Increased Manufacturing of Autonomous Vehicles to Provide Lucrative Opportunities for AI in Computer Vision Market Growth During Forecast Period

Computer vision is a fundamental technology for developing autonomous or self-driving vehicles. It provides the necessary perception capabilities, enabling vehicles to navigate and operate safely without human intervention. Computer vision algorithms can interpret complex visual data, including traffic signs, lane markings, traffic lights, and road conditions. This allows autonomous vehicles to make informed decisions about their movements and adjust their behavior accordingly. Computer vision is at the center of autonomous vehicle technology. By leveraging object detection algorithms while also using the latest cameras and sensors, autonomous vehicles get to identify their surroundings, making the entire driving process safer. Computer vision models allow autonomous vehicles to stop before they hit walkers or cyclists. Various companies are launching new autonomous vehicles. For instance, in June 2023, Volkswagen planned to launch autonomous, or self-driving, vehicles for ride-hailing and goods delivery services in Texas. Also, Volkswagen planned to test 10 ID Buzz electric vehicles retrofitted with Mobileye's autonomous driving platform with safety drivers on board in limited areas of Austin, including downtown. Similarly, in June 2023, Minus Zero unveiled the zPod, which it claimed to be India's first autonomous vehicle. The zPod showcased self-driving tech developed by the artificial intelligence (AI) firm. Minus Zero said that it would provide its autonomous driving tech to other manufacturers to help improve their ADAS suite. In addition, in February 2021, Luxury carmaker Jaguar Land Rover announced the opening of three new engineering hubs to develop autonomous vehicle technologies in Europe as part of its partnership with Silicon Valley artificial intelligence company Nvidia (NVDA.O). The hubs in Munich, Bologna, and Madrid develop self-driving systems for JLR's next generation of luxury vehicles. Therefore, the increasing manufacturing of autonomous vehicles is anticipated to provide growth opportunities for the AI in computer vision market.

Key Findings of AI in Computer Vision Market Study:

AI in computer vision market is segmented into component, end-use industry, and geography. Based on component, the AI in computer vision market is segmented into hardware and software. In terms of end-use industry, AI in computer vision market is segmented into security & surveillance, manufacturing, automotive, retail, sports & entertainment, and others. By geography, the AI in computer vision market is segmented into North America, Europe, Asia Pacific, the Middle East & Africa, and South America.

Based on end use industry, the AI in computer vision market is categorized into security and surveillance, manufacturing, automotive, retail, sports and entertainment, and others. The security and surveillance segment held the largest share in the AI in computer vision market. Security cameras and scanning devices utilize computer vision algorithms to recognize faces and detect objects. Additionally, using computers can help prevent mishaps. In strategic locations, authorities can make use of these technologies. It can also be utilized in surveillance traffic cameras. Nowadays, CCTV cameras are fitted in almost every place, such as roads, streets, shops, highways, and stores, to spot various suspicious or criminal activities. It helps provide live footage of public places to identify suspicious behavior, spot dangerous objects, and prevent crimes. Several players are providing computer vision platforms for security and surveillance. For instance, the company viso.ai provides computer vision smart city applications, which includes perimeter monitoring and person detection, roadside surveillance application, and weapon detection and reporting.

The automotive segment is expected to grow with the highest CAGR in the AI in computer vision market over the forecast period. For self-driving automobiles to be possible, computer vision is required. In order for their self-driving cars to recognize objects, lane markings, signs, and traffic signals and drive safely, automakers such as Tesla, BMW, Volvo, and Audi utilize lidar, radar, numerous cameras, and ultrasonic sensors to capture images from the surrounding environment. Several players across the globe are introducing AI in computer vision for the application of advanced driver assistance systems (ADAS). For instance, as of January 2022, Qualcomm Technologies, Inc. introduced the Snapdragon Ride Vision System, a scalable and modular computer vision software stack built on a 4-nanometer process technology system-on-chip (SoC). The software is designed for an optimized implementation of front and surround cameras for advanced driver assistance systems (ADAS) and automated driving (AD).

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