03 Jan Hanwha Techwin predicts top 5 video surveillance trends for 2023
Hanwha Techwin has published its predictions for how they see the future of video surveillance heading in 2023.
1: How AI tech is used effectively
In the video surveillance industry, AI has evolved to the point of reducing the frequency of false alarms and enabling accurate forensic searches based on object attributes. However, AI based on basic metadata has become commonplace and does not attract the end users to make purchases anymore.
Customers now prefer reprocessed information oriented from a user’s perspective such as vehicle type statistics by period or a customer’s gender and age, rather than just merely aggregated metadata such as vehicle, gender or age data.
This enables clients to find insights and make business decisions by managing the information directly. Information becomes valuable when users are able to use it efficiently. Currently, the video surveillance industry is focused on developing solutions for the efficient management of tremendous amounts of metadata collected by AI.
From now on, a dashboard or a report which can collect and reproduce AI metadata and reproduce as insight or information that requests user’s decision will be increased.
2: Unified solutions with on-premise and cloud
As cloud-based services become more common, the number of companies that provide cloud services increases. Users can easily integrate devices and systems by using cloud services without needing to purchase or install additional servers. However, due to security policies, network status or budget, many companies prefer to maintain their conventional on-premise infrastructure by installing servers and software directly.
Based on this, a hybrid system combining on-premise and cloud is becoming increasingly common. For example, a company may use one method or combination of two ways according to environmental requirements (on-premise for overall management and cloud-based back-up for critical data).
3: New possibilities with Edge AI
Edge AI technology, which was simply used for detection and classification of objects, is now enhanced with Neural Processing Unit (NPU). As NPU grows more technologically advanced, Edge AI’s functions expand to include behaviour analytics and abnormal behaviour detection, for example. In addition, it’s also possible for users to learn AI algorithms directly according to their customer’s needs.
4: Converging technologies for the future
Conventional physical security solutions such as video surveillance, access control or intrusion alarms are being expanded through integration with the Internet of Things (IoT), AI, or the Cloud. For example, IoT-enabled sensors that detect smoke, temperature, humidity or motion are becoming part of a sophisticated total surveillance solution through integration with an AI security system. Specifically, this type of total solution delivers insight to users based on data analysis with the Cloud system.
5: Zero trust and cybersecurity
Awareness of personal information and cybersecurity risks are heightened as new business models and solutions are extended through technological integrations with AI, Cloud, and IoT.