Autonomous mobile robots.

ABB has acquired Swiss start-up Sevensense, a leading provider of AI-enabled 3D vision navigation technology for autonomous mobile robots (AMRs). Sevensense was founded in 2018 as a spin-off from Swiss technical University, ETH Zurich.

“This marks a significant step towards our vision of a workplace where AI-enabled robots assist people, addressing our customers' needs for greater flexibility and intelligence amidst critical skilled labor shortages,” said Sami Atiya, President of ABB Robotics and Discrete Automation. “Each mobile robot, equipped with vision and AI, scans a unique part of the building; collectively these robots complement each other’s view to form a complete map, enabling them to work autonomously in a rapidly changing environment.”

The acquisition follows ABB’s minority investment in Sevensense after it joined the company’s innovation ecosystem in 2021, the same year ABB acquired ASTI Mobile Robotics. Financial details of the transaction were not disclosed. Following pilot customer projects in the automotive and logistics industries, ABB will integrate Sevensense’s technology into the company’s AMR portfolio, offering an unprecedented combination of speed, accuracy, and payload.

The market for mobile robots is expected to grow at 20 percent CAGR through 2026, from $5.5bn (€5bn) to $9.5bn (€8.66bn) and ABB’s AI-powered 3D vision technology is at the forefront of this growth.

Sevensense’s pioneering navigation technology combines AI and 3D vision, enabling AMRs to make intelligent decisions, differentiating between fixed and mobile objects in dynamic environments. Once manually guided, mobile robots with Visual Simultaneous Localization and Mapping (Visual SLAM) technology create a map that is used to operate independently, reducing commissioning time from weeks to days and enabling the AMRs to navigate in highly complex, dynamic environments alongside people. Maps are constantly updated and shared across the fleet, offering instant scalability without interrupting operations and greater flexibility compared to other navigation technologies.

Today, this AI-enabled navigation technology is already transforming the automotive manufacturing and logistics sectors, delivering value through faster and more efficient operations. For automotive manufacturer Ford, Visual SLAM enabled ABB AMR’s will create efficiency gains in production sites in the US, while Michelin will use the technology in intralogistics at its factory in Spain. Other automotive manufacturers will roll out the technology in Britain, Finland and Germany.

“Offering more autonomy and cognitive intelligence, ABB’s unique market-proven technology paves the way for a shift from linear production lines to dynamic networks. Intelligent AMRs autonomously navigate to production cells, tracking stock inventory as they go and sharing this information with other robots, while collaborating safely side-by-side with humans,” said Marc Segura, President of ABB’s Robotics Division. “With the acquisition of Sevensense, ABB becomes the leader in next-generation AMRs, offering Visual SLAM in Autonomous Mobile Robots, together with an integrated portfolio covering robots and machine automation solutions, all managed by our value-creating software.”

Gregory Hitz, CEO of Sevensense, said: “This is a significant moment in our shared journey, as we introduce our home-grown technology to a wider range of markets and sectors. ABB is the ideal home for us to continue scaling our versatile platform for 3D visual autonomy, serving OEMs across the automated material handling and service robotics industries. Together, we will redefine the limits of AI-enabled robotics.”

This revolutionary technology has the potential to impact robotics far beyond AMRs, leading to greater efficiency, flexibility and accuracy throughout production and intralogistics. The technology will also continue to be sold across segments including material handling, cleaning and other service robotics fields under the product name Sevensense.

The Sevensense partnership highlights the success of ABB’s commitment to nurturing the next generation of inno-vations. Through its partner ecosystem and collaboration with start-ups and universities, ABB develops leading technology for the benefit of global businesses. Sevensense’s approximately 35 employees will continue to be based at its Swiss office in Zurich.

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@ABBRobotics @ABBgroupnews @ABBMeasurement @abb_automation @7Srobotics @NapierPR #Automation #Robotics #AI

Accelerating workload consolidation.

Embedded solutions effectively reduce basic equipment and utilize more existing resources; furthermore, they also provide a highly flexible and scalable platform to meet the needs of various workloads, facilitating the integration of different devices and simplifying the architecture. DFI has taken the lead in jointly integrating ultra-compact embedded products, and Intel display chip processors to promote iGPU (Integrated Graphics) SR-IOV virtualization technology and commercialize modules.

With the current Software-Defined AIoT trend, hardware-supported virtualization technology is essential in the application environment. DFI products ranging from the industrial grade motherboard, ADS310, equipped with 12th generation Intel CPU, to the EC70A-TGU system and tablets, leverage virtualization technology to integrate and set up multiple virtual platform spaces. In addition to optimizing operations, it saves the cost of connecting data to the cloud and improves yield and efficiency.

DFI President Alexander Su said, “Benefiting from Intel’s technology and the support of SR-IOV architecture, the hardware can execute different operating systems through a single CPU and integrate large amounts of shared data. Due to substantial improvement in drawing performance within a virtual environment, features such as color recognition, measurements, and appearance flaw detection have increased in speed.”

Intel believes that cost considerations are a vital concern in industrial automation. DFI’s hardware can support SR-IOV virtualization technology. Through workload consolidation, it can improve cost efficiency, resolve the long term problem of graphics computing performance, and fulfill the needs of large-scale deployments in application fields.

