As groundwater levels continue to decline in several parts of India, a school student from Surat is using artificial intelligence to explore a possible solution. Dheyay Shah has developed a machine-learning model that estimates groundwater availability by analysing borewell records, rainfall patterns and soil-related data. His innovation has now earned him national recognition.
Titled JALAAKAR – The Shape of Water: Predict, Alert, and Act, the project secured the top honour at the fourth edition of vivo Ignite 2026, a nationwide technology and innovation challenge for school students. Shah’s idea stood out among thousands of entries submitted by students across the country.
His achievement reflects how school students are taking classroom learning beyond textbooks and using technology to explore solutions to pressing real-world challenges.
HOW CAN MACHINE LEARNING HELP PREDICT GROUNDWATER AVAILABILITY?
JALAAKAR uses historical groundwater records, rainfall information and soil-related data to estimate water availability at the taluka level. By identifying patterns across these datasets, the model generates estimates that could help communities assess groundwater conditions and make more informed decisions about water use.
In several parts of India, households and agricultural communities depend heavily on borewells, making groundwater monitoring particularly important. By combining different sources of historical data, Shah’s project explores how data-driven tools could contribute to more informed groundwater management.
However, the organisers have not disclosed the model’s prediction accuracy, independent validation results or whether it has been deployed in real-world water management systems.
WHAT DID OTHER STUDENTS DEVELOP?
Shah was among 13 young innovators recognised for 10 projects at the national finale. Their ideas addressed challenges ranging from water conservation and pollution to women’s safety, road safety and assistive technology.
The second-ranked project, JalRakshak, was developed by Vidyut Sundar and Shreyan Limaye of Dhirubhai Ambani International School, Mumbai. It uses borewell-specific time-series analysis to anticipate declining water levels by considering rainfall recharge and groundwater extraction.
Another notable entry, HydroPlastiNet, was developed by Anish Srinivas, Achyutha Pranav V Subramanian and Akhilesh Ram R of Padma Seshadri Bala Bhavan Senior Secondary School, Chennai. The proposed filtration system combines mechanical filtration, bentonite and activated charcoal to trap microplastics and adsorb dissolved pollutants.
Other shortlisted innovations included Project Unmuted, designed to guide women facing cybercrime; Project DrishtiBodh, a LiDAR-based safety collar for visually impaired people; and AquaSentinel AI, which aims to estimate fluoride concentrations in school drinking water.
OVER 6,100 IDEAS, 705 DISTRICTS: THE SCALE OF THE CHALLENGE
The fourth edition of vivo Ignite attracted more than 38,000 registrations, with students submitting over 6,100 ideas from more than 12,000 schools across 705 districts. The initiative saw participation from all 28 states and eight Union Territories, including 92 Aspirational Districts.
Shortlisted projects were evaluated by a panel of academicians and industry experts on parameters such as creativity, scientific application, feasibility, cost-effectiveness and potential social impact. The programme offers educational scholarships and rewards worth up to Rs 35 lakh, in accordance with its terms and conditions.
From groundwater prediction and water purification to women’s safety and assistive technology, the projects show how young innovators are taking classroom learning beyond textbooks. While several ideas may require further testing and development before they can be implemented at scale, they reflect the potential of school-level innovation to address some of India’s pressing challenges.
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