In this day and age, it is almost impossible to find a better alternative to video surveillance. Be it private property or public— video surveillance is everywhere.

From gas stations to universities, government and private industries have heavily invested in these surveillance settings. But the real question is— do we have enough manpower?

There are thousands of security cameras worldwide, and nobody has the patience to watch them all. This is where AI surveillance enters the conversation. AI has the ability to process every frame and give real-time feedback. It has made threat detection and monitoring so much easier that nobody has to sit in a chair for hours on end.

According to the AIGS index, note that this survey was conducted on 176 nations, and almost 75 countries actively rely on AI-powered analytics. China and the US are the top users and providers of this technology simultaneously.

How Does AI Analytics Work?

AI Analytics in video surveillance uses machine learning for the most part. Machine learning algorithms and computer vision analyzes video footage in real-time. Live data is compared against previous recorded data. This way, the system learns typical patterns of behavior like movement and interactions.

When the AI detects anomalies or deviations from its already recognized patterns, it triggers security alerts. Unusual loitering or unauthorized access, everything counts as an anomaly. So, the AI sends signals to the people in charge of the investigation. Let's check out its applicability.

Features of AI-Powered Security Systems

AI has more than a few monitoring applications. It can turn hours of security footage into useful information. It takes the load off your team members’ shoulder by automatically marking important events and security alerts. With a reduced workload, they can finally focus more on the in-house projects.

Tracking and Object Recognition

Advanced computer vision algorithms let AI to “see”— both literally and figuratively. Our traditional systems primarily rely on motion detection and manual monitoring. And, as useful as they may be, they have their shortcomings.

Manual monitoring and motion detection struggle to detect objects accurately. Irrelevant moments like swaying trees or passing vehicles can trigger the sensor, which often results in false alarms.

On the other hand, AI analytics are more likely to differentiate between objects, animals, and humans. The exceptionally high accuracy reduces the chances of those false alarms. Also, The average human brain cannot sustain concentration on something for more than 12 minutes. So, there's that. We should leave this monitoring task to artificial intelligence.

Facial Recognition

This is arguably the best usage of AI tools. AI algorithms can very efficiently identify facial features. From a person's hairline to their tiny moles— nothing gets unnoticed.

Facial recognition has made a wave in the market. Even androids have this feature built-in nowadays. This is a particularly useful tool in situations where access control is important, for example airports, government buildings, corporate offices etc.

Predictive Analysis

With predictive analysis, AI can anticipate and pinpoint security risks. It does so by putting live footage against previously recorded footage.

Crowded areas where it is difficult for regular motion sensors to give their best performance, predictive analytics is the best option. Think of subways, train stations and airports— AI can make monitoring so much easier!

AI can analyze human body language and detect when someone is just walking and when they are running away. It can even detect vandalism. Whenever an anomaly happens, this smart software sends an alarm to the person in charge. This proactive approach prevents the risk of potential threats.

Faster Data Extraction

This tool acts like a savior in a state of emergency. It becomes very challenging to extract information from each and every camera in times of calamities.

Pandemics, terrorism, riots, and all kinds of atrocities require immediate action. You can't possibly waste time going through every single detail. You need fast results, and AI is here to help you.

Fire and Smoke Detection

AI powered surveillance settings can detect smoke or fire in real time. It is crucial to detect fire before it's too late. This is how integrating AI allows every industry to add an extra layer of security.

Monitoring

If a business is considering AI Analytics, they probably already have a functional system. Despite the massive upsides, AI also has some challenges. Including:

• Privacy concerns
• Financial burden
• Requires special attention

Data Security and Integrity

AI surveillance creates a huge amount of data that needs to be carefully protected. Keeping this data secure from hackers and making sure it's accurate is important. But it can be tricky to manage because there’s so much of it and it has to be processed quickly. Implementing these security measures is challenging, and also necessary to keep the system safe and reliable.

Ethical Concerns

AI systems can create ethical problems like bias in decision-making and privacy concerns from constant monitoring. For example, an AI used in hiring could unfairly favor certain groups if trained on biased data. Similarly, AI surveillance might invade people’s privacy, making them feel like they're always being watched.

Organizations need to address these issues carefully to avoid losing public trust. If they don’t, they could face backlash, damage their reputation, and even face legal trouble.

Technical Challenges

Integrating AI analytics isn’t just about adding new technology. It requires careful adjustments to make sure the algorithms work correctly and fit with existing systems. This process is complex and needs experts who understand both AI and the current infrastructure to ensure everything runs smoothly.