perimeter security system which autonomously detects, identifies and intercepts intruding drones. DroneShield launched compact-vehicle mounted counter-drone solution, DroneSentry-X that performs automatic detect and defeat drones. It offers real-time mobile situational awareness with the ability to automatically counter the drone detected threats. Governments and defence departments have been heavily investing in counter-UAS solutions. DOD invested $900 million on counter-UAS solutions under The DOD’s C-UAS Strategy. DOD has diverted its funds from developing drone technologies to counter-drone technologies to secure the zones. Other C-UAS developer companies are been funded by the Defense Forces like; Ascent Vision Technologies secured a contract of $23 million to supply mobile counter-drone vehicles for the eXpeditionary Mobile Air Defense Integrated System program. Raytheon, a Military drone developer is working on ATHENA, a high-energy laser system. Soon counter-drone systems would be an integral part of aerial unmanned traffic management (UTM) system, where companies are working to develop softwares to integrate drones to airspace. Companies like Airmap, Altitude Angel, CerbAir, Involi and Flarm Technology have partnered to provide integrated, comprehensive solutions for low-altitude airspace safety and security. Technology companies are developing a comprehensive suite of UAS management and detection solutions. Flight planning softwares are available which provide real-time information about the no-fly zones and don’t allow the drone operators to fly the drones in the no-fly zones. To secure airspace, The North Atlantic Treaty Organization (NATO) has partnered with Fortem Technologies to showcase SkyDome Network defence platform and demonstrate C-UAS capability. For term, technologies have developed ThreatAware platform and an autonomous drone interceptor, DroneHunter. For term has been invited to showcase its C-UAS capability for “Comparative Analysis of Lethal, Low Collateral Damage Effectors Against Low, Small and Slow UAV” program where C-UAS will be evaluated for drone mitigation solutions for small, dangerous UAV. Also, DroneShield has partnered Altitude Angel to develop ‘single-point situational awareness’ for managed airspace such as national governments and airport operators. Counter-Drone Technology, What’s Next? Counter drone systems have started acting as a second degree of surveillance technology across the industries. Drone detection systems and counter-drone solutions have developed to an advanced level within a short period of time. Soon expect the counter-drone equipment could be modular and compact where multiple drone detection systems could be integrated. Integrating civilian and commercial UAVs into manned airspace through UTM would require remote identifications. Remote IDs equipped drones will provide remote information access about drone model type, operator’s identity, application of drone operation, time of flight and location. The remote ID will play a crucial for drone identification and narrow the C-UAS challenge. Governments have been working with the companies to enable the airspace through UTM. Switzerland has partnered Skyguide and Airmap to develop flight information management system (FIMS) for drones. This cloud-connected data exchange hub allows service providers to connect and receive information from Skyguide’s Air Traffic Management (ATM) system. Another way of detecting drones, video surveillance may also present itself as a promising technology to identify drones. IP camera and Video Management System companies have started developing passive drone detection capability. Their solutions are focused on software solutions and IP cameras. Integrating C-UAS with Artificial Intelligence (AI), Threat prediction software will enable faster mitigation response. AI will drive innovation with both AI-based visual transportation sensors used for object recognition and traffic flow analysis. More features like airspace mapping, central command and control systems, and rogue drone tracking. To deep dive and stay continuously updated about the most recent global innovations in the world of Drones and learn more about applications in your industry, test drive WhatNext now! Image courtesy : counterdronesolutions.com.au
FORMNEXT 2019- TECHNOLOGY UPDATES AND NEW LAUNCHES
Formnext 2019 is a global exhibition and conference dedicated to additive manufacturing and industrial 3D printing. This year, the fifth edition of the exhibition and conference was held at Messe Frankfurt, Germany, from 19 to 22 November 2019. It was attended by 34,532 specialists and managers, a growth of 28% over last year and 852 exhibitors with a growth of 35% over last year. Formnext summit also saw internationally-recognized organizations, industry experts, renowned academics and market analysts from Europe, USA, and Asia provides a truly global overview of how advances in 3D technologies, design, and engineering, are impacting the manufacturing world. The exhibition was attended by world-renowned companies across aerospace, automotive, healthcare sectors like Airbus, Apple, Adidas, Bayer, Honeywell, BMW, P&G Manufacturing, Roche Diagnostics, Siemens, etc. This year’s exhibition has been hugely successful witnessing number of technological updates and launches. Some of the launches and technology updates in areas of software, 3D printers, material and post-processing solution are discussed below. MSC Software Corporation - MSC Apex Generative Design MSC Software Corporation is an American software company based in Newport Beach, California, that specializes in CAE simulation software. MSC Apex Generative Design is a new design optimization solution. The optimization process is more straightforward and users can simply input boundary conditions and design objectives for a given part and the software will come up with design solutions. Hence, it can generate a part design that is ready to be printed within a few hours. By taking boundaries and objectives into account, the software will generate multiple lightweight design candidates while providing optimal stress distribution and minimized part weight. The software also employs an intelligent smoothing technology that ensures 3D models have a smooth, professional finish. It also offers integration of all steps into a comprehensive CAE environment, enabling users to easily navigate from design to AM preparation on a single platform. Since the program provides a high degree of automation for design processes, it has the potential to improve productivity by up to 80% compared to more traditional topology optimization software. Smarter generative