The Edge AI Software market is expected to grow from USD 684.18 Million in 2020 to USD 4458.07 Million by 2028, at a CAGR of 26.4% during the forecast period 2021-2028.
AI algorithms are processed directly on a hardware device using Edge AI Software. Data created on a device is used by the algorithms. A device does not need to be linked to the internet. It has the ability to process data and make judgments without the need for a connection. Edge AI software is designed to work with devices that have a microprocessor and sensors.
Edge AI enables real-time processes such as data production, decision making, and execution in situations when milliseconds are critical. Self-driving cars, robotics, and a variety of other applications can all benefit from real-time operations. Edge AI also tends to save data connectivity costs by reducing the amount of data sent. The data’s privacy is not affected by local processing.
Edge AI is very popular in the telecom industry, and the integration of the 5G network with telecoms provides a multitude of potential for edge AI integration with telecom. In a variety of industries, a huge number of AI edge applications have arisen. AI automates these processes for businesses, making it a driving force in this market. These applications require a large processing capacity in order to perform tasks such as real-time data acquisition and analysis. Edge AI overcomes the speed problems that concern other types of AI running on cloud platforms by putting processing resources at the network’s edge. As a result, the programmes can run with low latency and high bandwidth. This feature of edge AI software encourages more enterprises to include edge AI into their ecosystem, hence raising market demand. The Edge AI Software Market is expanding as a result of increased automation and the use of wearable devices. Edge AI software is gaining popularity among organisations because it supports essential AI applications such as self-driving cars and robots. However, because the edge nodes will connect with one another and share real-time data, security is a major worry with edge AI systems. The surge in security breaches, attacks, and Distributed Denial of Service (DDoS) on infrastructure such as routers, base stations, and switches is limiting the deployment of edge AI solutions. With the launch of the 5G network, however, IT and telecoms are converging, giving tremendous opportunities for the Edge AI Software Market in the next years. Furthermore, the expanding use of edge AI software in autonomous vehicle applications may present opportunities for edge AI software vendors.
Some of the major players operating in the global edge AI software market are IBM, Intel, Microsoft, Google, Octonion SA, TIBCO Software, Cloudera, Foghorn Systems, Synaptics, Anagog, and Eta Compute. To achieve a large market position in the worldwide Edge AI Software market, leading companies are increasingly focused on strategies such as product innovation, mergers and acquisitions, new advancements, joint venture, collaborations, and partnerships.
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The Telecom segment dominated the market with the largest market share of 29% in the year 2020.
Based on Vertical, the market is segmented into Healthcare, Telecom, Energy and Utilities, Automotive, Manufacturing, and Others. The telecom segment dominated the market with the largest market share of 29% in 2020. Edge AI software is employed in the telecom business for a variety of reasons, including 360-degree insight across connected devices, contextual push intelligence, and the availability of productivity tools in a specific location. Because of the growing number of internet users worldwide, connected networks have been modernised, allowing edge AI software to give enhanced working capacity. Previously, telecom businesses operated networks on hardware systems, but with edge AI software, the telecom industry can easily handle an increasing number of linked devices. Another attractive area for edge AI software installation and deployment is the increase of autonomous vehicles equipped with voice control.
The Video Surveillance market dominated the market with the largest market share of 35% in the year 2020.
Based on application, the Edge AI Software Market is segmented into Autonomous Vehicles, Access Management, Video Surveillance, Remote Monitoring and Predictive Maintenance, and Telemetry. The Video Surveillance market dominated the market with the largest market share of 35% in the year 2020. Edge AI for video surveillance has significantly boosted administration and monitoring while reducing the amount of raw data supplied to the cloud, resulting in its expansion. Edge AI enables machine learning intelligent camera systems to collect raw data, interpret it, and analyse it using facial recognition to detect persons of interest and dubious actions occurring directly at the edge.