What Drives Video Surveillance Technologies Forward?

What Drives Video Surveillance Technologies Forward?

surveillance

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Advanced video surveillance capabilities have many applications in business, industry and society in general, and are evident in a major market growth. The global video surveillance market size is expected to grow from $45.5 billion in 2020 to $74.6 billion by 2025, at a CAGR of 10.4%, according to a Markets and Markets forecast. Factors driving the growth of this industry include the increasing concerns about public safety and security, growing adoption of IP cameras, and rising demand for wireless and spy cameras. 

The enhanced functionality made possible by the Internet of Things (IoT) – namely the connected, smart monitors, sensors, and other devices – has been driving a substantial evolution in video surveillance.

IoT combined with emerging high-speed network solutions promise to improve the performance and capabilities of video surveillance systems. Two major technologies will drive the enhanced functionality of video surveillance equipment: Artificial intelligence (AI) and deep machine learning (ML) are bringing the power of analytics to unmanned video surveillance; Wireless communication technologies such as 5G and narrow band IoT (NB-IoT) improve the speed with which video feeds are made available to human and AI applications. 

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According to securitymagazine.com, building intelligence into video surveillance systems enables them to execute rapid searches through large volumes of footage, generate real-time insight through automated analysis, and use predictive analytics in order to produce alerts for proactively mitigating risks before they become problematic.

Smart cities benefit from cutting-edge IoT video surveillance to monitor vehicle and foot traffic, addressing congestion problems. Predictive AI analysis may identify dangerous situations before they escalate and give decision-makers ample time to react. This information can also help avert disasters such as those recently experienced from catastrophic weather events.

However, the connected nature of IoT implementations presents challenging security risks. Every smart camera provides an attack vector through which hackers can potentially access sensitive information and additional computing resources. 

The power of IoT-attached video cameras might be abused for stealing credentials and infringing privacy. These risks can be minimized by changing configuration parameters to limit access to video cameras, but they cannot be completely eliminated.