design process produces design candidates that can satisfy both engineering criteria and looks like the designer intended in 3D printing which absences in the traditional design solution. Desktop Metal – Shop System Desktop Metal is a technology company that designs and markets metal 3D printing systems. The company was founded in October 2015 in Cambridge, Massachusetts. Desktop Metal has launched “the world’s first metal binder jetting system designed for machine shops.” called Shop System. It is a high speed and single-pass printing system built for mid-volume production runs for machine shops. This technology enables affordable, reliable and flexible batch production of complex parts for machine shops. Users can print end-use metal parts with the quality, surface finish and tolerances needed to co-exist with machining – up to 10 times faster than laser powder bed fusion and at a fraction of the cost per part. It has the highest resolution single-pass binder jetting printing system on the market. With a spot size of 16 microns per drop, 1600 native single pass DPI and the ability to distribute up to 670 million drops per second. Compared to other single-pass binder jetting systems, it has a 33% higher resolution, as per the company. This system print fully supported in their powder bed and feature hand-removable sintering setters, users will avoid hours of labour machining or wire EDM off support structures typical of laser-based systems (traditional system). This, in turn, reduces the total number of manufacturing steps needed, increasing shop productivity and capacity without requiring additional headcount or machinist hours. Since, its world’s first metal binder jetting system for the machine shop, it has no current competition in the market. EnvisionTEC and Sartomer-E-Aquasol EnvisionTEC is a global developer of professional-grade 3D printing solutions with US offices in Dearborn, Michigan. Sartomer, a global supplier of specialty chemicals and a business line of Arkema with US headquarters in Exton, Pennsylvania. E-Aquasol resin has been jointly developed by the two companies. It is based on Sartomer’s N3xtDimension UV-curable resin technology and is characterized by its high water solubility. E-Aquasol resin is ideal for printing moulds in a wide variety of industrial applications. It allows industrial manufacturers to shell-cast thin-walled parts with high feature resolution. The material is thus a suitable and safer alternative to competitor’s resins, which are mostly soluble in more aggressive solvents like caustic. It is an optimal choice for users who seek to avoid the use of more aggressive solvents such as caustic. AMT-DMS post-processing solution Additive Manufacturing Technologies, a British industrial AM company focused on end to end post-processing technology solutions for Additive Manufacturing. AMT has launched its proprietary Digital Manufacturing System (DMS). It is fully automated safe and sustainable post-processing solutions enabling industrial production of parts at scale. It covers the entire manufacturing process chain from build through to final inspection. The DMS system handles unpacking the AM machine with automatic sorting, material removal and de-powdering with the PostPro3DDP system, smoothing and/or colouring and inspection with PostPro3DMet metrology system. The company had displayed stand with more than 6000 3D printed and post-processed parts which are light and completely modular, meaning that it can be reused in configurations that suit any future events while being easy and carbon-efficient to transport. AMT’s solution is superior to its competitors as it combines market-leading technology, machine learning capabilities, automation and superior research and production partnerships. It unites the stages of post-processing via intelligent, digital connectivity and innovative hardware. Conclusion In the last three decades, additive manufacturing has become an integral part of the manufacturing process in healthcare, aerospace and manufacturing where customization and precision are vital. As the speed of innovation continues to increase, it will help bring this disruptive technology to the forefront. This will aid in the production of high end and high precision products, cost reduction, a high degree of customization, reduced time lag between design and production, environmental sustainability thus overcoming the limitation of existing technology. Continuous technological updates and innovation in 3D technologies will make the process even more efficient, safe and is expected to see adoption across industries. To deep dive and stay continuously updated about the most recent global innovations in Additive Manufacturing and learn more about applications in your industry, test drive WhatNext now! Image Courtesy : formnext.mesago.com
Google conquers quantum computing with its new device
Quantum computing has been a source of great imagination for us over three decades now. Popularized by the 21st-century physics on quantum mechanics and the huge scope of applications, especially in space research, quantum computing is a key to mankind’s next big revolution in the domain of computer science. Google has claimed that it has achieved quantum supremacy through a programmable superconducting processor which is miles ahead of the fastest supercomputers available in terms of computing speed. The quantum processor devised by Google is a product of a quantum supremacy experiment to incorporate quantum concepts into a computer which is programmable as well as powerful. The device, christened as ‘Sycamore’ has been able to complete the intended calculations in 200 seconds as claimed by Google. To put it in perspective, it would take the fastest existing supercomputer 10,000 years to do the same calculation with available resources. What’s inside the Sycamore? The Sycamore quantum processor consists of a two-dimensional grid of 54 qubits. The qubits are arranged in such a way that each qubit is connected to the nearest four qubits by means of adjustable couplers. As the conducting electrons reach a quantum state, the currents and voltages in the circuit follow quantum mechanics rules. The qubits can be controlled in two ways – one to excite the qubit through a microwave drive and another to tune the frequency through a magnetic flux control. The coupling design in the quantum processor allows for a tuning range of 0 to 40 Hz. The key to success in achieving quantum-state behavior in Sycamore is the cryogenic chamber where the core setup of the processor is stored. Away from external disturbances, every qubit behaves like a superconductor facilitating electrons to move