DFI’s ECI and EIAMR products have been tested by Intel’s ESDQ, and DFI and Intel have released a technical white paper. Through working closely with Intel, DFI continues to assist and optimize the development of various services in IoT applications, accelerating the realization of Software-Defined IoT.

Smart poles and smart retail are also gradually moving toward the trend of workload integration. Smart Poles can identify pedestrian behavior with roadside and vehicle equipment and synchronize the data to the smart poles. Many devices can also execute high-performance AI edge computing and speed up people flow detection, people counting, monitoring, etc. Regarding smart retail, identification systems can be implemented to determine consumer age and gender to understand customers.

@DFI_Embedded @mepaxIntPR #AI, #PAuto 

Artificial intelligence in industry.

Using business AI applications in industry analysed by Henry Martel, Field Application Engineer, Antaira Technologies 

If there is an overarching technology theme to 2023 it is Artificial Intelligence. Despite its recent hype, however, Artificial Intelligence or “AI” is not a new concept. Its roots date back more than 70 years to a young British mathematician named Alan Turing. In 1950 Turing suggested that since humans have the innate ability to combine available information with reason to solve problems, why can’t machines?

Fast forward to the 1990s when Artificial Intelligence went from science fiction to science fact, thanks to landmark advancements in computational processing power, rule-based algorithms, neuroscience, and data storage capacity.

Today, artificial intelligence is being fully realized in industries as diverse as entertainment, manufacturing, finance, retail, and agriculture. AI can be found in autonomous vehicles, the optimization of pricing based on consumer and customer behavior alone, interactive chatbots like ChatGPT, automated financial planning, healthcare management, cybersecurity, Amazon product recommendations, and, countless other uses.

At the foundational level, AI is about extracting value from historical and real-time data. Data is a commodity that we have virtually no limit in our capability to collect, whether it's from sensors, cameras, or the importing of internal and external datasets. AI analyzes patterns hidden within “big data” in mere seconds and displays human-like cognitive processing in the form of reasoning, deep learning models, planning, and creativity to gain more contextual knowledge. For instance, the LinearFold AI developed by Baidu in 2020 was able to predict the RNA sequence of the COVID-19 virus in only 27 seconds, making it possible for researchers at that time to develop a vaccine.

Artificial Intelligence Subsets.
As with the human mind, AI is always learning. Each time AI performs a round of data analysis and processing, it tests and measures its performance and then uses those results to develop additional expertise in helping gain insight. This ability, better known as the AI subset Machine Learning, is constantly discovering new patterns and generating awareness from collected data. Other subsets of AI are:

• Neural Networks that utilize nervous system science,
• Deep Learning, which is like Machine Learning but uses a neural network of three or more layers,
• Robotics enabling advanced robot control and the robot's natural interaction with humans, and
• Computer Vision that trains computers to capture and interpret information from image and video data.

So how can AI improve your business? Let’s look at a few examples.

AI in Industrial Automation.
Perhaps more than any other field, Industrial Automation is a prime candidate for AI. Industrial automation already has many AI-driven systems with proven value. For example, asset monitoring in predictive maintenance is used in Industry 4.0.

Combining an existing industrial network with the capabilities of AI allows for more efficient and intelligent control of factory automation systems and business functions such as automatically adapting an assembly line to manufacture products that meet changing customer requirements. Complete inference solutions are now available that combine all the necessary hardware with ready-to-deploy AI algorithms in the cloud or in-house servers, eliminating the hurdle of having an inexperienced engineering team attempt to develop the algorithms themselves. Zero-touch AI devices connect to servers on power-up for instant configuration and real-time updates without any manual set-up by an on-site administrator. By being able to quickly and seamlessly interact with a factory’s IT infrastructure business processes, and automation systems, AI can hasten the adoption of autonomous mobile robots, collaborative robots, and computer vision systems, as well as the deployment of analytic tools including intelligent digital twins, order-controlled production, supplier selection, and predictive maintenance help drive operational efficiency and workplace safety.

AI in Agriculture.
AI in agriculture helps farmers ensure healthier food by minimizing the use of fertilizers, pesticides, and irrigation. All the while, it promotes greater crop yields and reduces the farm’s environmental impact on human resources.

Operating a farm requires collecting, analyzing, and using accurate data while monitoring hundreds of fluctuating variables that will determine a crop’s success. This data-intensive task is a natural fit for AI. AI will track and analyze variables ranging from weather patterns, hours of sunlight, planting cycles, and timing the migration of insects... to the use of fertilizers, insecticides, and irrigation systems. Data collected from in-ground smart sensors or from drones capturing real-time video streaming of fields can be integrated by AI with reports from the National Weather Service or the National Oceanic and Atmospheric Administration to make predictive analytics that assists in decision-making. AI can also predict potential yield rates of a given field before a vegetation cycle is ever started in a process known as yield mapping.

AI in Warehouse Management.

Applying AI in a warehouse or distribution center can guarantee accurate inventory data on-demand and a more complete understanding of customer requests in real-time. AI helps warehouses and distribution centers recognize their current situation by uncovering ordering patterns, tracking supply chains, and targeting areas to lower overhead costs. It also does away with antiquated Excel spreadsheets and time-consuming, overly complex formulas that always seem to come out wrong.

