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Cyber Physical system to Digital Twin – Recent Advances and Trends for Autonomous Vehicles

Edge AI

AI algorithms are processed locally, either directly on the device or on the server near the device. The algorithms utilize the data generated by the devices themselves. Devices can make independent decisions in a matter of milliseconds without having to connect to the Internet nor the cloud. Edge AI has almost no limits when it comes to potential use cases.

Expandable AI

Explainable AI is an important part of artificial intelligence. It provides humans with the ability to explain how decisions are made by machines. This helps people trust and understand what’s happening, instead of feeling like their information is being taken advantage of or used without their permission. In this blog post, we’ll explain explainable AI and explain it with examples so you know how it works!

Cyber Physical System

The term cyber-physical systems (CPS) refers to a new generation of systems with integrated computational and physical capabilities that can interact with humans through many new modalities. The ability to interact with, and expand the capabilities of, the physical world through computation, communication, and control is a key enabler for future technology developments. Opportunities and research challenges include the design and development of next-generation airplanes and space vehicles, hybrid gas-electric vehicles, fully autonomous urban driving, and prostheses that allow brain signals to control physical objects.

Concept map of CPS

Cyber-Physical Systems (CPS) are integrations of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. The economic and societal potential of such systems is vastly greater than what has been realized, and major investments are being made worldwide to develop the technology. The technology builds on the older (but still very young) discipline of embedded systems, computers and software embedded in devices whose principle mission is not computation, such as cars, toys, medical devices, and scientific instruments. CPS integrates the dynamics of the physical processes with those of the software and networking, providing abstractions and modeling, design, and analysis techniques for the integrated whole.

Digital twin

Digital twins have become important to business today. By producing a replica of the physical assets of a product or service in an industry, digital twin helps in analyzing the data, lends a platform to check the functioning beforehand so as to develop a solution for any potential problems. The term came into existence when Michael Grieves, then computer engineer at the University of Michigan, wrote about it in 2002 and was named one of Gartner’s Top 10 Strategic Technology Trends for 2017.

Core technologies

A digital twin is a digital representation of a physical object, process or service. A digital twin can be a digital replica of an object in the physical world, such as a jet engine or wind farms, or even larger items such as buildings or even whole cities.As well as physical assets, the digital twin technology can be used to replicate processes in order to collect data to predict how they will perform.

A digital twin is, in essence, a computer program that uses real world data to create simulations that can predict how a product or process will perform. These programs can integrate the internet of things (Industry 4.0), artificial intelligence and software analytics to enhance the output.With the advancement of machine learning and factors such as big data, these virtual models have become a staple in modern engineering to drive innovation and improve performance.

In short, creating one can allow the enhancement of strategic technology trends, prevent costly failures in physical objects and also, by using advanced analytical, monitoring and predictive capabilities, test processes and services

Applications

NASA was the first to leverage the digital twin technology, when Michael mentioned the possibility of creating digital representations of physical systems that had their own entity during a talk with John Vickers, NASA’s Director of Technology. The key objective was to devise a solution that can enable it to mend or update or check on a machine in outer space where it is practically impossible to be physically present at any given point in time. This inspired NASA to develop a virtual replica that can work from the desired place and can fetch real-time data. Today, NASA uses digital twins to develop new recommendations, roadmaps, and next-generation vehicles and aircraft.

AR and VR in digital twin

Augmented reality (AR), virtual reality (VR) and digital twins are on the cusp of enabling businesses to visualize key insights about their operational technologies. The ability to view both physical and virtual environments are an untapped boon for industries like manufacturing, transportation, and energy, where heavy machinery and other physical equipment often lies at the centre of business operations. The term “Industrial Internet of Things” (IIoT) refers to the use of intelligent assets, such as sensors, to connect other physical assets to the network for collecting and analyzing data in industrial settings. But technologies like digital twins, VR, and AR help organizations pursue industrial automation in a very different way.

XR in digital twin

XR is an emerging umbrella term for all the immersive technologies. The ones we already have today—augmented reality (AR), virtual reality (VR), and mixed reality (MR) plus those that are still to be created. All immersive technologies extend the reality we experience by either blending the virtual and “real” worlds or by creating a fully immersive experience. Recent research revealed that more than 60% of respondents believed XR will be mainstream in the next five years. To get a better picture of XR, let’s review each of the existing technologies that exist today.

Electric vehicle

All-electric vehicles (EVs), also referred to as battery electric vehicles, use a battery pack to store the electrical energy that powers the motor. EV batteries are charged by plugging the vehicle in to an electric power source. Although electricity production may contribute to air pollution, the U.S. Environmental Protection Agency categorizes all-electric vehicles as zero-emission vehicles because they produce no direct exhaust or tailpipe emissions. Tesla designs and manufactures electric cars, battery energy storage from home to grid-scale, solar panels and solar roof tiles, and related products and services.

Future directions

The key benefits pursued are improvements in driving security and overall safety (through driving assistance, crash avoidance systems and overall reduced human error), higher vehicle reliability with devices fitted with onboard diagnostic systems (OBD), better human-machine integration using speech recognition and operational improvements including reduced traffic congestion, optimized freight flow and traffic control, overall improved mobility, etc.

REFERENCE:

Edge AI

https://www.advian.fi/en/what-is-edge-ai

Explainable AI

https://vitalflux.com › what-is-explainable-ai-concepts-exa.

Cyber physical system

Baheti – Cited by 1336

Concept map of CPS

https://ptolemy.berkeley.edu/projects/cps/

Digital twin

https://www.analyticsinsight.net › understanding-the-impo

Core technologies