about and execute the laws of quantum mechanics. The processor consists of aluminium for its metal parts and Josephson junctions, and indium. Signals from the cryogenated processor are amplified and controlled through filters, attenuators and amplifiers. Scope, Applications and Challenges The development of Sycamore is to computing technology what Kiti Hawk was to the aerospace industry. Google’s achievement is a harbinger of further developments in quantum computing with players such as IBM already in the fray. While Google scientists have admitted that the Sycamore of today is not of much use, but once the number of qubits employed in such processors reaches thousands, one can imagine realistic devices with quantum capabilities in future. Advanced versions of devices like Sycamore will be capable of performing simulations of chemical reactions enabling scientists to create revolutionary drugs, generating ultra-strong passwords for cybersecurity, cracking cryptographic codes, calculating combinations of elements for building new materials, and solving the many mysteries in space research. For the huge powers that quantum computers promise, as, in the case of Googles Sycamore, the corresponding errors or challenges are also significant at this stage of evolution of quantum computing. Instability of coherence, caused by factors like vibrations, temperature changes, and other environmental elements, pose the biggest impediments to the rapid success of quantum computing. Present-day developments in quantum computing are challenged by the high cost of operation, especially the hardware which needs cryogenic conditions to function. To deep dive and stay continuously updated about the most recent global innovations in Quantum Computing and learn more about applications in your industry, test drive WhatNext now! Image Courtesy :
The lithium-ion battery is one of the most common energy storage entities in the world. Lithium-ion batteries are the driving forces behind several devices and machines from cell phones to laptop computers, electric vehicles to industrial tools. The revolution of lithium-ion battery that began in the 1970s has culminated into three chemists being awarded the Nobel Prize in Chemistry, 2019 – Stanley Whittingham, John Goodenough, and Akira Yoshino. The members of the Nobel committee 2019 cited the immense impact of contributions of all the three chemists in serving mankind. The Who’s Who of lithium-ion research Stanley Whittingham is a professor at the State University of New York and was formerly with the Oxford University. He is considered to be the pioneer of the lithium-ion battery. John Goodenough is a professor at the University of Texas at Austin. At 97, Goodenough has become the oldest to be awarded a Nobel Prize. Akira Yoshino works for the Japanese chemical firm Asahi Kasei Corporation and is a professor at the Meijo University in Nagoya. Yoshino perfected the present-day lithium-ion batteries. Evolution of the lithium-ion battery The global oil crisis in the 1970s prompted scientists to rank up research on non-conventional non-fossil fuel-based energy sources. Stanley Whittingham, then working for Exxon, began researching on energy storage techniques. His particular interest in superconductors led towards experiments in developing better batteries. He used lithium, the lightest metal, as anode owing to its affinity to release electrons readily and positively charged ions. He incorporated titanium disulfide as the cathode, packed in the layers and capable of housing lithium ions released from the anode. With 2 volts of output, what Whittingham developed can be regarded as the first lithium-based battery. The lithium battery had the capability of storing 10 times more energy than lead-acid batteries. The lithium batteries created by Whittingham had its issues. After a few cycles of recharging and discharging, strands of lithium would grow from the anode which upon touching the cathode would cause the battery to be short-circuited. John Goodenough built upon Whittingham’s developments and found that cobalt oxide can be a better cathode than titanium disulfide. The fact that cobalt oxide cathode could accommodate more lithium ions within its layers helped in doubling the voltage potential of the lithium battery. Goodenough’s efforts increased the battery output to 4 volts. It is noteworthy that several smartphones today use lithium-ion batteries with 4 volts of power output. Akira Yoshino later replaced the metallic lithium anode with layered petroleum coke, which had the capacity of holding more number of lithium ions. The removal of lithium metal from the battery did away with the danger of combustion or explosion as lithium burns when exposed to air. Yoshino’s findings made the lithium-ion battery more lightweight, safer and durable. The first commercial lithium-ion batteries appeared in 1991. Flaws and future Lithium-ion batteries have undoubtedly been a huge revolution of the century. But these are not without flaws which need to be ironed out. Like any other battery system, lithium-ion batteries have a limited recharge-discharge cycle. Defective fabrication of the batteries can cause short-circuit and explosions. The widespread instances of issues with the Samsung Galaxy Note 7 smartphone batteries highlight the risk of lithium-ion batteries. Sources of lithium are limited in nature and increased usage of lithium-ion batteries might exhaust the lithium sources in the near future. Ongoing researches on incorporating novel materials in the lithium-ion battery promise to shun out the existing issues like safety and charging speed. One such innovation hinges on the fact that lithium-ion batteries, when charged at optimum temperatures, will not degrade easily. Termed as a self-heating battery, the new approach includes a nickel foil in the battery setup that increases battery life as well as charging speed. Another research uses light irradiation to increase the charging speed of lithium-ion batteries. It has been found that charging rates of batteries can be enhanced by exposing the electrodes to a concentrated light. Environmental pressure might also pave the way for replacement of lithium-ion batteries in the future with batteries equipped with smart materials. Scientists claim to have developed a fully-rechargeable lithium-carbon dioxide battery that is 7 times more efficient than the existing lithium-ion batteries. To deep dive and stay continuously updated about the most recent global innovations in Energy Storage and learn more about applications in your industry, test drive WhatNext now! Image Courtesy :
Open Source 3D Printing – A new way of collaboration?
