Chase Carroll, Executive Vice President, BankPak
Dustin Giltnane, Director of Business Development, BankPak
Artificial Intelligence (AI) has witnessed remarkable advancements in recent years, transforming the landscape of video surveillance in ways previously unimaginable. In the realm of financial institutions, AI has been a game-changer, primarily in reducing false alarms. Gone are the days when basic motion detection analytics triggered alerts for trivial reasons such as changes in lighting, moving debris, or swaying trees. Today, AI-powered analytics have drastically cut false alarm rates, rivaling traditional alarm systems’ performance while offering invaluable context to security operations centers and monitoring centers. In this article, we will explore the current capabilities of AI in the video surveillance space and the exciting possibilities on the horizon.
The Current Capabilities of AI in Video Surveillance
AI in video surveillance is still in its infancy, but it has already made substantial strides in enhancing security and business operations. Traditional video analytics, which were not AI-powered, often suffered from high rates of false positives and false negatives. However, recent developments in AI have enabled analytics systems to classify objects, even in simplistic categories like people, cars, or animals. This classification capability has opened doors to various analyses, such as object detection, which provides businesses with advanced analytics to search.
Today’s AI can collect and analyze data points to provide valuable insights into business operations, including loitering detection, line wait times, ATM usage, facial recognition, demographic analysis for marketing, people counting, and more. Object attribution capabilities, such as clothing color, age, sex, vehicle classification, and clothing accessory classification, are available today and improving exponentially. These object attribution capabilities can be searched in CCTV software, greatly reducing research time. Right now, a lot of this information does not have a great use case. We will start to see a lot more value in this data 2 to 7 years down the road.
AI has also had a profound impact on improving the quality of video streams. AI-driven motion detection can better manage bandwidth and storage, ensuring efficient utilization of resources. Additionally, cameras equipped with AI can dynamically adjust settings like shutter speed to capture optimal images, eliminating the need for constant manual adjustments. Along these same lines, AI-drive analytics can send notifications when camera tampering, defocusing, and lens fogging occur.
Where AI in CCTV is Headed
We can expect AI-powered cameras to become increasingly intelligent, with the ability to predict and prevent crimes before they happen. Imagine a world where security systems are proactive, effectively thwarting potential threats and ensuring the safety of our communities.
AI-driven analytics are starting to emerge in preventing crimes with advanced detection such as hook and chain analytics, which will alert the authorities when an ATM Hook and Chain attempt is happening. Additionally, advancements in AI technology will enhance facial recognition capabilities, making it easier to identify criminals and locate missing persons. AI-powered CCTV systems will continue to evolve, incorporating machine learning and deep learning algorithms to improve accuracy and efficiency.
Gun detection, although a challenging and liability-laden area, is also on the horizon. Video surveillance AI gun detection is a technology that uses artificial intelligence algorithms to analyze video footage and identify the presence of firearms in real time. It can detect various types of firearms, including handguns, rifles, and shotguns. When a firearm is detected, the system can trigger alerts or notifications to security personnel, allowing them to respond quickly to potential threats.
We are rapidly approaching a time where the fusion of “computer vision” and language processing AIs is becoming a reality. This integration essentially equips ChatGPT with visual perception, enhancing its language comprehension capabilities. As a result, interactions will feel much more natural and human-like. Consider the example of security alerts. Instead of receiving a generic message like “Alert!! You are in a restricted area. You must leave now,” we will start to encounter personalized messages such as: “Hey there! The individual wearing a green shirt and sunglasses, this area is currently closed. It is imperative that you vacate immediately, or we will be forced to contact the authorities. Additionally, please be aware that you are under video surveillance, and we have observed the tattoo on your arm!”
Conclusion
The evolution of AI in video surveillance has come a long way, transforming security and business operations. Current AI capabilities substantially reduce false alarms and provide valuable insights into customer behavior and operational efficiency. AI is set to become even more intelligent, with enhanced object recognition, data analysis, and integration with language processing AIs. The future holds exciting possibilities for businesses and security systems, as AI continues to redefine the world of CCTV technology.
