AI video analytics software Your cameras record.
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Video analytics refers to the use of advanced algorithms and artificial intelligence to automatically interpret video footage. Instead of relying on human operators to watch hours of CCTV recordings, video analytics can identify important events, detect objects, track movement, and highlight unusual behaviour. It transforms video from a passive recording tool into an active intelligence system that understands what is happening in real time.

Video analytics processes video streams using computer vision and AI. It can detect motion, classify objects (such as humans or vehicles), track their movement, and generate alerts when specific rules or patterns are observed. This makes surveillance more efficient, reduces human workload, and improves accuracy by eliminating human error and fatigue.

CCTV with video analytics is a modern surveillance system where cameras are connected to intelligent software capable of analysing the video automatically. Instead of simply recording footage, the system can detect intrusions, identify people, recognise vehicles, monitor crowd behaviour, and send alerts instantly. This makes CCTV proactive rather than reactive.

Video analytics in CCTV refers to the intelligence layer added to traditional camera systems. It allows the system to understand the content of the video, such as detecting a person entering a restricted zone, identifying a vehicle moving in the wrong direction, or recognising a suspicious object left unattended. It enhances security, safety, and operational efficiency.

CCTV is basic video recording without intelligence. It captures footage but does not interpret it. Video surveillance includes monitoring, analytics, automated alerts, and intelligent detection. It uses AI to understand what is happening in the video. CCTV is passive; video surveillance is active and smart.

• Facial recognition: identifying individuals
• People counting: measuring footfall in retail or public spaces
• Vehicle detection: recognising cars, bikes, trucks, and more
• License plate reading (ANPR): capturing and analysing number plates
• Intrusion detection: alerting when someone enters a restricted area
• Loitering detection: identifying suspicious prolonged presence
• Crowd density analysis: monitoring crowd build-up
• Object-left-behind alerts: detecting abandoned bags or items

• Motion detection
• Human and vehicle classification
• Facial recognition
• ANPR (Automatic Number Plate Recognition)
• Heatmaps and footfall analysis
• Queue management
• PPE detection (helmets, vests, masks)
• Perimeter protection
• Behaviour analysis
• Object tracking

Each type serves a specific purpose depending on the environment and requirement.

AI video analytics processes video to detect objects, behaviours, and events using deep learning and computer vision. It provides real-time detection, reduces false alarms, and generates operational insights for security, retail, manufacturing, and smart city applications.

DhurgAI covers people, vehicles, objects, activities, safety and environment, with 40+ capabilities including intrusion and loitering detection, people counting, face matching, ANPR, traffic violations, PPE compliance, unattended objects, queues and heatmaps.

An AI-enabled camera has built-in processing chips that allow it to detect humans, vehicles, faces, and events without needing a separate server. These cameras perform analytics at the edge, meaning they analyse video inside the camera itself for faster results.

AI CCTV cameras use deep learning to detect humans, vehicles, faces, and license plates with high accuracy. They are widely used in traffic systems, industries, retail, and residential security. They reduce manual monitoring and improve overall safety.

A video analytics server processes multiple camera streams using deep learning models. It handles heavy analytics tasks and supports large-scale deployments. It is ideal for environments with many cameras or complex analytics requirements.

An AI camera app is a mobile or desktop application that displays AI detections, alerts, playback, and analytics dashboards from smart cameras. It allows users to monitor premises remotely and receive instant notifications.

Data can be extracted from NVRs, VMS systems, or directly from IP camera streams using RTSP links or API integrations. This data is then processed by analytics software to generate insights.

In most cases, no. DhurgAI connects to existing IP cameras over RTSP, or through your NVR or VMS, so many deployments reuse the cameras already installed. New cameras are only needed where coverage, angle or resolution is not enough for a specific use case such as ANPR.

Both are possible. Edge processing analyses video close to the cameras for fast response and lower bandwidth, while central servers handle many streams and heavier models. DhurgAI supports edge, central and hybrid architectures, so video can stay on your own network.

CCTV video analytics software processes CCTV feeds using AI to identify objects, track movement, detect violations, and generate real-time alerts. It can run on servers, cloud platforms, or directly on cameras depending on the system design.

AI analytics software uses deep learning models to detect humans, vehicles, faces, and behaviours with high accuracy. It can work in complex environments such as low-light conditions, crowded areas, or high-speed traffic zones.

Tools include object detection, tracking, ANPR, facial recognition, heatmaps, crowd analysis, and behaviour detection modules. These tools help automate surveillance and improve operational efficiency.

AI-enabled VMS platforms, ANPR tools, facial recognition systems, and behaviour analytics software can be used to analyse CCTV footage. These tools help identify events, track objects, and generate insights from recorded video.

Free tools exist but offer limited analytics compared to enterprise-grade AI systems. They are suitable for basic motion detection, simple playback analysis, or small-scale use cases.

A video analytics checker tests or validates analytics accuracy, performance, and detection quality. It helps ensure that AI models work correctly in real-world environments.

AI CCTV camera prices vary based on resolution, build quality, and analytics features. Basic AI cameras are affordable, while advanced models with deep learning, facial recognition, and ANPR cost more. Prices also depend on whether analytics run on-camera or on a central server.

AI-enabled CCTV systems cost more than traditional CCTV due to advanced processing hardware, analytics software, and storage requirements. The total cost includes cameras, servers, software licences, and installation. Because DhurgAI works with existing IP cameras, many deployments reuse the cameras already installed.

AI-based cameras in India are used for smart cities, traffic enforcement, retail analytics, industrial safety, and residential security. They provide automated detection, reduce manual monitoring, and improve response time in critical situations.

AI surveillance is used for traffic enforcement, crime prevention, industrial safety, and smart city monitoring across major cities. It improves public safety and operational efficiency.

The best fit depends on accuracy, features, deployment model, industry use case, and support quality. Strong solutions offer deep learning, edge AI, high accuracy, and scalable deployment options across multiple industries and use cases.

A video analytics company builds AI-powered video analytics platforms for security, operations, and business intelligence. They develop software, hardware, and integrated solutions, and provide deployment services.

Video analytics is done by using AI models for detection, tracking, and reasoning. It involves training models, deploying them, and integrating them with CCTV systems. The process includes data collection, model selection, testing, and real-time deployment.

An AI surveillance project integrates cameras, AI models, servers, dashboards, and alert systems for automated monitoring. It is used in industries, public spaces, and critical infrastructure.

AI monitors live video feeds, identifies threats, tracks objects, detects anomalies, and triggers alerts without human intervention. It enhances security, operational efficiency, and situational awareness. AI can also analyse historical footage to identify trends and patterns.

A video analytics course teaches AI, computer vision, object detection, tracking, and CCTV analytics fundamentals. It covers practical implementation, model training, and deployment techniques.