3D printing has been around for about 30 years. One of the factors that determine the success of a 3D printed object is largely dependent on the material and technology used. FDM is the most commonly used technology that provides the option of a wide range of plastics. Recent developments have led to metal printing with this technology. 3D Printing pioneer, Stratasys has in-house expertise for material development and offers advanced materials that can be used to achieve printing with the highest level of efficiency, if the process parameters are properly optimized. A majority of companies develop materials for a specific set of machines. Recently some chemical companies have shown an inclination towards 3D printing materials. China-based oil industry giant Sinopec has entered in a contract with HP to develop AM specific materials. The limitation of printers to be compatible with a specific material can be a major roadblock for companies that may intend to expand their application use cases with materials that offer different properties. Ultimaker has proposed a solution to this problem. It has developed an open platform, featuring a variety of quality materials that enable customization often required by manufacturers. Ultimaker has partnered with Essentium, Polymaker and eSun with an aim to expand the choice of materials and applications for extrusion-based 3D printing. The platform provides optimized material profiles in its software cura. This claims to solve the issue of the choice of materials. As a result, a user can adopt a required material from the Ultimaker market place and print its part with short lead times. The collaboration of materials and printer manufacturers can be seen as a move to push 3D printing into the mainstream. It offers an opportunity to print with a large variety of materials. In metal additive manufacturing, specific materials have been under development and several mergers such as carpenter and LPW have taken place. With growing interest in metal printing, such a collaborative model will gain more relevance in metal AM than in polymer because of the sheer scale possibility in terms of manufacturing. Such a platform has some advantages: Increased & Continued Innovation : The open market allows design engineers and R&D teams to work from an existing set of materials. It facilitates a larger pool of ideas that can be quickly deployed on an open platform without legal concerns. Global Engineering Team : The transition of a newly developed material to a product gets accelerated. In house, teams receive global material exposure. Challenges are solved more rapidly than would be possible within a closed model. Inexpensive & Accessible Technology : A multitude of material options in different price bands helps technology adoption, finally making the technology more accessible to a range of customers. To deep dive and stay continuously updated about the most recent global innovations in Additive Manufacturing and learn more about applications in your industry, test drive WhatNext now! Image Courtesy :
Canada based e-commerce firm Shopify has acquired 6 River Systems through a $450 million deal to enhance its supply chain system and logistics management. The deal includes a 60 per cent cash consideration and 40 per cent Shopify stock. The cloud-based software platforms at Shopify enable sellers from across the world to avail built-in online storefronts. Boston based 6 River System has a wide range of clientele and a base of over 20 facilities across the US, Canada and Europe that provide fulfilment solutions to e-commerce firms and retail operators. Through this deal, Shopify intends to incorporate 6 River Systems’ warehouse automation technologies to rank up its delivery process and increase the efficiency of warehouse operations. Upgrading technology: A shot in the arm At a time when the e-commerce market has witnessed rapidly growing competition, the race to be on top of the game demands investment in the best and latest technology. The acquisition of 6 River Systems by Shopify intends to augment the Fulfillment Network Service that Shopify had launched earlier this year. The service is a machine learning-enabled inventory allocation technology which facilitates merchants to locate the most convenient and accessible fulfilment centres for their online business. With e-commerce giants like Amazon providing a two-day delivery through its Prime package, the latest acquisition by Shopify intends to catch up in the game. Coupled with its new fulfilment network service, the 6 River Systems robotic services will aim at reducing shipping costs at Shopify and facilitate quicker delivery to users. Anti-Amazon move? Back in 2012, Amazon had acquired Kiva Systems in a $775 million deal to strengthen its operational efficiency and improve profit margins. The deal allowed Amazon to tap on to the Kiva robots and their advanced inventory management system. Kiva’s systems were revolutionary back in those days and it enabled Amazon to boost its delivery performances. It is noteworthy that, two of the three co-founders of 6 River Systems previously worked with Kiva until it was bought by Amazon. Technology pundits have refereed to Shopify’s acquisition of 6 River Systems as an anti-Amazon move as the Canadian company strives to catch up with Amazon by strengthening its warehouse automation resources. While Kiva Systems, rebranded as Amazon Robotics after its acquisition, ceased to deliver warehouse automation solutions to its previous clients, reports of the recent acquisition state that 6 River Systems will continue to build robotics solutions to global clients including the likes of Lockheed Martin and DHL. What’s ahead The rapidly evolving technology arena and rising customer expectations are paving the way for warehouse automation market to bloom. Technologies such as IoT, advanced sensors, real-time tracking of inventories, automated storage and retrieval systems, are being employed increasingly by several players in sectors like manufacturing, distribution and e-commerce. Robotic firms like Kiva and 6 River Systems are bound to add advanced features in their arsenal to