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What the Integration of Cognitive Twin Tech and IoT Will Mean for Consumers and Industry

The integration of cognitive digital twin technology with the Internet of Things (IoT) has the potential to revolutionize the marketplace by providing companies with valuable insights into their products and processes.

What is Cognitive Digital Twin Technology?

Cognitive digital twin technology is a virtual model of a physical system that uses data and artificial intelligence (AI) to simulate and predict the behavior of that system. This technology combines data from sensors and other sources with machine learning algorithms to create a digital representation of a physical system.

A cognitive digital twin model can be used to monitor and analyze the behavior of a system in real-time, and it can be used to simulate the behavior of that system under different conditions. By using this technology, companies can gain insights into the performance of their products, optimize their operations, and reduce maintenance costs.

What is the Internet of Things (IoT)?

The Internet of Things (IoT) is a network of physical devices, vehicles, home appliances, and other items that are embedded with sensors, software, and other technologies that enable them to connect and exchange data with other devices and systems over the Internet.

IoT devices can collect data from their environment, such as temperature, humidity, and pressure, and transmit that data to other devices or systems for analysis. By using IoT devices, companies can monitor their products and processes in real-time and gain insights into how they are performing.

The Impact of Integrating Cognitive Digital Twin Technology With IoT?

Cognitive digital twin technology can be integrated with IoT by using data from IoT devices to create a digital twin model of a physical system. IoT devices can provide data about the performance of a product or process, which can be used to create a digital twin model.

The digital twin model can then be used to simulate the behavior of the physical system under different conditions and to predict how the system will behave in the future. By using IoT data to create a digital twin model, companies can gain insights into the performance of their products and processes, and they can optimize their operations to reduce costs and improve efficiency.

There are several benefits to integrating cognitive digital twin technology with IoT, including:

  1. Predictive Maintenance: By using a cognitive digital twin model, companies can predict when maintenance is required on their products or processes, reducing downtime and maintenance costs.
  2. Improved Efficiency: By monitoring the performance of their products and processes in real-time, companies can optimize their operations to improve efficiency and reduce costs.
  3. Reduced Waste: With CDT, companies can reduce waste by identifying areas where resources are being wasted.
  4. Enhanced Product Design: By using a cognitive digital twin model, companies can simulate the behavior of their products under different conditions and make design changes in the earlier stages of R&D to improve performance, reduce costs, and cut time from POC to market.
  5. Improved Customer Experience: By monitoring the performance of their products in real-time, companies can improve the customer experience by identifying and addressing issues before they become major problems.

How the Market is Already Benefiting from Digital Twin and IoT Technologies

Many industries are already benefiting from the kinds of integration between CDT and IoT technologies. Chief among these is the transportation industry.

Cognitive digital twin technologies coupled with IoT are already proving invaluable for predictive maintenance of high-value military vehicles, airplanes, ships, and even passenger cars. For example, digital twin solutions like those developed by CarTwin extend the lifespan of cars and other vehicles by monitoring the vehicle’s “health” through its “digital twin.”

Basically, CarTwin can provide diagnostic and predictive models for all vehicle systems for which data is available (either directly or indirectly) onboard the vehicle.

Virtually any part of the vehicle that has sensors or that sensors can be developed for can be “twinned.” These data sets are then enhanced and augmented with design and manufacturing data that is already available by the OEM.

Primarily designed for use in fleets of vehicles, in combination with powerful AI models, CarTwin predicts breakdowns, monitors and improves performance, and measures and records real-time greenhouse gas emissions, which reduces expensive maintenance costs and avoids lost revenue associated with fleet downtime.

You can read much more about how AI and digital twin technology in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. While the book’s primary focus is on healthcare delivery, it also takes a deep dive into digital twin tech, with an entire chapter devoted to CDT, as well as IoT, and the development and launch of CarTwin!

Rohit Mahajan is a Managing Partner at BigRio and the President and Co-Founder of Citadel Discovery. He has a particular expertise in the development and design of innovative AI and machine learning solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

CarTwin has leveraged AI and Digital Twin technologies to create a digital, cloud-based clone of a physical vehicle designed to detect, prevent, predict, and optimize through AI and real-time analytics. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

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Startup Leverages AI to Challenge Google for Search Engine Supremacy!

Search engine technology startup You.com has announced the launch of YouChat 2.0, a groundbreaking new “multimodal conversational AI” system that the company says will take the internet search experience to “a whole new level,” leaving search engine giant Google wondering what happened!

The company says that YouChat 2.0 is the first web search that combines advanced conversational AI with community-built apps, offering a unique and interactive experience with each query. Its blended large language model, known as C-A-L (Chat, Apps, and Links), serves up charts, images, videos, tables, graphs, text, or code embedded in its responses to user queries. The idea is fewer open tabs and less drifting away from your search engine.

“We already have 150+ apps in our main search results page, but we’re now pulling more into the chat world and into this chat interface, which is non-trivial because you basically have to allow the chat model to decide when is best to answer a question by just showing you the facts,” said You.com co-founder and CEO Richard Socher in an interview with VentureBeat. “No one has done this yet — we’re the first to launch it to the world publicly.”

Socher knows a thing or two about groundbreaking advances in natural language processing (NLP), the technology that underpins all popular search engines. According to Google Scholar, Socher is currently the fourth most cited researcher in the field. As former chief scientist (and EVP) at Salesforce and former adjunct professor at Stanford’s computer science department, Socher has built his career on novel NLP applications. He now thinks it’s time to reimagine the way we interact with traditional search engines.

