Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Conference Paper
Publisher : 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017
Source : 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017, Institute of Electrical and Electronics Engineers Inc. (2018)
Keywords : Accidents, Ambulance services, Ambulances, Artificial intelligence, Central servers, Delay control systems, Design and implementations, Emergency services, Emergency situation, Emergency traffic control, GPS location, Inter vehicle communications, Location, Real-time traffic control, Traffic congestion, Traffic control, Traffic management, Traffic signals
Campus : Bengaluru
School : School of Engineering
Department : Electronics and Communication
Year : 2018
Abstract : pAccording to the recent survey there are thousands of people losing their lives due to the delay in the emergency services. Experts say that 3,000 more heart attack victims could be saved each year if 90 per cent of the delay could be minimized. And in the present scenario the number of deaths are in lakhs and this number can be effectively reduced by providing timely and accurate ambulance service. By avoiding the unnecessary time delay near traffic jams during an emergency situation. The shortest and the most efficient route that is asphalt constructed to the accident spot or the required location is displayed and the central server checks for the vehicles location and changes the traffic signal when the ambulance is approaching the traffic lights. The design and implementation of this technique is directly targeted for traffic management so that emergency service vehicles on road get a better way to reach their destination in shorter duration, efficiently and without any interference. © 2017 IEEE./p
Cite this Research Publication : D. Vishal, Reddy, R. J., M. Abhirami, B., and Dr. T. K. Ramesh, “Real Time Traffic Control for Emergency Service Vehicles”, in 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017, 2018.