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The Role of AI and AIoT in Physical Security

The market worth for Internet of Things (IoT) solutions is expected to surpass a trillion by 2030. However, the growth spurt shouldn't be surprising, considering the numerous applications of IoT in our daily lives.

In the industrial and commercial sectors, physical security is one of the most important applications of IoT. AI and AIoT can help create a safer working environment for employees and reduce the risks associated with theft, vandalism, and other malicious activities.

But what role can AI and AIoT play in physical security? How do you integrate these technologies into your security system? Below, we'll explore the role of AI and AIoT in physical security.

What Are IoT and AIoT?

Before we discuss the role of AI and AIoT in physical security, let's first define what these terms mean. IoT refers to the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, and connectivity tools that enable these objects to collect and exchange data.

Meanwhile, AIoT (or artificial intelligence of things) combines IoT and AI technologies. It refers to applying AI algorithms to data collected by IoT devices.

In other words, AIoT takes the data collected by IoT devices and turns it into actionable insights using AI. These insights can improve the efficiency of various processes, including physical security.

How Does AI Enhance Physical Security?

Traditional physical security systems are designed to detect and respond to human threats. They use sensors to monitor intrusions, identify potential safety hazards, and track the movements of people and vehicles.

But these systems have limits. For example, they can’t see through walls, so they can’t always detect hidden threats. Similarly, decoys and camouflage can fool them. Another considerable concern is the high rate of false alarms, which leads to security fatigue and can cause people to ignore real threats.

AI-enabled physical security systems address these limitations. For example, they can “see” through walls using thermal imaging and distinguish between humans and animals.

AI can also help reduce false alarms by filtering out irrelevant data and only sending alerts when a potential threat is detected. Most importantly, AI-enabled security systems can become more accurate over time by constantly learning and evolving.

AI-enabled physical security systems are already being used in various settings, including airports, banks, prisons, and military bases. Here are some ways AI enhances traditional security solutions.

AI-Enhanced Video Analytics

Video analytics is a prime example of how AI can enhance physical security. AI-enabled video analytics can detect and track people and vehicles, identify potential threats, and generate alerts.

These systems are often used in conjunction with CCTV cameras. But they can also be used with other types of cameras, including body-worn cameras, doorbell cameras, and drones.

AI-enabled video analytics systems are especially good at identifying unusual or suspicious behavior. They can also be configured to ignore false alarms, such as birds flying in front of a camera.

Access Control and Identity Management

Another way AI is being used in physical security is for access control and identity management. These systems use biometrics, such as facial recognition, to verify a person’s identity.

AI can be used to improve the accuracy of these systems by constantly learning and evolving. For example, if a system incorrectly identifies a person as being on the banned list, it can “learn” from its mistake and become more accurate over time.

More importantly, AI can improve the usability of these systems. For example, if a system is having trouble verifying a person’s identity, it can ask for additional information, such as a fingerprint or iris scan.

A physical security solution, such as Keer, can further enhance security operations by providing a unified platform where organizations can manage physical security hardware. Since Keer offers plug-n-plays to all your physical security assets, including access control and alarm systems, it connects all assets to form a smart mesh that’s easier to maintain and manage.

Request a demo to learn more about Keer’s functionality.

Intrusion Detection

Intrusion detection systems are designed to detect and respond to unauthorized access. They use a variety of sensors, including motion detectors, door and window sensors, and pressure mats.

AI can improve the accuracy of these systems by filtering out false alarms. For instance, if a system is triggered by a cat walking across a pressure mat, it can “learn” to ignore that type of event in the future, reducing the number of false alarms.

Similarly, AI also helps enhance how these systems function.

Suppose an intrusion detection system sends an alert to a security guard. The guard can use AI to quickly find the source of the threat and take appropriate action.

AI tools can also automatically generate a report of the incident, which can help investigate and prevent future incidents.

How Can Businesses Use AIoT to Improve Physical Security?

As explained previously, AIoT combines the power of artificial intelligence (AI) with the Internet of Things (IoT). By connecting devices and systems to the internet and using AI algorithms, businesses can gain insights into patterns and trends that would otherwise be undetectable.

Such a well-integrated system is handy for improving physical security, as it can help identify potential threats before they happen. Here are some ways AIoT can enhance a company's physical security.

Automated Security Monitoring

AI algorithms can help identify anomalies in security footage that may indicate a potential security breach. As a result, AIoT can reduce the time needed to review footage and identify potential threats by automatically monitoring security footage.

For example, in a bank, AIoT can automatically scan security footage for changes in crowd behavior, such as a sudden increase in the number of people congregating in one area.

The information can then be used to dispatch security personnel to investigate the situation and prevent potential threats from materializing.

Likewise, AIoT can monitor customer behavior and identify potential shoplifters in a retail setting, such as a shopping mall.

Predictive Analysis

What could be better than stopping a security breach before it even happens?

This is where predictive analytics comes in. By analyzing data collected by IoT devices, businesses can identify potential security threats before they happen.

For example, suppose a business notices that there has been a sudden increase in the number of people trying to enter their premises after hours. In that case, they can use this information to predict that there may be a break-in attempt in the near future.

The business can then take steps to prevent the break-in from happening, such as increasing security patrols or installing additional security measures.

Improved Incident Response

AIoT can help businesses respond more quickly and effectively to a security breach.

For example, if a security camera detects a potential intruder, it can send an alert to security personnel. The personnel can then use AIoT to track the individual's movements and predict where they are going.

The authorities can dispatch security personnel to the location and apprehend the intruder before they cause any damage.

Ideally, you want to keep the incident response time as short as possible. Unfortunately, the longer it takes to respond to an incident, the more damage the intruder can cause.

In addition, AIoT can also be used to improve post-incident analysis. By reviewing footage and data collected by IoT devices, businesses can identify what went wrong and take steps to prevent similar incidents from happening in the future.

Challenges for Implementing AI and AIoT Practices in Physical Security

Although there are many benefits to implementing artificial intelligence (AI) and AIoT technologies in physical security applications, businesses must overcome several challenges. Here's an overview of some of these issues.

Lack of Standardization

One of the biggest challenges is the lack of standardization in these technologies. That can make it difficult to compare different products and solutions and to know which one will work best for a particular application.

How will you know if the AI system you're considering is good? Is there a standard you can compare it to? Unfortunately, not yet.

Ethical Implications

Researchers have long talked about the ethical implications of biometric technologies. However, although it's becoming an internationally emerging trend in physical security, there are still discrepancies in the definitions of the privacy paradox, informed consent, and privacy.

Additionally, little is known about how these technologies will be used in the future and how they might impact people's lives. What happens when an AI-based security system makes a mistake? Who is responsible?

Liability and Security Issues

Another challenge is that AI-based security systems are often black boxes. That is, it's difficult to know how they work and why they make the decisions they do. This can be a problem when it comes to liability and security issues.

If there's a security breach, for example, who is responsible? Is it the company that made the AI system? Is it the security company that installed it? Or is it the user who didn't properly configure it?


Finally, AI and AIoT-based security systems can be expensive. The hardware, software, and services cost can be a barrier for many businesses, especially small and medium-sized enterprises.

Additionally, there are often ongoing costs associated with these systems, such as maintenance, upgrades, and support.

These challenges must be addressed before AI and AIoT-based security systems can be widely adopted.


There's no denying that AI and AIoT are shaping how physical security systems are designed and operated. However, some challenges still need to be addressed before these technologies can be fully embraced.

With the current attempts to resolve these challenges and make AIoT solutions more accessible, we'll likely see more widespread adoption of AI and AIoT in physical security applications.

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