Modern warehouses deploy AI solutions for different technologies, such as automated robots (i.e; smart forklifts) that mimic human behavior, and software platforms for managing inventory management, material handling, processing and packaging, supply chains, and demand planning. AI interconnects all these different systems and technologies so they work in unison.

AI-driven robots, Automated Guided Vehicles (AGVs), and Autonomous Mobile Robots (AMRs) are today delivering tremendous value in warehouse operations. Robots can safely handle heavier loads than a human, and will more accurately pick, place and transport loads by following precise instructions and routes without experiencing fatigue or colliding with human workers. While they work AI-driven robots, AGVs, and AMRs actively collect data that enhances visibility across the enterprise, whether it is spotting recurring patterns that can predict possible inventory shortages, pinpointing root causes of equipment failures, or locating small, easily overlooked anomalies. Warehouse systems with AI become more innovative, faster, and more efficient in providing precisely what customers need on-time worldwide.

AI in Healthcare.
Artificial intelligence in healthcare has the potential to reshape the way patients are diagnosed, treated, and monitored, resulting in drastically improved outcomes and enabling more personalized treatments. Potential applications and business benefits of AI in healthcare are broad and far-reaching, from analyzing x-rays for early detection of disease to predicting outcomes from electronic health records. AI eliminates the need to manually record data, freeing up time otherwise spent on data entry.

In medical research, AI is being used to automatically collect patient biological data around the clock to establish massive databases. By analyzing vast amounts of clinical documentation quickly, AI helps doctors conducting research pinpoint disease markers that would otherwise be overlooked.

Industrial Ethernet Switches as AI Tools.
Leveraging AI’s competitive advantage in the business world requires mountains of data combined with high-performance networking muscle. This is typically driven by accelerators, Central Processing Units (CPUs), Non-Volatile Memory Express (NVMe) storage devices, and Network Interface Cards (NICs) connected to a GPU or PCIe Switch.

Industrial Ethernet switches also play a critical role in AI and data analytics by acting as a central station for all the connected devices to communicate with each other. Industrial PoE switches can supply up to 100W of power to Powered Devices, for instance, IP cameras, LED lighting, wireless access points, and remote IoT sensors detecting temperature, humidity, pressure, moisture, and other data shared with AI. Transmitted data collected by an industrial switch is applied to artificial intelligence and machine learning algorithms. High-speed, low latency industrial Gigabit switches are also finding a home in the distributed applications AI often requires, at times even replacing InfiniBand switches which have long been the preferred network interconnection technology for GPU servers.

As human decision-making and reaction times are increasingly proving insufficient for managing modern enterprises, AI is helping business leaders overcome shortcomings by delivering insights based on the analysis of all available information with unprecedented speed and accuracy.

@AntairaTech  #AI #Ethernet #Communications

FPGA machine vision.

Innodisk has announced its latest step into the AI market, with the launch of EXMU-X261, an FPGA Machine Vision Platform. Powered by AMD’s Xilinx Kria K26 SOM, which was designed to enable smart city and smart factory applications, Innodisk’s FPGA Machine Vision Platform is set to lead the way for industrial system integrators looking to develop machine vision applications.

Automated defect inspection, a key machine vision application, is an essential technology in modern manufacturing. Automated visual inspection guarantees that the product works as expected and meets specifications. In these cases, it is vital that a fast and highly accurate inspection system is used. Without AI, operators must manually inspect each product, taking an average of three seconds per item. Now, with the help of AI solutions such as Innodisk’s FPGA Machine Vision Platform, product inspection in factories can be automated, and the end result is not only faster and cheaper, but can be completely free of human error.

Innodisk’s FPGA Machine Vision Platform comes with 1GbE LAN, 4 USB 3.1 Gen1 ports, 2 M.2 slots, and a series of other expansion and connectivity options. Thanks to the platform’s 0° to 70 °C operational temperature support, and optional industrial temperature support from -40° to +85°C, EXMU-X261 is tough enough for the harshest of industrial environments. In addition, EXMU-X261 features support for Innodisk’s InnoAgent out-of-band remote management module, allowing the platform to be remotely managed from anywhere, even during a system crash or an in-band network failure. This is important for any automated system, as it allows for it to be completely unmanned, which further reduces manpower and maintenance costs.

Customers can take advantage of AMD’s Xilinx Kria K26 SOM’s ability to quickly get applications to market thanks to EXMU-X261’s full support for Innodisk’s AI Suite SDK. The suite includes an FPGA Model Zoo, as well as Innodisk’s in-house software solutions, such as iCAP (Innodisk Cloud Administration Platform), and iVIT (Innodisk Vision Intelligence Toolkit). iVIT for example, provides a deep learning environment for efficient development and deployment of “no-code-operation” solutions.

@Innodisk_Corp @mepaxIntPR #PAuto #Smart

Edge AI computer.

The RSC100, ARM-based Edge embedded PC featuring the Hailo-8 AI accelerator is now available from Impulse Embedded. This is a streamlined processing unit for AI applications that can offer up to 26 TOPs of int-8 performance in a cost-effective, power-efficient unit. The Edge system combined with Hailo-8 is suited for a wide range of uses including public safety, smart factory, agriculture and intelligent transportation.