cater to the rapid demands in warehouse automation. The presence of technical players in the field of warehouse automation is evenly spread out across the world. Beijing based Geek Plus has contributed to the rising disruption in the supply chain automation market in Asia-Pacific through its innovative products that include automated forklifts and automated mobile robots for warehouses in different sectors. KUKA AG, a Germany based automation systems provider has been developing automated robotic solutions for food, glass and wood industry, apart from its long record of producing heavy industrial robots. On the global scale, players in the Asia-Pacific region are predicted to dominate the warehouse automation market due to the rapid growth of e-commerce and automation in sectors like food, pharmaceutical and electronics. Warehouse automation in the North America and Europe region looks equally promising given the substantial growth of automation in industrial activities like palletizing, packaging, transportation and manufacturing. A research by LogisticsIQ predicts the warehouse automation market to reach $27 billion by 2025. The competition among e-commerce players such as Shopify and Amazon can only usher the development of smarter warehouse automation solutions. To deep dive and stay continuously updated about the most recent global innovations in Robotics and learn more about applications in your industry, test drive WhatNext now! Image Courtesy : blog.aboutamazon.com
The field of bionics is the best example of the fact that science and technology are largely inspired by nature. While bionics can be broadly defined as biologically inspired engineering, it emphasizes on imitating certain biological functions that can be seen in nature. For instance, technologies like sonar, radar and medical ultrasound are inspired by animal echolocation. Velcro is another system that has been developed by observation of tiny hooks found on the surface of burs. Research and development in the field of bionics have had the highest impact in the healthcare sector as manufacturing of bionic limbs is catching speed in recent years. The advent of 3D printing has added an edge to the domain of bionics as it gives freedom to bionic experts and innovators in developing customized bionic components in lesser time. Areas of application In the case of bionic implants, there are four broad areas of application – vision, orthopaedics, hearing and neurology. Out of these, neurological bionics comprise a tiny section of the entire developments in the domain. Bionic eye Fabrication of bionic eye might seem to be a boon for the partially or completely blind but research in this area is still in a nascent stage. Few prototypes of the bionic eye that have been developed, consisting of bio-electronic implants that can mimic the retinal function. In 2018, a team of researchers at the University of Minnesota became the first to 3D-print a prototype of a bionic eye. The researchers embedded semiconducting polymer materials on a hemispherical surface to print photodiodes, which were used to convert light into electricity. California based Second Sight Medical Products of Sylmar is one of the foremost players in the realm of bionic eye fabrication. Its bionic eye prototype named Argus II implants a microelectronic array on the retina and processes images using a wearable camera and an image processing unit. The array, fed by images through the camera transforms light signals into electrical impulses which in turn stimulates the retinal cells. Other prominent players in this sector are French organization Pixium Vision, Bionic Vision Australia research consortium, and Germany based Retinal Implant AG. Orthopaedic bionics Bionic limbs are by far the most widely used bionic products and have replaced prosthetics to a large extent. An advantage that bionic limbs have over prosthetics is their ability to render better motor functionality to damaged limbs. 3D printed bionic limbs are helping millions of people to fight their disabilities. Bionic limbs link a person’s neuromuscular system with the brain for various functions like flexing, bending and grasping. The UK based Open Bionics has built upon the popularity of superhero movies like Iron Man to create the Hero Arm, a 3D-printed bionic arm that includes fancy features like haptic vibrations, beepers, buttons and lights, besides the basic motor functionality enabling the feature. Myoelectric sensors embedded in the Hero Arm lets patients mimic hand-like movements as precisely as possible. Italian company Youbionic provides similar customized bionic arms. German company Ottobock is the market leader in bionic prosthetics, Having been associated with the production of bionic limbs for over 20 years. It was the first firm to have created a completely microprocessor-controlled lower limb prosthesis system. Hearing Bionics Cochlear hearing implants are the bionic systems used to assist people with severe hearing disabilities. Auditory bionics includes a microelectronic array implanted either in the cochlea or the brain stem. The external component of the auditory bionics includes one or more microphones and the sound processor that transmits sound signals as electrical impulses to the brain. The brain senses these impulses as sound signals and gives the person a sense of hearing similar to normal hearing. Professor Graeme Clark is credited with inventing the first cochlear implant system back in 1978. Today, Cochlear Limited in Canada is the global leader in the production of cochlear implant solutions. Neurological Bionics Although a tiny spec in the emerging market of 3D printed bionics, research in neurological bionics is gaining speed in recent years. After years of research, Bivacor, a private medical company has developed a bionic heart that runs on magnetic levitation technique. The bionic heart consists of a system that spins a disc at extremely fast speeds to pump blood to the body and return oxygen-depleted blood to the lungs. Scientists at the Tel Aviv University have claimed to 3D-print a miniature heart from human tissue that includes vessels, collagen, and