Developments in Video Surveillance Technology for 2022

In 2022, technologies such as AI will continue to evolve to give users higher value, creating new business prospects for installers and integrators. The benefits of AI will reach a much broader audience as cameras use AI at the edge, causing a seismic shift in the security industry.

FREMONT, CA: The security sector cannot anticipate 2022 without first recognizing the significance of 2021: a year that altered every part of everyday lives, including how we socialize, work, communicate, and collaborate. As the world began to recover from an unprecedented worldwide pandemic, businesses reevaluated every element of their operations, from connecting with customers to managing their workforces and going to market.

This new environment has also generated new security issues. Employees, consumers, and partners increasingly work remotely, sharing and collaborating across different web networks, leaving data susceptible to theft. Moreover, since sites are remotely monitored, new public health and safety regulations control businesses' operations.

Here is a preview of these developments and an analysis of their impact on the sector in 2022:

AI edge computing and analytics: The proliferation of data and analytics drives commercial decisions

Surveillance and security solutions increasingly include onboard analytics to provide data that can drive intelligent protection and monitoring. In 2022 and beyond, the role of onboard analytics will continue to grow as clients integrate edge computing and AI to improve monitoring and search efficiency.

According to one projection, the worldwide edge computing infrastructure will be worth more than $800 billion by 2028. Various "smart surveillance" applications will rely heavily on using AI at the edge, particularly with analytics based on deep learning algorithms. These include object detection and classification, capturing metadata properties, decreasing latency and system bandwidth, and enabling real-time data collection and situational monitoring.

AI and edge computing will continue to increase the efficiency and efficacy of network video surveillance systems by applying analytics (object, loitering, virtual line and area crossing, detection, to name a few) to monitor every sort of location or circumstance. Users can undertake 'pre-emptive detection' and rely less on reactive monitoring due to AI and edge computing enabled by cameras deployed throughout vertical industries, enhancing safety and productivity.

Vision-based surveillance systems are currently incorporating AI

Network video surveillance systems are evolving from simple monitoring devices to complete solutions applicable to every business and market segment. This is being driven by integrating AI technology into systems at every level, a trend that is anticipated to experience unprecedented growth. Analysts predict that the global AI-based surveillance and security market will reach $4.46 billion by 2023.

The data provided by AI vision systems employing AI cameras as vision sensors help businesses obtain a deeper understanding of their clients and operations. At public space entrances and lobby areas, thermal imaging and body temperature detection cameras employ AI-based edge algorithms to bypass non-human heat sources and reduce the number of false alerts.

Businesses can automate their security strategies with the necessary response thoroughly planned and prepared for deployment. Cloud-based systems employ people-counting algorithms to assist store managers in evaluating sales or floor design ideas and heat-mapping to measure and avoid long checkout lines to boost customer happiness. Similar uses and benefits can be applied to traffic management or intelligent parking systems, logistics and distribution, and critical area monitoring in healthcare.