IIT Madras Organises Hackathon to Resolve Indian Traffic Problems

Diksha Nautiyal

Updated On: August 13, 2019 03:07 pm IST

In a Hackathon organised by IIT Madras Alumni Association, 50 teams make it to Phase 2 after competing with a total of 3,266 teams in the first phase. IIT Madras will be hosting the second phase of the competition on campus. 

IIT Madras, Hackathon 2019, Solves Traffic Promblems, Sangam 2019

With the announcement of the top 50 teams, IITMAA (IIT Madras Alumni Association) organised Machine Learning Hackathon Contest for solving the traffic problems in major Indian cities. The Hackathon is included in the flagship event of IIT Madras: ‘Sangam’, which is celebrated on an annual basis. In the first phase of the Hackathon, about 3,266 teams participated. Phase 1 of the Hackathon was conducted in an online mode in which the top teams reached the accuracy of up to 99.97%. To attain the highest prediction accuracy, the teams used Regression models like XGBoost.

Candidates from across the country including Delhi NCR, Mumbai, Pune, Chennai, Bengaluru, Kolkata, Coimbatore, etc joined to participate in the competition. A total of 50 teams topped the first phase of the competition. These teams included students from IIT Kharagpur, IIT Bombay, IIT Delhi, IIT Roorkee, Indian Statistical Institute, IIT Madras, NIT Jamshedpur, NIT Patna and Army Institue of Technology, Pune.

Unlike Phase 1, the second phase of the Hackathon will be conducted at the IIT Madras campus. The phase is set to be organised on 24th and 25th August 2019. The competition will provide the teams with Time series data on pollution and air quality by the Internet of Things (IoT) devices.

Also Read: EveryBusiness Needs Data Science : IIIT NR Chairperson Ajai Chowdhary

By promoting such initiatives, IITMAA is contributing to the nation’s growth. With the help of such ML / AI analysis and models, not only will it make the traffic management effective, but also help in analysing and observing the correlation between Traffic Volume and Air Pollution Index, consequently bettering the traffic situations in the country.

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