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Top 5 Computer Vision Applications in Security in 2024

Updated on Feb 20
3 min read
Written by
Shehmir Javaid
Shehmir Javaid
Shehmir Javaid
Industry Research Analyst
Shehmir Javaid in an industry & research analyst at AIMultiple.

He is a frequent user of the products that he researches. For example, he is part of AIMultiple's DLP software benchmark team that has been annually testing the performance of the top 10 DLP software providers.

He specializes in integrating emerging technologies into various business functions, particularly supply chain and logistics operations.

He holds a BA and an MSc from Cardiff University, UK and has over 2 years of experience as a research analyst in B2B tech.
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As the global crime rate increases, so does the need for security services. The demand for investigation and security services is projected to increase from $288 billion in 2020 to $417 billion by 2025.

While conventional security services such as manual surveillance are effective, they are limited to the capabilities of the person performing them. For instance, security personnel can only watch surveillance footage for a limited time and with a limited level of accuracy.

Business leaders in the security industry are leveraging digital solutions such as AI and ML to meet the increasing demand and optimize their offerings. Computer vision is a field of AI and can help the security sector overcome these challenges by providing higher accuracy and efficiency.

This article explores 5 applications and use cases of computer vision in the security sector that can help business managers implement this technology in their businesses.

Person detection

Finding escaped criminals or fugitives is a problem all over the world. Law enforcement agencies and government bodies have been using facial recognition for a long time to find criminals or people of interest. However, the level of accuracy and intelligence that computer vision and AI systems offer has only been achieved recently.

Many countries are using computer vision-enabled facial recognition systems to catch criminals at large, even with masks on.

Watch how the government of Dubai is using an AI and computer vision-enabled smart surveillance system to safeguard its public transport.

While computer vision-enabled facial recognition systems are effective, they face significant scrutiny in terms of public privacy. Some people feel that the technology violates their privacy and threatens their freedom. Therefore, many countries such as Canada, and the US are working towards regulating and limiting the use of this technology to protect public privacy.

You can also check our data-driven list of video annotation tools to find the option that best suits your project needs.

Dangerous situation detection

Another application of computer vision is smart security surveillance for violent and dangerous situations in urban cities. These systems are implemented through high-definition surveillance cameras deployed in different parts of the city to observe the people and detect violent behavior such as fights and alert authorities.

See how it works

These systems can be implemented in areas where there is a shortage of security personnel and a high rate of street crime.

School shootings have also increased since the pandemic started. In 2021, the highest number of school shootings was recorded in the US since 1999. Smart surveillance systems enabled with computer vision and AI can also help improve security and safety in schools in the following ways:

  • Detect suspicious behavior of students
  • Flag unwanted persons
  • identify unsafe objects
  • send alerts if there is overcrowding in any area

Theft and fraud prevention

Computer vision-enabled smart surveillance systems also help detect thieves:

Retail theft prevention

Retail crime is a big issue in the retail sector and it has increased after the Covid-19 pandemic. Companies have to face significant losses every year due to shoplifting and theft. Computer vision-enabled systems can observe customers in the stores to accurately detect shoplifting.

According to a recent report, computer vision systems are proving to be effective in minimizing retail theft and reducing product loss.

Walmart is also using AI-enabled surveillance cameras to detect store theft.

To learn more about how computer vision is revolutionizing the retail sector, check out this quick read.

ATM theft prevention

Computer vision-enabled systems can also observe the people using an ATM. The system can analyze the behavior of the person using the ATM to detect suspicious activities and alert authorities. 

In 2020, 2 people were arrested for tampering with around 700 ATMs in India. In a situation like this, a computer vision system can use facial recognition to identify those people and alert authorities to take action.

Crowd disaster prevention

Crowded events such as concerts, sports, or political events involve a high level of risk. Usually, in events like these, a large security team consisting of many security guards and staff is appointed to protect the crowd from potential incidents such as stampedes, terrorist attacks, etc.

Computer vision-enabled smart surveillance systems can help eliminate the challenges in high-risk events. It can help security companies cover larger areas and crowds with fewer security guards and higher accuracy. This can also reduce the costs of hiring and managing a big security staff.

Watch how a computer vision-enabled system can help manage the flow of crowds in busy places like airports and malls to avoid incidents and disasters.

Computer vision systems can also help detect abandoned objects in high-risk areas such as airports. The system detects the abandoned object and alerts the authorities for further investigation. 

See how it works

To improve your computer vision project, you check our data-driven lists of:

Further reading

If you have any questions, feel free to contact us

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Shehmir Javaid
Industry Research Analyst
Shehmir Javaid in an industry & research analyst at AIMultiple. He is a frequent user of the products that he researches. For example, he is part of AIMultiple's DLP software benchmark team that has been annually testing the performance of the top 10 DLP software providers. He specializes in integrating emerging technologies into various business functions, particularly supply chain and logistics operations. He holds a BA and an MSc from Cardiff University, UK and has over 2 years of experience as a research analyst in B2B tech.

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1 Comments
RANDY
May 24, 2023 at 01:47

Great blog post! Computer vision has truly revolutionized the field of security. These top five applications showcase the power and potential of this technology. From facial recognition for access control to object detection for threat detection, computer vision is making our world safer. Kudos to the developers and researchers pushing the boundaries and making these advancements possible. Looking forward to seeing more exciting developments in computer vision security applications in the future! Keep up the great work!

Bardia Eshghi
Jun 10, 2023 at 04:13

Hello, Randy. We’re glad you enjoyed our content.

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