MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641085369 A) filed by Sri Eshwar College Of Engineering on July 11, 2026, for An Integrated Artificial-Intelligence-Driven Bus Monitoring Framework For Real-Time Passenger Overload Detection And Zone-Based Forgotten-Belonging Alerts.
Inventors include Karthik Sriram Sj; Pooja T; and Muthu Shyamala S.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: This invention is directed to a cohesive smart monitoring system to address two major problems that are often encountered in public bus transit systems: an overcrowded bus and the unintended loss of personal items. Overloading is a common issue in public transport systems, causing discomfort among passengers, an increase in the risk of accidents, a loss of vehicle stability and violation of the laws of transport safety. Currently, the maintenance of passenger capacity is based mainly on manual checks rather than continuous checks by automation. A common problem also happens when passengers leave their belongings, such as their mobile phones, wallets, handbags, laptops, documents or shopping bags, on their seats when getting off the bus. There is no real-time detection system on current buses, making it more likely that the items will be discovered too late to prevent theft or loss. The proposed system is a fusion of two intelligent subsystems in a single system. The first subsystem continuously monitors the on and off of the passengers by automatic counting sensors and compares the actual count of passengers with the legal number of capacities of the bus. If the number of passengers exceeds, the system will immediately recognize and record the situation of overloading. The second subsystem uses a zone monitoring approach, not having sensors on each seat. There are three observation zones in the bus and each has a motion detector. When any passengers are detected, an AI-based camera on the roof evaluates the area, determines the seat occupancy before and after the passengers and checks whether any objects have been left behind. If an item is not found, it will generate an alert in 1 second and the passenger can retrieve their belongings immediately. The system combines embedded sensor technology with AI and computer vision to provide an affordable, scalable solution that improves passenger safety, prevents theft and intelligently automates public transport.
Disclaimer: Curated by HT Syndication.
