With the ever-growing availability of video data thanks to the low cost of high-resolution video cameras and storage, artificial intelligence (AI) and deep learning analytics now have become a necessity for the physical security industry, including access control and intrusion detection. Minimising human error and false positives are the key motivations for applying AI technologies in the security industry.

What is artificial intelligence?

Artificial intelligence is the ability of machines to learn from experience using a multi-layer neural network, which mimics the human brain, in order to recognise items and patterns and make decisions without human interference.

The human brain is estimated to have 86 billion neurons; in comparison, the newest Nvidia GPU Volta has 21 billion transistors (the equivalence of a neuron), which offers the performance of hundreds of CPUs for deep learning.AI can learn continuously 24 hours per day every day, constantly acquiring, retaining and improving its knowledge

In addition, unlike humans, AI can learn continuously 24 hours per day every day, constantly acquiring, retaining and improving its knowledge. With such enormous processing power, machines using Nvidia GPU and similar chips can now distinguish faces, animals, vehicles, languages, parts of speech, etc.

Depending on the required complexity, level of details, acceptable error margin, and learning data quality, AI can learn new objects within as fast as a few seconds using Spiking Neural Network (SNN) to a few weeks using Convolution Neural Network (CNN). While both SNN and CNN offer advantages and drawbacks, they outperform tradition security systems without AI in terms of efficiency and accuracy.

According to the research reports of MarketsandMarkets, the market size of perimeter intrusion detection systems is projected to increase from 4.12 billion USD in 2016 to 5.82 billion USD in 2021 at a Compound Annual Growth Rate (CAGR) of 7.1%.

Meanwhile, the predicted market of AI in security (both cyber security and physical security) will grow from 3.92 billion USD in 2017 to 34.81 billion USD by 2025, i.e., with an impressive CAGR of 31.38%.

Legacy perimeter intrusion detection systems

Legacy perimeter intrusion detection systems (PIDSs) are typically set up with the following considerations:

  • Geographical conditions: landscape, flora, fauna, climate (sunrise, sunset, weather conditions, etc.), whether there are undulations in the terrain that would block the field of view of cameras
  • Presence or lack of other layers of physical protection or barriers
  • Integration with other systems in the security network: camera, storage, other defensive lines (door, lock, alarm, etc.)
  • Types of alarm triggers and responses
  • System complexity: intrusion detection with various types of sensors, e.g., microwave sensors, radar sensors, vibration sensors, acoustic sensors, etc.
  • Length of deployment
  • Local regulations: privacy protection, whether the cameras/sensors must be visible/hidden/buried, etc., electromagnetic interferences that may affect other systems such as oil rigs or power plants
  • Human involvement: on-site personnel arrangement, human monitoring, human action in response to alarms

The amount of false alarms can be reduced by 70% to orders of magnitude with AI
AI object detection can easily distinguish different types of people and objects

Pain points and benefits of AI

The conditions listed above correspond to certain requirements of an intrusion detection systems: minimal false alarm, easy setup and maintenance, easy integration, and stable performance.AI by nature is designed to learn, adapt itself and evolve to work in multiple conditions: it should be integrated with existing video recording systems 

Minimal false alarms: False alarms lead to increased cost and inefficiency but are the main problem of PIDSs without AI technology, where animals, trees, shadows, and weather conditions may trigger the sensors. 
AI object detection can easily distinguish different types of people and objects, e.g., in a region set up to detect people, a car driving by, a cat walking by, or a person’s shadow will not trigger the alarm. Therefore, the amount of false alarms can be reduced by 70% to orders of magnitude.

Easy setup and maintenance: Legacy PIDSs without AI must account for terrain, line of sight of cameras, sensor locations; any changes to the system would require manual effort to recalculate such factors and may disturb other components in the system. 
In contrast, AI PIDSs enable the system administrator to access the entire system or individual cameras from the control room, configure the region and object of interest in the field of view of cameras within minutes, and adjust with ease as often as necessary. Computing knowledge and even specific security training are not required to set up a secured PIDS with AI because AI PIDS is designed to relieve humans from knowing the inner working of machines.

Easy integration with complementary technologies: Legacy PIDS without AI relies on physical technology, which are often proprietary and require complete overhaul of systems to function smoothly. On the other hand, AI by nature is designed to learn, adapt itself and evolve to work in multiple conditions, so AI PIDS is easily integrated with existing video recording (camera) and storage (NVR) systems. 
AI also eliminates the need for physical wireless or fiber-based sensors; instead, it functions based on the videos captured by cameras. Furthermore, AI enables easy and instantaneous combinations of multiple layers of defense, e.g., automatic triggering of door lock, camera movement focusing and access control as soon as a specified object is detected in the region of interest, all set up with a click of a button. 

Stable performance and durability: Legacy PIDSs without AI requires complicated setup with multiple components in order to increase detection accuracy. More components mean a higher probability of malfunction in the system, including exposure to damages (e.g., sensors can be destroyed) and delay in detection, while human monitoring is inconsistent due to human fatigue (studies have shown that a person can concentrate in mundane tasks for only up to 20 minutes, and the attention span decreases even more rapidly when humans are faced with multiple items at once, e.g., multiple camera monitoring screens). 
AI significantly reduces, if not completely eliminates the need for human involvement in the intrusion detection system once it is set up. In addition, AI reduces the risk of system malfunction by simplifying the hardware sensors needed.

The most advanced AI intrusion detection system today provides an all-in-one solution to distinguish any combination of alarm-triggering criteria
Minimising human error and false positives are the key motivations for applying AI technologies in the security industry

Additional benefits of AI in intrusion detection

Artificial Intelligence is undeniably reshaping every business and weaving into every aspect of daily lifeMaximal detection capability: The most advanced AI intrusion detection system today provides an all-in-one solution to distinguish any combination of alarm-triggering criteria beyond perimeter protection. Using AI, the system administrator can configure as many zones with different settings and object of interests as necessary, which include detections for specific colors or attributes (e.g., person not wearing the required uniform or carrying food/drink), numbers and dwell time (e.g., group of more than 5 people loitering), or movements (e.g., cars moving faster than the speed limit). 
In addition, AI can accurately pinpoint the location of event occurrence by displaying the camera that records the event in near real time, i.e., with few-second delays.

Lower security operation cost: By minimising the number of false positives and human involvement while maximising ease of use and stability, AI intrusion detection systems significantly decrease the total cost of ownership. Companies can reduce the large security personnel overhead and cost of complicated and expensive legacy PIDSs systems. McKinsey Global report in June 2017 shows that proactive AI adopters can realize up to 15% increase in profit margin across various industries.

Artificial Intelligence is undeniably reshaping every business and weaving into every aspect of daily life. In security, legacy systems are giving way to AI-based systems, and the first enterprises to adopt AI-based systems will soon, if not immediately, benefit from such investment.


By Paul Sun, CEO of IronYun, and Mai Truong, Marketing Manager of IronYun

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