New obstacle detection system to protect on-road cows and other animals

In a bid to protect animal on roads, a doctoral student at Gujarat Technological University has developed a real-time automatic obstacle detection and alert system that will help cars avoid colliding with cows and other animals on the road. 

Sachin Sharma, a PhD student of Electronics and Communications Department and his supervisor Dharmesh Shah have filed for a patent of the product they have developed.

Shah, former dean at GTU who is now into business, said the aim was to help drivers by warnign them about the obstacle on the road. “Foreign countries have many innovative measures like fencing the highway to restrict animals, or placing RIFD chip to locate strays and warn cars on the highway. These measures may not be feasible for India and that is why we thought of developing this system. The system uses a dashboard camera and an algorithm that can determine whether an object near the vehicle is an on-road cow and whether or not its movements represent a risk to the vehicle”, said Shah.

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A timely audio or visual indicator can then be triggered to nudge the driver to apply the brakes whether or not they have seen the animal, he added.

The system uses a dashboard camera and an algorithm that can determine whether an object near the vehicle is an on-road cow and whether or not its movements indicates a risk to the vehicle.

Referring to its efficiency Sharma said, “The proposed system has achieved an overall efficiency of 80 per cent in terms of cow detection. With the system, we can alert the driver if there is a cow within a distance of 30 metres on the road. We are working on improving the distance alarm to around 60 metre to 80 metre”.

According to the researchers the system is highly reliable with a low-cost and can be easily implemented in automobiles for detection of cow or any other animal after proper training and testing on the highway.

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The algorithm requires optimisation and the issue of night-time driving is yet to be addressed, the team stated in an article in International Journal of Vehicle Autonomous Systems.