How can IP camera video analytics and AI reduce false alarms?

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False alarms are a common and costly problem for security systems that rely on IP cameras. They can waste time, resources, and money, as well as reduce trust and confidence in the system. However, with the advances in video analytics and artificial intelligence (AI), it is possible to reduce false alarms significantly and improve the accuracy and efficiency of security monitoring. In this article, you will learn how IP camera video analytics and AI can reduce false alarms by using smart features such as motion detection, object recognition, face recognition, and behavior analysis.

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David Garries

Top Voice 2024 | Leader in Technological Innovation | DevOps & Full-Stack Development Expert | IT Project Manager
Tom S.

Halo, tu mówi kamera ... voco.camera - monitoring sterowany g?osem

1 Motion detection

Motion detection is a basic feature of IP cameras that can trigger an alarm when a change in the image is detected. However, not all motion is relevant or suspicious, and motion detection can be easily fooled by factors such as shadows, light, wind, or animals. To reduce false alarms, IP cameras can use video analytics and AI to enhance motion detection by filtering out irrelevant motion, adjusting sensitivity levels, and applying regions of interest. For example, a video analytic algorithm can ignore motion that is too small, too fast, or too far from the camera, or motion that occurs in a predefined area that is not important.

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David Garries

Top Voice 2024 | Leader in Technological Innovation | DevOps & Full-Stack Development Expert | IT Project Manager
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De momento, y por la mayoría de software que he probado, pruebas y experiencia. Al final conoces, los propios algoritmos y los entornos que producen las falsas alarmas, banderas, ramas, luces, sombras, lluvia... Al final, aprendes a configurar los tama?os, el tiempo en escena del objeto y otros elementos

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Tom S.

Halo, tu mówi kamera ... voco.camera - monitoring sterowany g?osem
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1. AI-powered video analytics can filter out false triggers, distinguishing an intruder from a pet by focusing alerts on real threats. 2. By recognizing patterns, such as shadows moving as the day progresses, AI reduces false positives by adjusting sensitivity to environmental changes. 3. By implementing a virtual geo-fencing within the camera's field of view, AI monitors specific areas while ignoring irrelevant traffic outside these zones to reduce false alarms.

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Caio Henrique

Criador do PRONATAS | Especialista em Seguran?a Corporativa | Avalia??o de Riscos e Vulnerabilidades | Gerenciamento de Projetos | Tecnologias de Vigilancia (CFTV) | Gest?o de Crises e Continuidade de Negócios
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Para ter eficiência ao utilizar esses analíticos com cameras IPg deve-se levar em considera??o o projeto de ilumina??o, o fluxo de pessoas do ambiente bem com todas as recomenda??es técnicas da inscri??o do equipamento e ajuste periódicos por parte do operador de CFTV..

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2 Object recognition

Object recognition is a feature of IP cameras that can identify and classify different objects in the image, such as people, vehicles, animals, or weapons. This can help reduce false alarms by distinguishing between objects that pose a threat and objects that are harmless or authorized. For example, a video analytic algorithm can recognize a person carrying a gun and trigger an alarm, while ignoring a person carrying an umbrella or a bag. Object recognition can also help verify alarms by providing additional information about the object, such as its size, color, shape, or license plate.

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Tom S.

Halo, tu mówi kamera ... voco.camera - monitoring sterowany g?osem
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Artificial intelligence can distinguish between human and non-human shapes, reducing alarms caused by animals or falling leaves. Video analytics filters movements based on size and speed, ignoring small, fast-moving objects such as birds to reduce false alarms. The AI learns normal patterns by identifying and ignoring regular, non-threatening activities, such as a routine visit from a supplier.

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3 Face recognition

Face recognition is a feature of IP cameras that can match faces in the image with faces in a database, such as a whitelist or a blacklist. This can help reduce false alarms by verifying the identity and authorization of people who enter or exit a secured area. For example, a video analytic algorithm can recognize a face that belongs to an employee or a visitor and allow access, while detecting a face that belongs to a stranger or a criminal and alerting the security personnel. Face recognition can also help track and locate people of interest by comparing faces across multiple cameras and locations.

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Tom S.

Halo, tu mówi kamera ... voco.camera - monitoring sterowany g?osem
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Artificial intelligence improves facial recognition to identify known people, reducing false positives by distinguishing residents from potential intruders. By analyzing facial features in real time, the AI can ignore animals or moving objects, focusing only on human faces and triggering alarms. Through continuous learning, the artificial intelligence updates its database with new faces, minimizing false positives by recognizing frequent visitors or staff.

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4 Behavior analysis

Behavior analysis is a feature of IP cameras that can analyze and interpret the actions and interactions of people and objects in the image, such as walking, running, falling, fighting, or loitering. This can help reduce false alarms by detecting abnormal or suspicious behavior that indicates a potential threat or an emergency. For example, a video analytic algorithm can detect a person who falls down and does not get up and trigger an alarm, while ignoring a person who sits down and rests. Behavior analysis can also help prevent or respond to incidents by providing alerts and suggestions based on the behavior patterns and scenarios.

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Tom S.

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Artificial intelligence monitors common movement patterns and flags unusual behavior, such as wandering at odd hours, to reduce irrelevant alerts. Behavior analysis distinguishes routine activities from potential threats, focusing alarms on activities such as intrusion attempts. By learning daily activity cycles, the AI predicts normal behavior, reducing false positives by ignoring expected movements within these cycles.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can IP camera video analytics and AI reduce false alarms?

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1 Motion detection

2 Object recognition

3 Face recognition

4 Behavior analysis

5 Here’s what else to consider

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