UP To Deploy AI-Powered Footfall System At Major Religious Sites For Tourist Management | Key Features

Tourist movement at Uttar Pradesh’s major pilgrimage and tourist destinations will soon be tracked using Artificial Intelligence (AI). In the first phase, the system will be implemented at Kashi Vishwanath Dham in Varanasi, the Shri Ram Mandir in Ayodhya, and the Gorakhnath Temple in Gorakhpur.

According to Tourism Minister Jaiveer Singh, the camera-based ‘Footfall Counting System’ will provide real-time data on visitor numbers, helping improve crowd management, security, sanitation, and infrastructure planning. The Tourism Department has invited Expressions of Interest (EOI) from agencies to execute the project.

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This AI-driven initiative will integrate advanced features such as face recognition, behavioural analysis, crowd density monitoring, and emergency response systems. The minister added that the technology will enable data-backed decisions for effective tourism policy and management.

The Footfall Counting System functions by using AI-powered cameras to track and count visitors at entry and exit points, offering precise analytics on movement patterns and crowd flow in real time.

How it works:

-Camera and Analysis: The system uses cameras installed at entry and exit points to capture video. Software: A software or AI algorithm analyses this video to identify and count people. 

-Data Collection: This system collects data such as visitor visit times, frequencies, and other behaviours. 

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Key Features and Benefits:

-Accuracy: It provides very accurate counts by using advanced technologies like AI and 3D stereoscopic cameras. 

-Data and Analysis: It goes beyond mere counting to analyse visitor behaviour, crowd density, and flow, which helps in effective management. 

-Security: It can ensure security monitoring and a quick response in emergencies. 

-Identification: It can identify duplicate visitors and exclude staff from the count. 

-Visibility: It can work in various lighting conditions and helps in identifying people even if they are close to each other.