Thanks to the reduction of high-resolution cameras and storage costs, the availability of security surveillance video data has been greatly improved. Artificial intelligence (AI) and deep learning analysis have become an inevitable choice for the physical security industry, including access control and intrusion detection. Reducing human error and reducing false alarm rate is one of the main motivations for the security industry to introduce AI technology.
What is artificial intelligence?
Artificial intelligence is the machine's ability to learn experience by using a multilayer neural network that mimics the human brain in order to recognize objects and patterns and make decisions without human intervention.
The human brain has approximately 86 billion neurons; in comparison, the latest Nvidia GPU Volta has 21 billion transistors (one transistor is equivalent to one neuron), which can provide deep learning for hundreds of CPUs. ability.
In addition, unlike humans, artificial intelligence can learn every day 24 hours a day, continuously acquiring, saving and improving its knowledge. With such huge computing power, these machines using Nvidia GPUs or similar chips can now distinguish faces, animals, vehicles, languages, words, and more.
Depending on the level of complexity, level of detail, acceptable error range, and quality of learning data, artificial intelligence can use pulsed neural networks (SNN) to quickly learn new objects in seconds, whereas using convolutional neural networks (CNN) requires For several weeks. Despite their respective advantages and disadvantages, both SNN and CNN are superior to traditional security systems in terms of efficiency and accuracy.
According to the MarketsandMarkets research report, the market size of the peripheral intrusion detection system is expected to increase from 4.12 billion US dollars in 2016 to 5.82 billion US dollars in 2021, with a compound annual growth rate of 7.1%. At the same time, AI's anticipated market for security (including cyber security and physical security) will grow from 3.92 billion U.S. dollars in 2017 to 3.481 billion U.S. dollars in 2025, a compound annual growth rate of 31.38%.
Traditional border intrusion detection system
Traditional boundary intrusion detection systems (PIDSs) usually need to consider the following factors:
Geographical conditions: landscape, flora, fauna, climate (sunrise, sunset, weather conditions, etc.), and whether there are fluctuations in the terrain will obstruct the vision of the camera; the presence or absence of physical protection or obstacles in other dimensions; and other security network systems Integration: Cameras, storage devices, and other lines of defense (doors, locks, alarms, etc.); ways to trigger alarms and responses; system complexity: use various types of intrusion detection sensors such as microwave sensors, radar sensors, vibration sensors, sounds Sensors, etc.; length of fortification;
Local regulations: such as privacy protection, whether the camera/sensor must be visible, hidden or buried, and whether it may cause electromagnetic interference to other systems such as oil rigs or power plants;
Staffing: on-site personnel, monitoring personnel, personnel action arrangements in response to alerts, etc.
AI object monitoring can easily distinguish different types of people and things
The advantages of pain points and AI
The conditions listed above are consistent with some of the requirements of common intrusion detection systems. That is, we hope to achieve the lowest false positive rate, easy installation and maintenance, easy integration with other security systems, and stable performance.
False alarm rate is minimized: Before the application of AI technology, false alarms are the main problems faced by traditional intrusion detection systems, which leads to increased operating costs and inefficiency because animals, plants, shadows, weather conditions, etc. may trigger Sensors cause false alarms. AI object detection can easily distinguish between different types of people and objects. For example, a specific area can be set, and no alarm is triggered for pedestrians, cars, cats, or people passing through the area. In this way, the false alarm rate may be reduced to the order of 70%.
Easy to install and maintain: For traditional intrusion detection systems without artificial intelligence, factors such as terrain, camera line of sight, and location of sensors must be considered; and any adjustment of the system requires manual recalculation of these factors and may interfere with other equipment in the system . In contrast, having an AI technology intrusion detection system allows system administrators to easily access the entire system or a camera in the control room, configure cameras to monitor specific areas and objects within minutes, and also Adjust it at any time.
AI security intrusion detection systems do not even require a lot of computing power, knowledge, or security training, because the main purpose of AI intrusion detection systems is to reduce the labor burden through the machine.
Easily integrate related assistive technologies: Traditional intrusion detection systems without AI rely mainly on physical technologies. These technologies are usually proprietary and require thorough overhaul of the system to run smoothly. Artificial intelligence, on the other hand, is designed to learn and adapt to work under a variety of conditions. Therefore, an artificial intelligence intrusion detection system can be easily integrated with existing video recording (camera) and storage (NVR) systems.
AI also eliminates the need for physical wireless or fiber optic sensors because its functionality is based on video captured by the camera.
In addition, AI technology can also implement a simple and fast combination of multi-layered defense systems. For example, once a certain area detects the movement of an object, the system automatically triggers the door lock, the camera automatically focuses, and performs access control. All of this is done with just a click of a button.
System is stable and durable
Traditional intrusion detection systems without AI need to use many components for complex setup in order to improve the accuracy of detection. More components means that the system is more likely to fail, including more easily exposed to damage (for example, the sensor may be damaged) and delay detection. Moreover, due to the fact that people are prone to fatigue, it may lead to errors. (Some studies have shown that one person can concentrate on boring work and concentrate for about 20 minutes; and when one person has to deal with multiple items at the same time, the attention is reduced even more. For example, to face many surveillance video displays.) In addition, AI technology can also reduce the risk of system errors by reducing the application requirements for sensor hardware.
Reducing human error and reducing false positives are the main drivers of AI for the security industry
Other advantages of AI in intrusion detection
Maximum detection capability: Today's state-of-the-art artificial intelligence intrusion detection systems can communicate to provide a complete solution that can identify any combination of triggered alarm combinations that exceed perimeter protection standards. Using AI technology, system administrators can personalize different areas and objects as needed, including the detection of specific colors or attributes (eg, people who are not wearing the required uniforms or carrying food/drinks), numbers, and dwell times ( For example, a stay of more than 5 people) or a sport (for example, a speed exceeding a limit). In addition, AI technology can accurately mark the location of the incident and record the incident in real time.
Reduce Security Operations Costs: By minimizing the number of false positives and human intervention while maximizing ease of use and stability, AI intrusion detection systems can significantly reduce total cost of ownership. Enterprises can reduce the cost of large security personnel and the cost of complex and expensive traditional intrusion detection systems.
The McKinsey Global report for June 2017 shows that proactive adoption of AI can help industries achieve up to 15% profit growth.
It is undeniable that artificial intelligence is reshaping every industry and integrating it into every aspect of daily life. In terms of security, traditional security systems are giving way to artificial intelligence-based systems.
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