How DeepScenario and Intel OpenVINO Create Digital Twins
Concerning DeepScenario
DeepScenario, an Intel Ignite and Intel Liftoff startup, uses artificial intelligence (AI) to establish the crucial connection between the real and virtual worlds, enabling industry-specific solutions in dynamic contexts. This enables businesses like Volkswagen, Bosch, and Torc Robotics to establish a continuous loop that involves observing the real world, comprehending its dynamics, and applying this understanding to their unique applications, like autonomous driving.
A basic computer vision programme from DeepScenario is utilised to do this. Videos of the real world are transformed into a dynamic virtual counterpart using highly developed algorithms and commercially available cameras, laying the groundwork for the related application.
The Problem Applications requiring a dynamic digital counterpart of the world are multiplying. This makes it possible to automate processes, cut expenses, and increase the functional scope. Digital twins of road traffic are required, for example, in order to test car software in a simulated environment and advance autonomous driving.
Another example is the transportation sector, which uses real-time digital twins to control traffic in cities and monitor parking space occupancy. Significant obstacles stand in the way of current techniques, such as limited application due to simplifying assumptions or limited scalability because of costly sensor sets.
The Resolution This is the exact situation that Stuttgart-based AI startup DeepScenario finds itself in. Using its 3D computer vision software, DeepScenario creates dynamic virtual worlds out of films. Because it uses widely available cameras and a 3D methodology to assure generalisation, the solution is incredibly scalable.
For example, the automotive sector makes use of DeepScenario’s AI technology. Here, videos from cars, traffic cameras, or drones are transformed into dynamic digital twins of road traffic using the industry-leading algorithms from DeepScenario. Next, new car software is trained and tested in these virtual environments through simulation.
The software developed by DeepScenario can also be applied to transportation-related applications. This involves using already-installed cameras to precisely monitor parking lots, for instance. All objects in the scene are immediately recognised by the programme, which tracks them over time with centimetre accuracy in 3D. DeepScenario’s algorithms, in contrast to current 2D-based techniques, can accurately ascertain the position, orientation, and dimensions of the objects in 3D without the use of extra sensors like LiDAR. They can use this to determine possible parking infractions or infer the occupancy of a parking place in real time.
Additionally, DeepScenario’s software can be used to develop entirely new services, such as automated valet parking. Such a service was just introduced by Bosch Mobility.
With DeepScenario’s AI technology, numerous new use cases are possible, such as applications for logistics or intelligent traffic control.
DeepScenario for Edge Intel Tools Intel has made it possible for its software to run in real time on edge servers in a very short amount of time by using Intel tools. With over a billion fixed cameras and a volume of roughly $15 billion, this creates a market for us that is likely to develop.
What is OpenVINO The optimised interface of DeepScenario’s software with Intel hardware which makes use of tools like the Intel OpenVINO Toolkit is another advantage. The inference of AI applications on Intel hardware is accelerated by this open-source software, particularly when creating and utilising deep learning-based AI models like those from DeepScenario.
Intel OpenVINO Increasing the Usability of Generative AI in Practical Situations The OpenVINO toolbox is an open-source toolkit that maintains accuracy, minimises model footprint, and maximises hardware utilisation while speeding up AI inference with lower latency and faster throughput. Large language models (LLM), generative AI, computer vision, and deep learning integration are among the areas it simplifies and integrates more easily.
Intel Geti Platform With the help of this for-profit software platform, enterprise teams can create vision AI models more quickly. Businesses may use the platform to create models with little data, and by integrating OpenVINO, it makes it easier to deploy solutions widely.
Software & Solutions Catalogue for AI Inference Examine ISV solutions built on OpenVINO when you’re prepared to launch your solution. This ebook is divided into parts, like banking or healthcare, to make it easier for you to traverse the options table and select the solution that best fits your use-case demands.
In actuality, DeepScenario and Intel SceneScape work together to provide a smart parking solution that is a shining example of their teamwork. This method uses just existing monocular cameras to build realistic 4D digital twins of parking lots by utilising the OpenVINO toolset. Apart from surmounting the constraints of conventional techniques, it is also applicable to a range of uses such as intelligent traffic control, port surveillance, and Industry 4.0 programmes.
Additionally, DeepScenario and the autonomous driving area benefit greatly from Intel’s funding of the Carla Simulator’s development.
Intel Ignite With the help of Intel, Intel Ignite, and the Intel Liftoff programme for AI companies, DeepScenario is setting new standards in the creation of dynamic virtual environments from real-world recordings thanks to its AI technology. The methodology employed by DeepScenario is very scalable and has numerous applications. Utilising 3D algorithms creates new technological opportunities, of which DeepScenario has already shown to be indispensable in the transportation and automotive sectors.
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