AI-powered computer vision is revolutionizing every industry, and it’s the new eyes of security in recent times. By enhancing security measures, security and surveillance take a big leap, covering various applications such as license plate recognition, facial recognition, and anomaly detection in real-time, expanding their impact across various sectors like healthcare, transportation, and healthcare. FastEdge.AI’s state-of-the-art security and surveillance solution EdgeGuard AI is transforming surveillance and security monitoring with AI-powered computer vision driven by edge computing, artificial intelligence, machine learning, and IoT technologies. This blog delves into the trends of AI in the surveillance arena.
The Power of Intelligent Video Surveillance
Large scale AI vision systems integrate numerous cameras using intelligent video surveillance at any remote locations, with the wide range of use cases and applications for object detection and tracking, anomaly detection, monitoring systems, movement analysis technologies, identification, prevention, and warning systems.
- People Detection
Object detection algorithmsare widely used to detect people in video feeds, which includes automated multi-person and single-person detection using intelligent video security systems.
AI-powered crowd analysis saw a 25% increase in adoption at public events and large crowd gatherings such as concerts and sports games in 2023. With global market growth projected to reach $86.5 billion by 2027, the demand for critical infrastructure with precise security in urban areas is in increasing demand. Due to recent advancements in AI technology, human-detecting systems, achieving more than 95%, have significantly reduced the occurrence of false alarms in security and surveillance system.
- People Movement Analysis
Path modelling techniques and people detection combines to perform human movement analysis. For instance, in smart city applications, to analyse pedestrian behaviour, vehicle behaviour, movement speed, acceleration, and trajectories and to perform motion prediction, movement analysis can be used.
Pedestrian behaviour movement analysis has been included in almost 60% of smart city initiativesto ensure public safety and enhance traffic management. In cities like Los Angeles, by using vehicle behaviour monitoring, traffic flow has been improved by about 12%, improving commute time and reducing congestion. Study reveals the accuracy rate reaching 85-90%, where the AI-empowered systems detect and respond to any potential accidents or collisions up to 3 seconds faster than human intervention.
- Facial Recognition Technology
Facial Recognition Solutions have become an intrinsic part of the modern security system with recent advancements. On a broad level, a sequence of tasks is performed using computer vision AI to detect people’s faces andfocus on the face areawith the facial image points it compares with the images of the database. Facial recognition algorithms require sophisticated security infrastructure and privacy. On the other hand, people are identified using pictures and videos without their permission and knowledge.
In developed nations, over 65% of the security and surveillance systems are empowered with facial recognition technology, which is extremely critical for law enforcement and public safety perspectives. The global market is valued at $5.8 billion in 2023 and is projected to grow to $10.2 billion by 2027, with a CAGR of 12.5%. Under ideal conditions that capture high-quality images in a well-lit environment, the algorithm achieves an accuracy rate of about 99.97%.
- Human Behaviour Understanding
Through video-based surveillance, people are detected, classified, and tracked in accordance with specific behaviour patterns or actions. Theft detection, robbery detection, aggression detection, or brawl detection can be captured and identified using AI, machine learning, and other imaging technologies.
In detecting suspicious behaviour or theft, AI-powered systems bring in a substantial difference, thus reducing shoplifting incidents and enabling immediate response from security personnel. Algorithms detect brawl or aggressive behaviour by analysing movement patterns in real-time. Whereas in robbery and crime prevention, early detection would certainly reduce incidents by alerting security teams to potential robbery scenarios.
- Weapon and Dangerous Object Detection
Real-time object detection is very challenging in real-time scenarios, and to implement it with proper detection and localizing specific objects using live video feeds is extremely critical. Protective equipment detection or weapon detection (knives or firearms) are some of the common object recognition applications.
AI-powered detection systems are being adopted at rapid pace across the developed nations. According to a recent study, in high-risk environments such as airports, schools, and public events, there has been an increase of about 40% in new security systems, which enable almost instant alerts to security personnel, ensuring continuous monitoring without missing critical moments.
The role of AI-empowered security and surveillance in today’s modern infrastructure and technological advancements is undeniable and is transforming how we monitor and respond to potential threat situations. A more secure and safer world is what everyone embraces, and thus it is essential to balance innovation with ethical and legal consideration in adopting computer vision AI-powered solutions to boost our security game. The future of security lies in our hands, the decision-making to move to a smarter, more responsive, and more secure environment, & with solutions like EdgeGuard AI, we are well on our way to a new era of intelligent surveillance.
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