The system chassis is made up of aluminium and heavy-duty steel with an IP40 rating and supports a wide operating temperature of -20°C to +70°C, ideal for use in harsh, industrial environments where the temperatures can vary throughout operation. Being an Edge device the RSC100 is kitted out with dual Gigabit Ethernet ports, an M.2 3052 B-key slot which can be used to install a 5G module and two full-size miniPCIe slots for expansion. The RSC100 also has seven SMA antenna breakout holes to meet the wireless comms requirements of your application.

The 8-core ARM processor is backed up with 4GB of LPDDR4 system memory and has 16GB of eMMC storage onboard as standard as well as an M.2 2280 M-key SSD slot with PCIe x4 NVMe support and a MicroSD card slot for additional storage. Further I/O includes a built-in HDMI 2.0 port with 4K resolution support, two serial ports supporting RS-232/422/485, two CANbus ports, two USB2.0 ports and 8-channels of digital I/O, (4-DI/4-DO). Embedded operating system support comes in the shape of Yocto Linux 3.0.

All of this I/O, software and connectivity combined with an AI focused microprocessor that uses just 2.5W whilst achieving 26TOPs of INT-8 performance, means the RSC100 can process complex deep learning neural networks out at the Edge in a wide range of smart embedded applications.

As with all of their embedded computing range, Impulse can fully configure the RSC100 to customer’s exact specifications in their engineering facility with a wide choice of storage, peripheral cards, operating system, and neural network.

@ImpulseEmbedded @proactivefleet #PAuto #Smart

Rapid roaming enhanced WiFi.

Rapid Roaming provides many of the same advantages of 802.11r wireless at a much lower cost in areas where necessary infrastructure does not exist.

Modern factories heavily rely on Artificial Intelligence (AI) driven processes in order to optimize every step of production. Often, the sensors used to collect data for AI were connected with slow cable-driven serial protocols with RS-232 cables or twisted pairs for RS-422/485. With the development of newer technologies, however, there has been a transition to Ethernet-based communication. Two main factors played a key role in this process: one, the price of Ethernet nodes went down with the advent of cheap microcontrollers that included fully integrated Ethernet communication hardware in one chipset, and two, sophisticated new sensors came to market that were not compatible with old serial buses.

Rapid Roaming WIFI
To solve these problems, WIFI communication has become a key technology to deliver metrics from sensors, providing freedom from cables and to allow unrestricted 3D movements by a client in motion such as a vehicle or robot.

The trouble is that 802.11ac wireless communication extends only 100 meters, a distance normally not sufficient for reliable service and requiring multiple access points (AP) be installed to cover a large area of operation. A moving vehicle or robot needs to constantly switch over communication to the next strong signal access point.

The best solution is the implementation of 802.11r across the infrastructure that manages the switch-over mechanism with below 50ms transition. However, some areas of a factory or warehouse may not support 802.11r. In this situation, Antaira's new Rapid Roaming enhanced WIFI client is an ideal solution, as it monitors surroundings and prepares new possible access points (APs) connection opportunities before die-down and drop-off connection processes take place. Supported by the new Antaira ARS-7235-AC-T dual-radio industrial WAP, Rapid Roaming protocols seek a new AP when communication is still healthy, assuring superior throughput and faster transitions with below 150ms switch time.

Steps of Fast Roaming

IEEE 802.11R Wireless Roaming
Roaming has been a desired feature in wireless devices for decades. In 2002, the IEEE 802.11r standard was introduced and is still under heavy development with major fundamentals published in IEEE 802.11r-2008. The main goal of 802.11r was to hand over wireless connections between numerous APs along a client travel path without significant delay. It has been particularly important for Voice over Internet Protocol (VoIP) applications where human conversation requires 50ms or better of transmission time to avoid undesired noticeable interruptions. The 802.11r standard allowed for speed with secure and seamless handoffs where authentication and Quality of Service (QoS) configurations were preconfigured ahead of switching to the next AP. It made for a stable throughput of data without delays caused by the regular authentication process.

To implement 802.11r, the wireless infrastructure needs to support this standard. This typically will require significant additional investment as most systems that support 802.11r must have a Wireless LAN Controller in addition to the APs that are then controlled by the Wireless LAN Controller. Applications where necessary infrastructure does not exist and there are cost restrictions, then Antaira Rapid Roaming technology can provide many of the same advantages at a much lower cost.

Steps of Fast Roaming
1) Authentication and QoS
a. In this step, two technologies are properly transitioning. Not just units are connected to one AP, but it has the same privileges in respect to communication priority. It is important in voice-over IP scenarios when delays could affect the human-to-human conversation.
2) Exchange 802.11r (2a - cable, 2b - radio)
a. This special protocol allows to exchange all necessary information ahead of travel path of a client. Making the transition smooth and fast.
3) Travel path
a. This is the way Client travels along the available APs

Infrastructure requirements for rapid roaming

Infrastructure Requirements for Rapid Roaming

1) Same Service Identifier (SSID)
2) Same Password
3) Same Security Mode
4) Sand Band
5) Same Channel Width

In order for the rapid roaming technology to work correctly, it is necessary to use an AP with the same SSID and security key. When rapid roaming is enabled, the client device will be configured to scan for the surrounding APs. It is necessary to set slow scan time intervals to specify relatively slow scans when Received Signal Strength Indication (RSSI) signal levels are high and the client device can comfortably concentrate on delivering the maximum data throughput. Next, specify the RSSI threshold level that will indicate an imminent need for a new connection. When this level is reached, the client device will be performing fast scans looking for a new AP. When it is detected it will authenticate and auto-connect to the new AP while simultaneously dropping the current connection. This active process eliminates weak signals deprived of links and prepares a new connection ahead when needed.