biological molecules. This achievement has paved the way for further advancement in 3D printing of bionics and promises to be a game-changer in the field of healthcare. Bionic 3D printing market The bionic 3D-printing market is set to grow bigger in the coming years. A number of players such as Envisiontec Inc., Stratasys Ltd., Materialise, 3D Systems, Inc., Bio-Rad Laboratories, Organovo Holdings Inc., Simbionix USA Corporation, Metamason Inc., Youbionic, Bio3D Technologies Pte Ltd, and 3D Matters have emerged in the bionic 3D-printing arena over the years. The future of bionic 3D-printing lies in developing robotic exoskeletons made popular by movies like Iron Man. The bionic 3D-printing business not only targets physically disabled people but also aims at providing enhanced motor functionality to able people. Organizations are investing in research and development of such bionic exoskeletons that can enhance physical abilities for industrial applications and assist patients suffering from an acute neural disability or spinal injuries. To deep dive and stay continuously updated about the most recent global innovations in Additive Manufacturing and learn more about applications in your industry, test drive WhatNext now! Image Courtesy : english.tau.ac.il
Cloud robotics has been one of the most researched topics in the robotics space for the last few years. There is enough reason for enthusiasm. The possibilities of new business models and faster integration of AI and remote management capabilities have led to new ways of deployment of robots with customizable software. The sector has attracted all the major cloud providers like Amazon, Google and Microsoft who envision robots as the next sector to use the cloud backbone. Amazon has its RoboMaker platform, which mainly focuses on ROS based development with simulation so that the development can be done iteratively. But, the solutions now also consists of over-the-air updates of software and easy deployment of robots on-site. Google is developing its Google Cloud Robotics Platform that combines artificial intelligence (AI), cloud computing and robotics whose aim is to enable “an open ecosystem of automation solutions that use cloud-connected collaborative robots.” Similarly, Microsoft also is planning to get its Azure and Windows platform to robotics. Robotics-as-a-service (RaaS) is the new business model, robotics companies want to deploy the robots. This lowers the upfront cost for the customers and also gives leverage for the companies to generate service revenues with upgraded solutions and a large amount of data of operation helping in creating better robots. Other companies such as Honda, IBM, Huawei are also coming up with their open platforms to have a foot in the robotics market. Some market estimates show a robust 20-30% CAGR for cloud robotics market for the next 5 years. The incumbent industrial robotics players like KUKA, Yaskawa, ABB have also emphasized their research in the area of cloud robotics and it is getting integrated into many of their products. But, using OTA updates and tracking maintenance data is only scratching the surface of the possibilities presented by cloud robotics. Artificial intelligence at scale can be incorporated in a fleet of robots using a cloud backend. This is probably the most interesting application that could be possible if the cloud – robot communication is set up reliably. The robots could act as sensory data providers and much of the heavy-duty, AI-based data analytics can be done on the cloud. This allows the hardware setup at the robot to be cheap and minimal. Cobalt Robotics is one such startup which patrols building with robots for guarding premises and sends the streams of data to the cloud where AI-based algorithms can derive insights into making security operations better. Similarly, a few warehouse robotics startups are trying to sell a robotic fleet as complete automation. Taking this one step further, research is focusing on using the cloud infrastructure for transfer learning in a fleet of robots. This means that while training robots in a particular task using AI, the learning from one robot could be transferred to a cloud pool and other robots can then learn from the pool as well. This could be a new paradigm in much faster training for artificial intelligence and many complex applications can be developed for robots. Rapyuta Robotics, a startup spun-out from ETH Zurich and based in Japan is working in this domain. The big validation came for Rapyuta as Microsoft Japan, announced a partnership with the company for developing its cloud robotics platform on the Azure platform. Cloudminds, the pioneer in the cloud AI architecture for robots and business announced recently that it has received the order to supply over 10000 intelligent robots to Jin Yu Ao Environmental Technology and Zhongtai Min’an Security Services Group. Jin Yu Ao is a large scale cleaning services provider which is also heavily investing in the next generation 5G smart cleaning command center along with the Cloudminds technology. Zhongtain Min’an, on the other hand, is a security services and property management consultant. Cloudminds technology would be used here to make smart decisions in the cloud for cleaning and advanced property management solutions. Cloudminds, which is backed by Softbank, is also rumoured to be planning a $500 million IPO. Much of this shows the confidence in the growth in this sector. Acquisitions have also started in the space. Recently, Formant acquired Formation to integrate teleoperation into robotic fleet management. We believe, this kind of news will get prominent in this as well as the next year. With the 5G adoption becoming more widespread, the true potential of the cloud robotics technology will be realized. We would see robotics-as-a-service dominate the robotics market in the coming few years. To deep dive and stay continuously updated about the most recent global innovations in Robotics and learn more about applications in your industry, test drive WhatNext now! Image Courtesy :
The next best thing in the construction industry: 3D printers and eco-friendly concrete.
