The surge in the number of applications deployed on the cloud across multiple industries, rapid improvements in the IoT space, advancement in numerous smart applications, and the increasing popularity of AI software are the major factors driving the growth of the global edge AI software market. According to relevant data reports, due to these factors, the market generated revenue of US$600 million in 2020 and is expected to witness huge growth during the period 2021-2030.
Pandemic boosts edge AI software market
Several countries have implemented lockdowns to mitigate the spread of COVID-19 infection, which has negatively impacted the operations of many businesses but has had a positive impact on the growth of the edge AI software market.
The COVID-19 pandemic has spurred progress in the healthcare services industry, with many organizations making huge investments in edge AI software to increase its use in the field. In addition, as the rate of digitization in the medical and training fields continues to increase, the demand for edge AI software is also rising sharply.
However, increasing security and piracy issues have hindered the market growth as data is stored in various micro-data centers at edge nodes, which share real-time data with each other and are highly vulnerable to cyber attacks.
The global edge artificial intelligence software market is segmented on the basis of data source into categories such as speech recognition, sensor data, mobile data, biometric data, and video image recognition. Among them, the video and image recognition categories will dominate the market until 2030.
This is due to the increasing number of image recognition and AI-controlled video applications, such as facial recognition and motion detection cameras for security reasons, as well as the rapid application of edge AI in video surveillance to prevent data theft. occur.
Video surveillance category leads the market in 2020
Furthermore, the global edge artificial intelligence software market is segmented on the basis of application into access management, autonomous vehicles, remote monitoring and predictive maintenance, video surveillance, energy management, and telemetry. Among them, the video surveillance category led the market in 2020.
The growing need for higher security and system detection is driving the need for edge artificial intelligence in video surveillance. The self-driving car category will expand rapidly in the coming years due to a surge in investment in self-driving technology.
Ключевые слова: edge computing RTU
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