Artificial Intelligence is paving its way to most applications, providing real-time intelligence and quick decision-making capabilities. This trend is pretty much visible in Smart City initiatives too. Mistral’s AI based smart city solution can play a crucial role in Smart City projects. Our solution enables Government and law enforcement agencies with a keen understanding and learning about people’s behaviour to optimize the use of existing infrastructure and available resources and improve public safety.
Law enforcement and security agencies garner a large chunk of video data via the CCTV network in a city. Analysis of this video content has become a key challenge for these agencies, which either delays their response or get curbed due to the clutter of massive data. That’s where a structured method for analysis and management of the video content generated becomes a need of the hour. Mistral’s AI based video analytics platform aims at fulfilling this need.
Based on a cutting-edge Artificial Intelligence technology, Mistral’s AI based Video Analytics Engine processes live camera feeds to achieve the objectives of Smart City Mission (SCM) under Smart Urban Solutions, by providing improved visualization of ambient or emergency in the city and facilitating data-driven decision making. The AI Analytics follows an AI and ML approach, where at each step data is collected and analyzed, thereby improving the system in a continual manner.
Our solution enables several applications wherein video analytics plays a crucial role. License plate recognition (LPR), Smart Parking, Traffic Violation Detection, Public Transit Monitoring, and Crowd Management are a few applications that make your surveillance task easier and quicker.
Mistral’s AI based Video Analytics Solution has the capability to detect and recognize faces, differentiate vehicles, capture Signal Violations, provide Object Tracking across cameras, AI-Based Predictive Policing and more. The solution provides actionable intelligence based on the video captured from different sources. It can be used for on-site real-time analysis, or even for post-event investigations which integrates motion prediction and estimation strategies across frames reducing overall computation requirements.