The year 2021 has significantly changed every aspect of our daily lives from socializing, working, collaborating, and communicating. As the world began to emerge from a bizarre global pandemic, businesses and organizations in every industry were forced to re-evaluate almost every aspect of their organization based on their interactions with customers, how they managed workforces, and how they would maintain their market share.
This re-evaluation resulted in new types of security challenges arising. Now that most companies have successfully operated whilst working remotely, many have adopted that culture as a permanent solution. However, that decision exposes the company and staff to threats as everything is done online, exposing data being vulnerable to theft.
Let’s have a look at these video surveillance trends and how they will impact the industry in years to come:
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AI Edge Computing/Analytics: The reproduction of analytics and data for prompting security business decisions
Security and surveillance solutions are progressively incorporating onboard analytics to report data that can initiate intelligent protection and monitoring. As the years progress, onboard analytics will continue to thrive and expand significantly based on customers combining AI and edge computing to successfully enhance monitor and search efficiency.
The use of AI at the edge incorporating analytics based on deep learning algorithms, will structure a fundamental element of “smart surveillance” applications. These characteristics include object classification and detection, along with the collection of attributes in the form of metadata. All of this can be achieved whilst reducing system bandwidth requirements and latency, enabling situational monitoring and real-time data gathering.
Hanwha Wisenet P and X series AI cameras can apply AI and deep learning technology to identify only user-defined data for competent forensic search and improved operational efficiency. Deep learning algorithms and AI neglect movements of unwanted objects like swaying trees, shadows, or animals, resulting in a reduction of false alarms.
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Vision-based surveillance system integrated with AI technology
Network video surveillance systems are transitioning from being modest monitoring devices to developing comprehensive solutions that can be applied in every industry. The initiation behind this is AI technology integrated with systems at entry level. The data generated by AI cameras and AI solutions create valuable business intelligence to assist organizations in better understanding their operations and customers.
Body temperature detection and thermal imaging cameras at public points of entry use edge-based AI algorithms to reduce the frequency of false alarms and omit non-human heat sources. Cloud-based solutions are more effective and resourceful for store owners that wish to evaluate sales or floor design strategies as it uses people-counting algorithms. These applications can also be useful in logistics and distribution, smart parking systems or critical monitoring in healthcare.
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The “As a Service” Model
“As a service” is becoming increasingly popular when referring to video surveillance or access control in the security industry. The evolution of technology has enabled video surveillance manufacturers to expand their offering from product based to being a service provider as well. Cloud-based platforms have now become a service offering within the video surveillance industry. The “as a service” approach delivers cost-effectiveness and scalability, whilst maintaining an expenditure framework within your budget, offering services provided on a subscription basis.
This model also offers the convenience of eliminating on-site servers with the adoption of cloud-based recording. Organizations can therefore avoid the complex and time-consuming procedure of network configuration.
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Integration of Technology
The continuous advancements in network technology and the Internet of Things (IoT) results in a ripple effect within the security camera market. These advancements will broaden the possibilities for audio and video analytics, including AI. There has also been a significant incline in digital transformation with the influence of IoT and network, intelligent data, AI, as well as cloud computing.
Bandwidth and latency are also expected to improve as network technology positively advances. The inclusion of advanced network technology to cameras enables remote real-time video surveillance, legacy network management and the expanded use of mobile applications. Artificial Intelligence opens close to unlimited potential opportunities with open and integrated platforms that can expand device connectivity.