Warehouse application

Additionally, there are two modes of channels for scanning. One mode is “standard” and it works when all the channels are scanned. The other mode is “intelligent” and it works when a client device for example goes back and forth along the same APs. In this scenario, it can learn those APs channels and look for them automatically, further speeding up the reconnection process. 

Warehouse wireless system(Graphic 3)
One example of where this scenario plays out is in a warehouse application with autonomous robots that move about the warehouse stocking shelves and fulfilling orders. Here, a legacy WIFI network was already in place to support employees connecting their PCs, tablets and phones, but the network did not have the necessary equipment to support 802.11r. Antaira was able to provide the solution by fitting each of the robots with an ARS-7235-AC wireless router that could implement Rapid Roaming technology at a fraction of the cost of installing an entirely new wireless network.

@AntairaTech @OConnell_PR #PAuto #Communications

AI board instituted.

Global trade group to promote adoption of AI in industrial automation, focusing on new certifications, standards, education programs and events

The Association for Advancing Automation (A3) has created a new Artificial Intelligence (AI) Technology Strategy Board of leading AI experts, part of a major initiative to promote education and adoption of the applications of artificial intelligence in automation industries.

This new board places AI leadership at the same level as A3’s existing technology groups: robotics, vision & imaging, and motion control & motors. The AI Technology Strategy Board will be comprised of senior executives from leading AI and technology companies. This is the first time the global trade association has added a technology group to its leadership since adding motion control in 2006. A3 represents 1,100 companies from across the automation industry.

Last autumn, A3 hosted its first virtual AI conference, the AI & Smart Automation Conference, with more than 1,600 virtual registrants. Last year, A3 released the whitepaper, “Intelligent Automation: 6 AI Applications That Are Changing Industry.” Focused on real-world use cases for AI, the 20-page paper has become the most-read whitepaper in the history of the association. The association’s website has devoted an entire section to AI. AI technologies will play a central role at A3’s two major trade shows in 2022, The Automate Show & Conference, June 6-9, in Detroit, (MI USA), and The Vision Show, October 11-13, in Boston (MASS USA).

Artificial intelligence is layering atop robotics, vision, motion control, and other automation technologies to create new solutions, great flexibility, and expanding opportunities. Big tech companies—once focused more on phones than factory floors—now view manufacturing, robotics and industrial automation as key segments of their business.

“Artificial intelligence—in many shapes and forms—will be the stitching that weaves together a new age of industry,” said Jeff Burnstein, president of A3. “As the global trade group of the automation industry, we need to help prepare our members to seize this potential.”

The creation of the technology strategy board is the culmination of a three-year effort to educate and inform automation leaders about the growing importance of artificial intelligence. The board’s chairman is John Lizzi, Executive Leader-Robotics at GE Research, who has chaired and played a leading role in the A3’s AI efforts to date. Companies such as Amazon, GE, Google, Intel, Microsoft, NVIDIA, Siemens and others have helped guide A3’s initiatives. Robert Huschka, A3’s vice president of education strategies, will serve as the association’s liaison to the new board.

@a3automate #Automation #AI

Partnership bridges IT and OT worlds in mission-critical industrial environments

Lynx Software Technologies has announced a partnership with the CODESYS Group to provide a platform that can deploy industrial control automation technology on general purpose computer platforms alongside artificial intelligence (AI) / machine learning (ML), security and other application workloads.

The LYNX MOSA.ic™ for Industrial product, Lynx’s mission critical edge platform, provides virtual air gapping between the control automation and other workloads. The combination makes it possible for edge use cases that require mixed criticality workloads to be hosted on the same hardware platform.

The foundational building block in the LYNX MOSA.ic for Industrial product is the LynxSecure® Separation Kernel, which provides strong isolation of applications, deterministic real-time performance and management of critical system assets outside operating systems to increase immunity to cybersecurity attacks. In addition, Lynx has developed unique management technologies that allow mission critical edge systems to be deployed at scale and meet the unique requirements of systems that enable OT and IT convergence.

In the majority of current deployments, Information Technology (IT) and Operational Technology (OT) domains are separated by a demilitarized zone, the platform from Lynx and CODESYS can enable a software programmable logic controller (PLC), an ML/AI model, a human-machine interface (HMI) and an IoT Gateway workload to all run on the same edge system without hampering real-time performance.

“Our partnership with Lynx provides a bridge between the IT and OT worlds so industrial operators can now experience both functions coexisting on the same system while simultaneously meeting security and performance demands across every single edge workload in their mission critical industrial environments,” said Dieter Hess, co-CEO and co-founder of the CODESYS Group.

Benefits for industrial operators of the combination of technologies include: 

• Flexibility to deploy, manage and update workloads using the LynxSecure separation kernel hypervisor and its manageability features, following a consistent software lifecycle management, from the cloud to industrial endpoints
• Reduced system cost, power and footprint from the integration of multiple discrete systems into a single platform, while maintaining the real-time performance, reliability and safety demanded by OT networks
• Flexible management model of edge OT systems - devices can be managed from within the OT zone and host cloud managed and delivered workload alongside the CODESYS-based workload.

