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EcoInnovators Ideathon 2026 Finalists Announced - Click Here!
Global Learning Council

ECOINNOVATORS IDEATHON 2026

Innovate for the Planet
Build AI-powered solutions that verify rooftop solar installations under the PM Surya Ghar Yojana, ensuring transparency, trust, and real climate impact.
Powering Change with AI
Students harnessing AI and vibe coding to create low-cost, governance-ready systems that drive renewable energy adoption across India's households.
Recognised by Ministry of Electronics and Information Technology
Official Pre-Summit Event of the India AI Impact Summit 2026, reflecting the Ideathon’s alignment with India’s AI priorities & innovation ecosystem.
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The Innovation Pathway

1
LEVEL

Registration

Register online and kickstart your innovation journey.

Last Date: 14 November 25
2
LEVEL

Onboarding

You will attend a webinar explaining the problem statement and addressing your questions.

Webinar + Q&A

Dataset Release: Train/Test Csv + Starter Kit

Date: 17 November 25
3
LEVEL

Prototype Submission

You need to submit a working model for review

  • 1. Repo Link
  • 2. Dockerhub Link & Tags
  • 3. Model Card File
  • 4.Json Output
Last Date: 14 December 25
4
LEVEL

Shortlisting

The top 5-10 solutions will be shortlisted for the grand finale.

Last Date: 18 December 25
5
LEVEL

Grand Finale

Shortlisted candidates to give final presentations

20 Min Demo Of Their Model

5 Minutes Q&A.

Date: 12 January 2026 | Venue: Infosys Science Foundation, Bengaluru

Rules of Participation

  1. Open to undergraduate students across all streams.
  2. Teams of 1-3 students from the same college/university.
  3. You may use open-source libraries and permissible datasets with attribution.
  4. No use of private or illegally obtained imagery.
  5. Do not hard-code answers for the test set; submissions will be integrity-checked.
  6. Share a short license statement (preferably an OSI-approved license) in your repo.
Focus Areas
PM Surya Ghar: Muft Bijli Yojana is a government scheme that aims to provide free electricity to households in India. The scheme was launched by Prime Minister Narendra Modi on February 15, 2024. Under the scheme, households will be provided with a subsidy to install solar panels on their roofs. The scheme is expected to benefit 1 crore households across India. It is estimated that the scheme will save the government Rs. 75,000 crore per year in electricity costs.
Solar Energy
Governance for this scheme include the need to verify rooftop solar installations, so that subsidies reach genuine beneficiaries and public trust remains high. Field inspections alone are slow, costly, and uneven across states and DISCOMs. This challenge asks you to build a governance‑ready, auditable, and low‑cost remote verification digital pipeline that answers a simple question at any given coordinate (latitude, longitude):

“Has a rooftop solar system actually been installed here?”

Your system should work reliably across India's diverse roof types (sloped, flat roofs) and imaging conditions. The goal is not only accuracy, but also auditability and generalization across states.

Core Objectives (What your system must do)

When given an input folder location with a CSV containing list of geographic coordinates (latitude and longitude)

1. Fetch: Automatically retrieve or accept a recent, high-resolution rooftop image for a given (lat, lon). Be robust to small coordinate errors by searching within a configurable buffer (e.g., 10-20 m).

2. Classify: Run inference using your trained model and determine whether rooftop PV is present (binary: present / not present) and return a calibrated confidence score.

3. Quantify: If PV is present, estimate panel count, PV area (m²), and optionally capacity (kW) using a transparent assumption (e.g., Watt Peak/m²).

4. Explainability: Produce audit-friendly artifacts — polygon mask or bounding boxes, short “reason codes” (e.g., 'module grid', 'rectilinear array', 'racking shadows'), and a quality control (QC) status.

5. Store: JSON file for the test dataset into output folder location

Required QC status values:

· VERIFIABLE — Clear evidence either way (present/not present).

· NOT_VERIFIABLE — Insufficient evidence (e.g., low resolution, heavy shadow/cloud, occlusion by tanks/trees, stale imagery).

Ethics & Privacy Expectations

· Use only permissible imagery and respect licensing; cite all sources clearly.

· Document known biases (e.g., urban vs rural performance gaps) and mitigation steps.

Appendix: Definitions & Helpful Hints

· Capacity inference: document the Watt peak/m² or Watt peak/panel assumption with references.

· Buffer search: if (lat,lon) is slightly off, scan within ±10-20 m to lock onto the roof region.

Evaluation Criteria

Idea Icon
Your final score is a weighted aggregate across accuracy, auditability, efficiency, and ethics/operability.
Criterion
Metric / Evidence
Weight (%)
Detection accuracy
F1 score on has_solar
40
Quantification quality
MAE for area (m²); RMSE for capacity (kW)
20
Generalization & robustness
Performance across diverse states/roof types; handling look-alikes
20
Others - code quality, documentation, usability
Code quality, documentation, usability
20

You can access these resources for ideas and support

To access all the resources, you need to first register here -
Infosys Springboard
Once registered, you can access the following resources for ideas and inspiration.
You will receive:
Training dataset (train_rooftop_data.csv): id, lat, long, has_solar, panel_count (if positive), area_sqm (if positive), rooftop image
Test dataset (test_rooftop_data.csv): id, lat, long, rooftop image

You may use additional permissible imagery sources if they respect licensing and privacy. Clearly cite every external source you use.
artwork

The Prize

The winning team will participate in the Villars Symposium 2026 in Switzerland

Prize money for the Top 3 winners : Rs. 100,000 for the First Prize Rs. 50,000 each for Two Runner-Ups. .

Internship opportunities to the Top 3 winners - with the Centre for Responsible AI, IIT Madras

FAQ’s

Supported By National & Global Partners

Global Learning CouncilVillars InstituteIIT MadrasSchool of Sustainability IIT MadrasHpCSTEPInfosys Science FoundationInfosys SpringboardAXILORPratithi InvestmentsCapableMelloneSchoolnetCeraiNextgrids
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Inspiring Moments from Ideathon 2025

Ideation highlights
28th January 2025 - Infosys Science Foundation, Bangalore

Questions? Contact us!

glcideathon@schoolnetindia.com

Become An Eco Innovator!

Students Registered
3500+
Submissions Received
~120
From
10 States & UT
Finalists Shortlisted
6
Grand Finale on
12th Jan 2026