The terms “intelligent video analytics” (IVA) and “video analytics” often overlap in usage. Still, they can be distinguished by the level of sophistication in their capabilities and the technologies they employ. Here’s a breakdown of the main differences:
- Basic Functionality: Traditional video analytics uses software algorithms to analyze video feeds to detect basic patterns and conditions. This technology often focuses on simple motion detection, such as identifying movement within a designated area, or rule-based analysis, like line crossing and loitering detection.
- Rule-Based Processing: Video analytics typically uses pre-set rules or configurations to identify specific activities or behaviours. For example, it might be configured to alert if an object appears in a restricted zone or if a person moves in a certain direction.
- Limited Contextual Understanding: These systems do not usually incorporate advanced context or situational awareness. Their analysis is often limited to the rules they are programmed to follow, and they might struggle with complex scenarios or ambiguous situations.
Intelligent Video Analytics (IVA)
- Advanced Technologies: Intelligent video analytics builds on the foundation of traditional video analytics by incorporating more sophisticated technologies such as artificial intelligence (AI) and deep learning. This integration allows for more complex processing and understanding of video data.
- Deep Learning Capabilities: IVA uses AI models, particularly deep learning neural networks, to analyze video content. This allows the system to learn from vast amounts of video data and improve its accuracy and effectiveness over time. It can identify objects, classify behaviours, and predict future events based on learned patterns.
- Contextual and Situational Awareness: One of the significant advancements of IVA is its ability to understand context within a scene. For example, it can differentiate between a person loitering and someone merely standing still or recognize the difference between a vehicle parked illegally and one loading or unloading goods.
- Proactive Responses and Insights: IVA not only detects and alerts based on video content but also provides actionable insights that can be used for more proactive responses. For instance, it might analyze shopper behaviours in a store to improve layout and marketing strategies or monitor traffic patterns to optimize urban planning.
While video analytics provides the foundational technology for monitoring and detecting specific activities based on predefined rules, intelligent video analytics enhances and extends these capabilities by incorporating AI to deliver deeper insights, predictive analytics, and more contextually aware responses. This makes IVA particularly valuable in high-precision, adaptability, and understanding scenarios.