“By welcoming CODESYS into our growing industrial partner ecosystem we are able to solve an important challenge in the industry - that of enabling the software-defined world on the operational floor,” said Pavan Singh, vice president of product management, Lynx Software Technologies. “Now operators can leverage the best of new technologies developed in the information technology world while protecting and enhancing their current operations.”

• This partnership builds upon Lynx’s growing technology partner ecosystem to accelerate the realization of mission critical edge for industrial applications. Other recent news includes partnerships with Bosch Italia, Eurotech and the availability of Lynx MOSA.ic for Industrial in the Microsoft Azure marketplace.

@LynxSoftware @CODESYS_Group #Pauto 

Cutting-Edge applications in artificial intelligence.

Mouser Electronics has released Artificial Intelligence: The Next Wave in Life Sciences , the first eBook from The Intelligent Revolution series. In the new eBook, experts from Mouser and the life science industry explore cutting-edge applications for artificial intelligence (AI) in areas such as speech therapy, flu prevention, and wildlife protection. The captivating new AI series is the latest addition to Mouser’s award-winning Empowering Innovation Together™ program.

“We are excited to provide this type of enlightening content for our customers and followers. Artificial intelligence has revolutionized many high-profile industries, and we are now seeing this groundbreaking technology applied to new applications in life sciences,” said Kevin Hess, Senior Vice President, Marketing at Mouser Electronics. “This first eBook in The Intelligent Revolution series explores some of the most exciting new uses for AI in life sciences, as industry leaders highlight what has been achieved as well as what’s to come.”

Artificial Intelligence: The Next Wave in Life Sciences eBook features a fascinating article about Tanya Berger-Wolf, a computational ecologist at the Ohio State University, as well as insightful contributions from noted science writer David Freedman. The first article explores Berger-Wolf’s use of AI in matching photographs to specific animals, a critical function in wildlife protection. Specific animal matching enables scientists to determine whether a population is increasing or declining, and to determine how much funding and land should be allocated to protect the animal population.

Freedman’s contributions explore the role of AI in two medical applications: analyzing the sounds of coughs to track flu outbreaks, and identifying patterns in brain scans to predict the outcomes of speech therapy.

@MouserElecEU #AI #Health #Environment #LifeScience

Alliance for digital transformation.

Wunderlich-Malec Engineering (WM) and Quartic.ai have formed an Alliance to deliver smart manufacturing solutions for industrial applications using WM automation expertise and the Quartic Platform’s IIoT, Machine Learning and Artificial Intelligence (AI) capabilities.

Manufacturers who successfully apply AI will increase efficiency by an average of 12% in 5 years. Digitalization of manufacturing is therefore a key business imperative for all manufacturers. Shoring up local supply chains in the wake of the COVID-19 crisis has further increased the urgency to leverage these new powerful technology solution.

Quartic.ai, founded by a team of process manufacturing and reliability experts, has developed a platform that accelerates the deployment of machine learning and artificial intelligence applications when combined with subject matter expertise. WM’s deep domain expertise and knowledge of customer’s automation challenges will accelerate the delivery of value to these customers.

“Our mission is to keep building smart manufacturing technology. While ease of use and focus on subject matter experts are the key attributes of our technology, the value to the end users is delivered when subject matter experts use our platform to build valuable applications.” said Rajiv Anand, CEO, Quartic.ai. “End users have relied on and trust the expertise that WM brings to deliver technology-based integrated automation solutions. We are excited that this alliance will bring the value of our technologies to many more users.”

“Digitalization of process and operations is a top priority for our customers. Quartic.ai have proven the unique value their platform brings to industries like life-sciences, medical devices, chemicals, energy and mining. We are excited to deliver valuable applications built on this technology foundation and integrate them with the end-users’ automation and business management systems”, said Neal Wunderlich, President. Wunderlich-Malec Engineering, Inc.

@WunderlichMalec @QuarticAI #PAuto #IIoT

Investment in mining AI solutions.

BASF Venture Capital (BVC) is leading a strategic investment round in IntelliSense.io with follow-on participation from a group of British-based technology angel investors including Dr. Steve Garnett and Stephen Kelly. IntelliSense.io is a leading provider of AI-based solutions for the global mining industry. Its customers include mining majors and diversified mining groups.

To extract metals from the mined ores, mining companies must overcome two main challenges: First, today’s known ore deposits are increasingly difficult to mine, with declining ore grades and greater environmental challenges. Second, the composition of the orebody is not known with high accuracy. This variability impacts operational conditions and control, as well as plant performance and throughput. This is where IntelliSense.io’s technology comes in.

IntelliSense.io has combined the disciplines of mining expertise with software engineering and data science, enabling products to be designed by industry experts for end-users in the mining industry. The result is a unified technology platform, including a portfolio of process optimization applications spanning the entire mining value chain, from the mine to the plant and the markets. This is unique in the industry due to its breadth, scope and scale and it helps mining operations to become more efficient, sustainable and safe with accelerated value delivery. The platform also includes built-in simulation tools that can be used to test alternative operating conditions, train staff and run non-intrusive ‘what if’ scenarios.

