As cameras and sensors proliferate, computer vision provides insights into public spaces and workplaces, airports, and industrial sites so that security and safety officials can understand images and data from remote and high-traffic areas.
Business leaders in the security industry are using digital solutions like AI and ML to meet growing demand and optimize their offerings. Computer vision is a branch of AI and can help the security sector overcome these challenges by providing high accuracy and efficiency.
This article explores the top Application of computer vision in security to help business managers implement this technology in their businesses.
Why Use Computer Vision for Safety and Security?
More organizations are taking the right approach to apply computer vision for security AI to keep their employees, customers, and assets safe. Computer vision is a subdomain Applications of artificial intelligence that deals with how computers "see" digital images and videos.
The goal of computer vision is to provide machines with a high-level understanding of visual images that approaches or mimics human perception. In recent years, advanced computer vision algorithms and techniques have been able to equal or beat human performance on tasks such as object recognition.
AI Computer Vision Applications in Surveillance and Security
Intelligent video surveillance has a wide range of applications and uses cases for anomaly detection, object detection and tracking, movement analysis technologies, monitoring systems, prevention, identification, and warning systems. Collaborative video surveillance enables large-scale AI vision systems that integrate multiple cameras in remote locations.
Human Identity
People detection uses object detection algorithms to localize people in video feeds. Automated single-person and multiple-person detection are important features of intelligent video surveillance systems. Human detection also includes crowd analysis to estimate visual density and moving object interaction in crowded and uncrowded scenes.
Analysis of People's Movements
Path learning combines human recognition with path modeling techniques and clustering to perform people's movement analysis. For example, in smart city applications, motion analysis is used to perform motion estimation and analyze vehicle behavior, pedestrian behavior, acceleration, movement speed, and trajectories.
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Health and Safety Regulations
Whether they come from OSHA or come up with them yourself, each organization has its own laws, standards, and regulations that must be complied with. Computer vision systems can detect whether workers are wearing protective clothing such as hard hats or masks while on the job, sending an immediate alert when they detect non-compliance.
Vehicle Identification
Computer vision systems can help you automatically identify a vehicle by identifying its make, model, and color, while security cameras can capture and record the license plate details of suspicious vehicles.
Face Authentication
By using computer vision, you can create a highly accurate facial authentication system that identifies authorized users in a fraction of a second. Whether you need to restrict access to restricted areas or identify VIPs, computer vision allows you to create a facial authentication system with liveness detection that protects against possible attacks.
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Remote Perimeter Sensing
Vehicle identification and license plate recording, border violations, alteration, water or heat detection. Alerts and logs are sent via text message. Increased awareness of the edge.
AI Fire Detection
With a public AI model that can detect wildfires and internal fires by streaming video or images to an edge device or the cloud.
Advantages of Computer Vision
Computer vision can automate many tasks without the need for human intervention. As a result, it offers several Computer vision applications Benefits to organizations:
Faster and simpler process – Computer vision systems can perform repetitive and monotonous tasks faster, making tasks easier for humans.
Better products and services - Well-trained computer vision systems make zero mistakes. This leads to faster delivery of high-quality products and services.
Cost-reduction – Companies don't have to spend money fixing their faulty processes because computer vision leaves no room for faulty products and services.
The End
The Future of Computer Vision can be used successfully in a variety of businesses that rely on image and video data. It helps us automate routine processes, improve diagnostic accuracy, increase agricultural production and maintain safety. We can predict that computer vision will continue to be a driving force transforming all types of businesses as more organizations adopt an AI-first strategy.
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