Automated signal pre-emption system for emergency vehicles using internet of things - Sothenahalli Krishnaraju, Pushpa; Thimmasandra Narayanappa, Manjunath; Kathavate, Sheela; Shirwaikar, Rudresh; Chandrakanth Rao, Anupchandra Rao; Rohith, Jayachnadra (Institute of Advanced Engineering and Science, 2024)
Vehicle administration systems are one of the major highlights especially in urban areas. One important critical component that requires attention are signal preemption systems. Every single work on traffic congestion identification either requires prior learning or long time to distinguish and perceive the closeness of congestion. FutureSight performs predictive analysis and control of traffic signals through the application of machine learning to aide ambulances in such a way that, a signal turns green beforehand so as to ensure an obstacle free path to the ambulance from source to destination based on various parameters such as traffic density, congestion length, previous wait times, arrival time thereby eliminating the need for human intervention. The method allows flexible interface to the driver to enter the hospital details to reach the destination with in time. The app then plans out the fastest route from the pickup spot to the selected hospital and sends this route to the system. The system then predict the amount of time that is required by the signal to remain green so as to clear all traffic at that specific junction before the ambulance arrives at that location.