Students and Faculty Innovators from the Indian Institute of Technology (IIT) Mandi, have developed a Smart Road Monitoring System to prevent accidents caused at sharp/ blind turns, causing fatalities and injuries and enhanced traffic management.
With a surge in increased traffic, the manual interface becomes a challenge to control and prevent road accidents, and traffic management especially in the hilly terrains. Traffic Police intervention, convex mirrors installation, and other techniques, though helpful in these situations, become difficult to manage in severe and extreme conditions like rainfall, snow, foggy weathers and high number of sharp curves.
To address this, Dr. Kala Venkata Uday, Assistant Professor, School of Engineering, IIT Mandi, along with his team of B.Tech. students from the 2016 – 20 batch including, Naman Chaudhary and Shishir Asthana from Mechanical Engineering; Amudhan Muthaiah from Electrical Engineering, and Nidhika Kadela from Civil Engineering, have developed a monitoring system that can be used for speed detection, vehicle counts, enhanced traffic control and road usage, by employing the Micro-Electro-Mechanical Systems(MEMS) and Internet of Things (IoT) technologies.
The developed system comprises two layers of detection units on each side of the turn and two signaling units to alert the drivers. When a vehicle passes through the two consecutive layers of detection units, the sensing system detects the speed, direction and type of vehicle (two/ four/ multiple wheels). The detected direction confirms if the vehicle is advancing towards the turn, and a corresponding signal (light/ sound/ barrier) is displayed on the other side to alert the drivers of an oncoming vehicle. If the vehicle moves away from the curve, no signal is displayed. The signals are decided based on the speed, direction, gradient of slope and type of vehicle.
Explaining the applications of the developed innovation, Dr. K. V. Uday, Assistant Professor, School of Engineering, IIT Mandi, said, “This technique will not only reduce the accident risk in sharp curves, but will also help in reducing human intervention on traffic counts, management and helps in decision making.”
Apart from alarming the curves, the developed system can also be used for vehicle counts and its advanced versions will also be able to detect the load of the vehicle. This data can be used for enhanced traffic management, road use, traffic flow on single line tunnels and restricted areas by employing Artificial Intelligence and Machine learning tools. The prediction on traffic jams, increased flows and diversion alerts also can also be generated after sufficient data collection.
Being mechanical in nature, the developed system can work in any weather including rain, snow, fog or other poor visibility conditions and the data can be encrypted and shared to only appropriate stakeholders.
“Though existing technologies are effective, their effectiveness drastically is affected during adverse weather conditions, that is where our system is robust”, added Dr. K.V. Uday.
At a prototype development stage, the system costs less than Rs. 20,000 excluding the alerting units per curve. However, the innovators are currently working on the commercial aspects and trying to bring down the overall product cost, by lowering operating & maintenance costs, and utilizing alternative energy sources to make the system self-sustainable using solar energy.
IIT Mandi has a unique project-based approach to B.Tech. learning. The Institute’s Undergraduate programs are designed from scratch which gives students the ability to tackle real-world problems, to work in teams across disciplines and to deliver value to society. This project got initiated from the idea projected in a practicals course, Design Practicum, by 2nd year B. Tech. students of IIT Mandi. by Identifying the severity and the extent of the traffic and road accident issues. Dr. K.V. Uday and his team decided to address this societal problem using technology. This development reinforces ‘Learn by doing’, the vision of IIT Mandi.
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