Sleep Detector Device Aims To Facilitate Road Safety

Sleep Detector Device Aims To Facilitate Road Safety

Students' Corner November 2018 Sleep Detector Device UPES University

Two young engineering students – Lakshya Gupta (Above) and Jaldeep Giniya (Below) of Dehradun-based UPES University – have developed a ‘Sleep Detector’ device aimed at reducing road accidents in the country.


Umbeo Tech was kick-started by two engineering students – Lakshya Gupta and Jaldeep Giniya of Dehradun-based UPES University – aimed at providing solutions to real-world problems leveraging technologies such as computer vision, machine learning, and artificial intelligence. The talented duo recently designed a Sleep Detector device that focusses on reducing road accidents in the country. This device facilitates timely detection of a car driver’s drowsy state, alerts him and prevents occurrence of any accident.


Road rage is a serious issue in India – if statistics are anything to go by, there is one death every four minutes due to a road accident in India. In fact, 30 % of road accidents are caused by driver drowsiness. This has been a huge concern area in India as precious lives are being lost or people have to live with injuries due to either their own callousness or the callousness of others on road. A road accident can occur within a split second but could have far-reaching consequences. The traffic police of various states, especially Kerala (where a young violinist lost his life along with his daughter because the driver at the wheel of the car fell asleep while driving), have been undertaking efforts to raise awareness about road safety and the perils of getting drowsy while driving. However, it is important to understand that one cannot always avoid drowsiness while driving as even the best of drivers at times, can feel drowsy behind the wheel. The reasons for feeling drowsy could be many, including not having had adequate sleep or not taking enough breaks on a long drive.

The ‘Sleep Detector’ is required to be fitted in the windshield of a car and detects drowiness based on facial expressions


Gupta and Giniya identified the opportunity and diligently worked on developing a solution, which is yet to be tested in the market. They have engaged in talks with the Uttarakhand state government for installing this device in all state transport buses, provided it successfully conforms to the government’s tests and requirements. The innovators of ‘Sleep Detector’ are also winners of the Startup Yatra Uttarakhand award.

The product, which has been christened “Sleep Detector”, is required to be fitted in the windshield of a four-wheeler, where it detects the sleepiness or lethargy of the driver based on facial expressions and alerts him in time. The product is based on the technology of computer vision and machine learning. A small camera embedded in the device feeds into a processor, which identifies the driver’s face and eyes and measures his facial patterns at the time he is drowsy or is about to fall asleep. Thus, this new technology is able to send out timely alerts or warn the driver to prevent the occurrence of any accidents.


Driver drowsiness detection is an advanced driver assistance system (ADAS) that is now offered in many premium vehicles by manufacturers across the world. The solution developed by the young students at UPES is praiseworthy, considering their device is priced at around Rs 3,000 per piece, and is claimed to be user-friendly and cost-effective. In a country that accounts for 1.5 lakh road-related fatalities each year, any technology that helps avoid accidents can help minimise human and financial losses.

The scope of the use of the ‘Sleep Detector’ is immense and can be extended to transport vehicles of other states as well as private vehicles, said the students. Additionally, this ‘Sleep Detector’ can also assist in gathering information on the driving habits of individuals, avoiding accidents, minimising loss of human life and financial losses, and enhancing connectivity on highways due to a reduced number of accidents causing traffic jams.