BASF has a broad portfolio of mineral processing chemicals and technologies to improve process efficiencies and aid the economic extraction of valuable resources while offering global technical support to mining customers. In addition to the investment by BASF Venture Capital, BASF Mining Solutions has entered into an exclusive partnership with IntelliSense.io, bringing together their expertise in mineral processing, ore beneficiation chemistry and industrial artificial intelligence technology. The joint offering is called “BASF Intelligent Mine powered by IntelliSense.io” and delivers artificial intelligence solutions embedded with BASF mineral processing and chemical expertise.

“The world is becoming increasingly digital and artificial intelligence can make a vital contribution in many areas,” said Markus Solibieda, Managing Director of BASF Venture Capital. “The IntelliSense.io team offers a flexible and future-proof system which can help to optimize the metal lifecycle from extraction to processing to disposal. We believe in the IntelliSense.io team and the potential of this technology, and we are happy to support the further development and distribution of this innovative solution with our investment.”

Sam G. Bose, Founder and CEO of IntelliSense.io, commented: “Our fast-establishing leadership in industrial AI is driven by vertical industry-specific applications that require partnerships combining decades of industrial experience with emerging technologies. In the BASF group we are humbled to have found such a partner. We are delighted to have BVC’s support in building a category-leading industrial AI company and the capital raised will be deployed to increase our applications portfolio and support distribution capacity globally.”

 @IntelliSenseio @BASF #PAuto #AI

Digitally transforming the mining industry.

BASF and IntelliSense.io, the artificial intelligence (AI) company, has announced an exclusive partnership which will combine their expertise in mineral processing, ore beneficiation chemistry and industrial AI technology. The joint offering is called the ‘BASF Intelligent Mine powered by IntelliSense.io’ and delivers AI solutions embedded with BASF’s mineral processing and chemical expertise. This solution will enable mine operations to become more efficient, sustainable and safe.

“Our partnership with IntelliSense.io combines state of the art artificial intelligence and decades of ore beneficiation experience in to a powerful, fast and easy to deploy optimization platform,” said Damien Caby, Senior Vice President, BASF Oilfield Chemicals & Mining Solutions. “Efficiency improvements resulting from the first implementations by our joint dedicated team are helping customers accelerate the digital transformation of their mining operations.”

BASF Intelligent Mine powered by IntelliSense.io is an open, real-time, decision-making platform that can be configured for individual sites, typically within three months. Each mining process, such as grinding, thickening, flotation and pumping, is supported by an Optimization as a Service (OaaS) application which predicts and simulates future performance, generating process-specific recommendations for insights and optimization. As multiple OaaS applications link together, customers can generate efficiency gains throughout the entire mine-to-market value chain.

Remote operations access allows for 24/7 visibility of mine operational and financial performance, with BASF process experts available to provide real-time support. Additionally, the in-built simulation tool can be used to test alternative operating conditions, train staff and run non-intrusive ‘what if’ scenarios.

 Sam G. Bose (IntelliSense.io) and
Damien Caby (BASF Oilfield Chemicals & Mining) 

The AI solutions are based on a hybrid cloud architecture, enabling both on site and cloud deployments, to help mining industry partners accelerate their digitalization programs in their operations.

Early adopters of the Intelligent Mine, Image Resources, have experienced promising results from the Intelligent Mine deployment in the mineral sands industry. “Image Resources is both excited and optimistic about the potential the BASF Intelligent Mine powered by IntelliSense.io can have to positively impact the accuracy and efficiency of our process control functions to meaningfully improve our bottom-line,” said Patrick Mutz, Image Resources Managing Director. “From our experience so far, we are confident it will achieve these results whilst simplifying and de-stressing operational decision making.”

"In a tough economic climate, the need to focus on mining productivity, within sustainable and remote operational constraints, is driving pressure on operating and capex budgets and requires innovative solutions with accelerated value delivery,” added Sam G. Bose, CEO IntelliSense.io. “The partnership between BASF and IntelliSense.io ensures mining organizations have a partner that understands both their operational risk as well as new technologies.”

@IntelliSenseio @BASF #PAuto #Mining

Co-operation towards next-generation applications for artificial intelligence

Emerson and Quantum Reservoir Impact (QRI) have teamed up to develop and market next-generation applications for artificial intelligence (AI)-based analytics and decision-making tools customised for oil and gas exploration and production (E&P). Together, the two E&P software industry leaders will help oil and gas customers embrace digital transformation technologies and harness vast amounts of data to optimise their reservoir management strategies.

The collaboration combines the power of Emerson’s global reach and the world’s largest independent E&P software portfolio with QRI’s leading industry expertise in applying augmented AI, machine learning and advanced analytics for asset and reservoir management.

“The combination of our technologies and deep E&P expertise in offshore, unconventional and mature fields results in a robust offering that can give customers a significant advantage in the marketplace,” said Steve Santy, president for E&P software at Emerson. “Collaborating with QRI enhances our capabilities to give customers meaningful analytics to maximise production and capital efficiency and for better reserve assessment.”

As part of the ongoing collaboration, the companies will apply advanced computational technologies to help geoscientists and engineers make actionable and reliable field development decisions quickly, mitigating risks and leading to higher productivity and better performance.