“Google has done incredible research and propelled the field forward in many dimensions in terms of its research, but they are making $150 billion a year by invading your privacy and showing you ads on a search results page,” Socher said, appearing visibly frustrated with the current state of affairs. “So when you develop technology, that would work great if, instead of six ads, you had one ad, but [if] it means you lose $500 million a day, you’re probably not incentivized to launch that new technology into the world.”

“It’s the classic innovator’s dilemma,” he added. “Google is very good at running things not profitably for a long time, like Maps and YouTube, and then pulling ads into it. The problem is this particular technology changes their core product.”

The company invites developers to submit apps to its open platform and work together to create the ultimate chat-search-do engine. Developers can learn more at You.com’s developers page.

How BigRio Helps Bring Advanced AI Solutions to the Internet Experience

The announcement of YouChat 2.0 by You.com is yet another example of how innovative startups are advancing the ubiquity of AI and NLP. AI algorithms are already “running behind the scenes” of most of our internet and social media experiences, and soon they will be little or no separation between Internet of Things applications, chat, and AI, with one very much totally reliant on and integrated with the other.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve the digital world.

In fact, we like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting out in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the Sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the expertise to not only weed out the companies that are not ready for the market, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the AI investment community.

You can read much more about how AI is redefining the Internet of Things in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. While the book’s primary focus is on healthcare delivery, it also takes a deep dive into AI in general, with specific chapters on IoT and NLP technologies.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

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Digital Twin Technology Being Used to Create Next-Gen Aircraft

Digital twin technology is becoming more and more mainstream, particularly when it comes to the maintenance and monitoring of complex mechanical systems such as aircraft.

GENEX, an EU-funded startup, has announced the creation of a new digital twin framework that will be used to create “the next generation” of safer and greener composite aircraft.

Launched on Sept. 1, 2022, GENEX is a 42-month, 5.7 million Horizon Europe collaborative research project seeking to develop an end-to-end digital twin-driven framework for optimized manufacturing and maintenance of next-generation composite aircraft structures.

According to the company, “enhanced computational models will embed interdisciplinary knowledge of aircraft components and manufacturing/repair processes to support their optimization as well as enable data management and monitoring across the entire life cycle of the aircraft’s operation.”

GENEX will really ramp up in the New Year. It is projected to run through 2026.

According to a company press release about the initiative, “The core of the GENEX project is based on three [digital twin] blocks focused on different facets of the aircraft use life, which, eventually, will be integrated into a fourth to form the multidisciplinary digital twin.”

Each block is as follows:

     • Block 1 – Manufacturing Process Digital Twin: An automated tape laying (ATL) process, coupled with hybrid-twin simulation methods, will be developed for the eco-efficient and advance manufacture of recyclable thermoplastic composites.

      • Block 2 – Product Usage Digital Twin: Data- and physics-based machine learning (ML) algorithms for damage detection and location, combined with high-performance computing (HPC)-based multi-physics and AI-powered digital twin tools for fatigue life prediction.

      • Block 3 – MRO Digital Twin: Augmented reality tools, together with novel laser-assisted methods for surface cleaning and monitoring, smart monitoring, and in-situ tailored heating of composite repair blankets, will be further developed to provide additional assistance in manual scarf repair operations, increasing the reliability of the repair process, while supporting the modification and virtual certification of MRO practices.

    • Block 4 – Cognitive Digital Twin: Combined integration of blocks 1-3 for the realization of a digital twin-drive framework implemented into a common industrial internet of things (IIoT) platform.

“The aviation industry is facing a two-fold challenge — targeting carbon neutrality while also adopting the digitalization of next-generation aircraft,” Dr. Calvo-Echenique says. “In GENEX, we hope to provide the needed technological impulse to optimize composite components manufacturing, and operation and repair processes using digital twin strategies.”

Other Industries Benefiting from Digital Twin Technologies

As you can see from the GENEX project, AI and digital twinning are revolutionizing many industries, chief among them transportation. Cognitive digital twin technologies are proving invaluable for the predictive maintenance of high-value military vehicles, airplanes, ships, and even passenger cars. Digital twin solutions like those developed by CarTwin extend the lifespan of cars and other vehicles by monitoring the vehicle’s “health” through its “digital twin.”

Basically, CarTwin can provide diagnostic and predictive models for all vehicle systems for which data is available (either directly or indirectly) onboard the vehicle.
Virtually any part of the vehicle that has sensors or that sensors can be developed for can be “twinned.” These data sets are then enhanced and augmented with design and manufacturing data that is already available by the OEM.

Primarily designed for use in fleets of vehicles, in combination with powerful AI models, CarTwin predicts breakdowns, monitors and improves performance, measures and records real-time greenhouse gas emissions, which reduces expensive maintenance costs and avoids lost revenue associated with fleet downtime.

Rohit Mahajan is a Managing Partner at BigRio and the President and Co-Founder of Citadel Discovery. He has a particular expertise in the development and design of innovative AI and machine learning solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

CarTwin has leveraged AI and Digital Twin technologies to create a digital, cloud-based clone of a physical vehicle designed to detect, prevent, predict, and optimize through AI and real-time analytics. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

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