The fundamentals of construction have remained more or less unchanged since the last few decades, buildings/structures have been constructed. This includes a mason piling bricks with cement mortar mix. Few inherent challenges of the process are that it is highly dependent on the skills and speed of the manual worker. It takes a lot of time and releases dust, noise and waste as by-products. Efforts are being made to change these very fundamentals of the construction industry. 3D Printing in the construction industry or contour crafting has attracted the attention of technologists and engineers alike. With claims of printing entire houses in a matter of hours, the new applications of the two-decade-old additive manufacturing technology are not limited to prototyping or printing of spare parts of industrial machines/automobiles. Recent funding activity in the area of material development (UCLA granted $1.5M to develop eco-friendly concrete; Penn state receives a grant to commercialize concrete 3D printing system) signal increased interest of industry giants in the commercialization of the technology. Currently, the bricks are bound with cement. Cement production consumes a lot of energy and the process contributes a significant portion of the overall carbon emissions each year. UCLA has developed an eco-friendly concrete material that uses carbon-di-oxide as a part of its binder. The core team believes that with their process, the carbon footprint could be reduced to a large extent. The Penn state university is using the funds from the grant to test new reinforcement concepts for a recently developed printable concrete mixture. They claim that their printing methods have advantages such as minimized construction waste, faster construction, less labour, more economical construction and building in limited-resource areas or areas that are hazardous for humans. Start-ups across the world have shown significant technological breakthrough to achieve ensure that the technology is considered for wide-scale adoption. Paris based startup, Xtree offers construction 3D printer for rent and purchase. It has developed connected 3D printers and plans to have a worldwide network of such printers by 2025. The initiatives of China-based company Winsun date back to 2013 when it printed a series of 10 homes with its printers. 50% of its concrete mixture is waste gathered from the demolition of buildings. Cybe construction, a Dutch company has launched a mobile 3D printer to print at multiple locations. It includes a robotic arm provided by ABB that extrudes a concrete/mortar mixture that is deposited as desired. Winsun has entered in a partnership with the Dubai government to 3D print 25% of all the buildings in the Emirate by the year 2030. The initiative by the Dubai government can be seen as a very unique one to promote the city as a hub of global construction 3D printing. These initiatives and events have been followed by dialogues between governments and technology companies for wide-scale creation of buildings. The construction industry has been defined by the craftsmanship of architects, masons and civil engineers, generating complex structures with the knowledge of environmental factors and structural/material properties resulting in designs that leave the audience in awe. As mentioned earlier hand-production methods have been abundant. The technology can empower such proficient individuals to create unimaginable structures. Some benefits of the technology are listed below: Design Freedom: Computer-aided designing has bolstered the architects to create path-breaking models. However, such structures have been difficult to achieve because they were unattainable with legacy methods or were too expensive or labour-intensive. Robotic arms with multiple degrees of freedom, enable developing such designs with absolute ease. Reduction of steps: The traditional construction industry includes a range of steps (sub industries) such as raw material sourcing, brick/block making, tooling, and finally manual construction. This also includes wastage of unused material. With the robotic printing methods, the whole cycle narrows down to– Raw material sourcing, Material feeding in the printer and Printing. Thus reducing the overall time, efforts and labour needed. Worker Injuries: Traditional practices in the industry require extensive heavy lifting and manual work that has resulted in injuries and even deaths whereas robotic machines would require less manpower along with the provision of safe spaces to manoeuvre the robotic arms. Wastage: Since the robots extrude the mortar mixture based on the design instructions provided by architects, the waste of materials is radically reduced to a large extent. While the technology looks promising, debottlenecking these roadblocks will determine the success of technological cum governmental initiatives. Lack of regulation: Since this is a nascent technology, it could lead to the beginning of an anticipated infrastructural revolution. With every large scale business opportunity, a range of product/service providers try to have a slice of the pie. This may also result in a range of issues that are difficult to imagine today. Hence it is essential for governments/organizations to regulate the whole market, before setting off to develop the much celebrated, digitally constructed cities of tomorrow. High cost: As of now these printers are complex and large. The associated variable cost of construction of a building may surpass the cost incurred