“People, process and data are as important as technology to the success of the solution. Our partnership with Emerson makes for a very powerful team to ensure that our offerings will become a prominent choice in the market,” said Dr Nansen Saleri, QRI’s chairman, CEO and co-founder. “As our industry continues to transform, we share Emerson’s vision of applying state-of-the-art deep learning tools to automate next-generation workflows and offer our customers a rapid means of generating value.”

#PAuto  @QRIculture @Emerson_News @ParadigmLtd @EMR_Automation

Automated driving.

Xilinx and ZF have announced a new strategic collaboration in which Xilinx technology will power ZF’s highly-advanced artificial intelligence (AI)-based automotive control unit, called the ZF ProAI, to enable automated driving applications.

ZF is using the Xilinx® Zynq® UltraScale+™ MPSoC platform to handle real-time data aggregation, pre-processing, and distribution, as well as to provide compute acceleration for the AI processing in ZF’s new AI-based electronic control unit. ZF selected this adaptable, intelligent platform because it provides the processing power scalability and flexibility essential for the ZF ProAI platform to be customized for each of its customer’s unique requirements.

"The unique selling proposition of the ZF ProAI is its modular hardware concept and open software architecture. Our aim is to provide the widest possible range of functions in the field of autonomous driving," explained Torsten Gollewski, head of ZF Advanced Engineering and general manager of Zukunft Ventures GmbH. This approach is unique compared to other systems on the market, which use a fixed combination of hardware and software architecture – a solution that can potentially limit functionality and add more cost.

“We are proud to partner with ZF on its ProAI platform and help solve the challenges associated with autonomous vehicle development,” said Yousef Khalilollahi, vice president, core vertical markets, Xilinx. “By providing an adaptable hardware platform, ZF can design flexible and scalable systems that seamlessly incorporate AI compute acceleration and functional safety (FuSa) through diversity in processing engines. We look forward to expanding our collaboration with ZF to take autonomous and AI innovation to the next level.”

@XilinxInc @ZF_Group

AI drives Daimler forward!

Xilinx and Daimler AG are collaborating on an in-car system using Xilinx technology for artificial intelligence (AI) processing in automotive applications. Powered by a Xilinx automotive platform consisting of system-on-a-chip (SoC) devices and AI acceleration software, the scalable solution will deliver high performance, low latency and best power efficiency for embedded AI in automotive applications today.

“We are proud to announce this collaboration with Daimler on advanced AI applications,” said Willard Tu, senior director, Automotive, Xilinx. “Our adaptable acceleration platform for automotive offers industry leaders like Daimler a high level of flexibility for innovation in deploying neural networks for intelligent vehicle systems.”

Xilinx has a strong pedigree in automotive. For more than 12 years the company has shipped over 40 million cumulative automotive units to automakers and Tier 1 suppliers.

“We are accelerating our product development using AI technology by engaging our global development centers with Xilinx experts,” said Georges Massing, director user interaction & software, Daimler AG. “Through this strategic collaboration, Xilinx is providing technology that will enable us to deliver very low latency and power-efficient solutions for vehicle systems which must operate in thermally constrained environments. We have been very impressed with Xilinx’s heritage and selected the company as a trusted partner for our future products.”

As part of the strategic collaboration, deep learning experts from the Mercedes-Benz Research and Development centers in Sindelfingen (D) and Bangalore (IND) are implementing their AI algorithms on a highly adaptable automotive platform from Xilinx. Mercedes-Benz will productize Xilinx’s AI processor technology, enabling the most efficient execution of their neural networks.

@XilinxInc #Automotive @Daimler

AI integration added to suite.

"We welcome the industry old guards that validate our approach..."

IntelliSense.io has announced the integration of Artificial Intelligence (AI) to its applications suite. Having worked closely with the mining industry for two years as the sector’s innovation partner of choice, Intellisense.io understands and appreciates the challenges and benefits of delivering OaaS to an asset and process-intensive industry.

“I welcome Honeywell’s recent entry to provide optimisation as a service,” said Sam G. Bose, IntelliSense.io Founder and CEO. “This is the vision we pioneered from the start of our company. We have rapidly established a market leadership position, with our customers experiencing success and now demanding this approach.”

During the past 24 months Intellisense.io’s Industrial Internet of Things platform, Brains.app™, has delivered economic value with a rapid ROI to several mining majors. The mining industry has faced increasing pressure to reduce operating costs and improve yield. This is made significantly more difficult to achieve as a consequence of the continuous variation of incoming material composition.

“We welcome the industry old guards that validate our approach,” said Bose. “Whenever there is a technology revolution, new leaders emerge as the old guard fail to change sufficiently.”

The advantage of continuous optimisation, enabled by OaaS, ensures the software and data models incorporate the continually changing operating conditions to deliver the optimum process control variables in real time. Intellisense.io’s OaaS applications are delivered on an annual subscription basis with no upfront capital equipment expense.

“Honeywell UOP’s recent announcement launching their ‘optimisation as a service’ for the energy industry is a rapidly growing trend toward the future of process automation,” said Bose. “Cloud computing, the evolution of Internet of Things technologies and the more recent emergence of artificial intelligence are all combining to propel process automation to deliver continuous optimisation through OaaS applications.”

 @IntelliSenseio #PAuto #IoT