Artificial intelligence (AI) has brought about surprising developments in various sectors including automotive, manufacturing, healthcare, finance, entertainment, among others, while still being in its infant stage.
Of all the applications, the use of artificial intelligence along with its sub-sects deep learning, and machine learning in the surveillance of the market is growing by leaps and bounds because of its intense impact in achieving security by anticipating and preventing hazardous situations. According to recent international research, the global video surveillance market size is foreseen to grow at a CAGR of 10.4% from 45.5 bn dollars in 2020 to 74.6 bn dollars by 2025.
Let’s discuss the way AI is transforming market surveillance
* AI is Taking Over Passive Surveillance Solutions
While the adoption of CCTV cameras to enable live streaming of videos on screens has been done on a large scale globally, be it in hospitals, markets, retail stores, or offices, usually, they are passive and only paid attention to after an unforeseen incident has taken place or after receiving information about a potential threat. Also, interpretation of unclear information can be a daunting task as the massive data gathered cannot be utilized to the full extent in conventional systems. Artificial Intelligence and Machine Learning-powered cameras are more intrusive and can efficiently make real-time monitoring and intelligent analysis of the footage that can prevent the happening of such unexpected events.
* Automated platforms are Making the Process Smoother
Today, the importance of AI in the surveillance of the market is growing like never before. Machine-based learning algorithms were used to observe and analyze the videos, images, and other forms of data recorded from surveillance solutions in the past.
But today, the world is slowly adopting behavioral analytics powered by artificial intelligence that does not need pre-defined rules is growing. Modern self-learning systems work by auto-detecting, classifying and analyzing data related to the target environment. The automated platforms are enabling a smoother collection and storage of information flooding in from diverse sources.
* Real-time Detection and Analysis of Objects
When it comes to surveillance of the market, AI-powered tools can utilize machine-based vision and can observe every detail in a live video stream, or can record and notify the operators in case of the slightest deviation from activity (actions, behavior or incidents). Data fed into the algorithms can include biometric data, geographic location, social media feeds, history of arrest, and more.
Deep learning has engineered neural networks that can detect and analyze objects in real-time. Common methods include You Only Look Once (YOLO), faster Region-CNN (RCNN), and Single Shot Detector (SSD) networks. The choice of algorithm depends on the parameters like size, speed, accuracy, and so on.
AI in Surveillance of Market: The Future scope
AI has proved itself a great tool for spotting crimes and accidents in the market easily and mitigating them effectively. Slowly, but every industry is expected to embrace this revolutionary technology. Along with its advantages, it also raises grave concerns about the future of privacy and risks to the contemporary social structure.
If businesses and governments fail to take adequate steps to control and monitor the privacy violations in this field, it can have destructive consequences. However, the opacity regarding the usage of data obtained through surveillance varies from country to country.
The use of AI in the surveillance of the market is expected to grow at an unprecedented rate. The reason artificial intelligence is making a vast impact on market surveillance is its self-learning capabilities.
Across the globe, governments and businesses have already started investing in establishing AI-powered surveillance infrastructures. There are billions of cameras, but no one has the time and efficiency to monitor them 24/7. However, with the help of artificial intelligence, each and every bit of data can be analyzed in real-time to save millions of lives.