with conventional methods. However, it is hoped that with advances in technologies, smaller and cheaper printers would be made. Also, the wide-scale adoption of the technology will reduce the cost incurred per constructed structure. The amalgamation of traditional methods and robots: Since this is a new technology, the available materials are limited and a great deal of research is needed to ensure that the quality of final structures not just matches the quality provided by traditional methods, in fact, surpasses it. The overall design and construction calculation methods may change, based on the technology and the set regulations. In a nutshell, the technology looks promising, but the way these issues are handled remains to be seen. To deep dive and stay continuously updated about the most recent global innovations in Additive Manufacturing and learn more about applications in your industry, test drive WhatNext now! Image Courtesy :
Robots can perform a variety of tasks and automate a range of manual processes associated with growing crops. Harvesting, weeding, mowing, pruning, seeding, spraying, sorting, and packing are the areas where robots can be implemented. Deployment of agricultural bots is a highly compelling idea that offers high efficiency and round the clock operations. It offers the ability to scale up agricultural operations to thousands of hectares. Information regarding activities that occur in a farm can be collected via bots that are embedded with sensors. This would help to make the whole operation smarter, more efficient with a reduced waste of energy, water, chemicals and fertilizers. While traditional farming, equipped with scientific practices has led to some increase in food production levels, it is clearly not enough to satisfy the needs of the ever-increasing global citizenry. The need of the hour is to increase the productivity per hectare of land. Agricultural robots and automation is the way forward to achieve this goal. Classification of agribots based on application: These robots can be classified based on their application area. Weed removal bots to fruit picking bots to digitalising yield count and soil monitoring, agribots could enhance farming processes in just about every area of the sector. In general, robots used in agriculture can be categorized into four: Drones for surveillance Weed control Crop harvesting Planting and seeding Ways of deployment of agribots: Servitization farming The capital expenditure involved can be met by servitization. Adoption of a service-based model. This would serve as a beneficial pathway to all stakeholders involved that is between the agribot supplier and farmer, yielding valuable revenue and relationship opportunities. A robot is a very different machinery compared to traditional machinery. It is a complicated setup but can be operated by the service provider. Pay-as-you-go bots A fixed payment per hectare after initial deployment of the robot. Employment of a robotic system in farming that would autonomously look after feeding, seeding and weeding on farms and guarantees the result. Use of robots in agriculture in the future: The number of automated machines for agriculture would rise and this has already started with the advent of driver-less tractors. Companies like John Deere have already released prototypes of the same. One of the disadvantages of traditional farming is the usage of bulky machines doe’s soil compaction. These will be replaced by small mobile robots that do soil compaction only in a light manner and can provide individual plant attention. Drones can be used to provide aerial maps of farms. These can provide farmers with parameters that determine the agricultural yield. These include plant health, water stress levels and deficiencies in nutrients. Post-harvest, with the help of collaborative robots it would be possible to work with humans in further processing activities. Robots can be employed to perform activities such as labeling and keeping a track on the products throughout the supply chain. In a way, this will help to provide customers with information regarding the origin of the food and a faster way to address food safety issues. The collected data can be used as a feedback mechanism to improve quality. Robots can be employed for what is called selective harvesting. Harvesting only that part of the field that meets all required properties for a good yield. This can be done effectively with data collection, improved machine vision for recognition, segmentation, spatial localization and tracking. Ploughing is one of the tedious tasks in farming and eats up a lot of energy. Usage of small robots as said earlier prevents soil compaction. Local environment can be monitored using vision systems and seeds can be placed accordingly. Mapping and placing of seeds can be further optimized according to as per requirements for air, light, nutrients and ground moisture of the individual crop plants. Additional opportunities can be tracking of farming equipment thereby preventing theft and damage. Many ecosystems co-exist; robots can be made to ensure that these coexist with farming. The above-mentioned opportunities along with the acute availability of labour shortages and the possibility to implement a service-based model may well be the impetus the sector needs to adopt agribots. To deep dive and stay continuously updated about the most recent global innovations in Robotics and learn more about applications in your industry, test drive WhatNext now! Image Courtesy :