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LakeSignal report builder with an evidence checklist
What is the specific problem, and how do I know it is real?
Bengaluru's lakes face documented environmental pressure. A 2016 Indian Institute of Science assessment of 105 lakes reported widespread impacts from untreated sewage and industrial effluents. This is historical, city-wide evidence; it does not prove a new incident at any specific lake today. The BBMP Lake Monitoring System also provides a path to Sahaaya 2.0 for lake-maintenance grievances, showing there is an official channel for residents to report issues.
When someone sees litter, unusual foam, an apparent inflow, or distressed wildlife, the useful first step is a specific record of what was visible, where, and when. LakeSignal is a prototype for preparing that record. I have not claimed a personal sighting or filed a complaint through this demo; its sample observation is explicitly fictional.
Sources: https://wgbis.ces.iisc.ac.in/biodiversity/pubs/ETR/ETR101/results.html and https://lms.bbmpgov.in/lake
What I built
LakeSignal is a browser-based report builder. A resident enters a waterbody, observation date, shoreline landmark, visible concern, and first-hand description, with an optional evidence link. The live checklist identifies missing essentials. Field-level validation prevents incomplete reports. A successful entry becomes a copyable and downloadable note with a request for inspection. The generated text explicitly states that observations alone cannot establish a pollutant, source, or measured water-quality result.
The draft stays in browser storage. LakeSignal does not collect accounts, send information to a server, or file complaints automatically. It links to BBMP's official lake channel so the resident can review and submit their report there if appropriate.
The built-in example is marked as fictional in the interface and the generated report. It exists only to show how the tool works.
How it was built
This project was built during the October 16–23, 2026 Neighborhood Hacks hacking period using HTML, CSS, and vanilla JavaScript. Browser localStorage keeps the draft on-device. The public repository shows the work. An AI assistant generated the initial code and design, created the synthetic demo narration, and helped test the prototype in a browser. Earlier lake-awareness projects informed the general subject, but no prior project code, design, or content was copied into LakeSignal.
Challenges and next steps
The hardest design choice was keeping the report useful while avoiding an implied environmental diagnosis. The app asks for visible details and labels the example repeatedly. A next version would add user-tested multilingual guidance, safe offline image handling, and an optional way to track official complaint numbers with the resident's consent. The prototype has not been tested with BBMP staff or real residents, so I do not claim it improves response times or lake conditions yet.
Links
Built With
- css
- html
- javascript
- localstorage
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