Bharat in Betastartup field guide
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No. 1234Problem statementPublic services

AI-Based early warning and landslide Risk Monitoring System in NER

Source

Source summary

MDoNER asks for AI-based landslide monitoring in the North Eastern Region, combining rainfall, soil moisture, satellite imagery, terrain and historical events. The platform should map vulnerable roads, villages and infrastructure, accept geo-tagged field reports, predict risk and send multilingual alerts to authorities and communities. IMD and sensor integration, SMS/app notifications and offline collection with later synchronization are part of the requested design.

No. 273Problem statementPublic services

Evaluate and optimize an existing open-source speech-to-text transcription tool for accurately converting feedback calls related to citizen grievances into English text.

Benchmark and improve an existing open-source speech-to-text tool for citizen grievance feedback calls in Hindi, English and Hinglish, producing English text. The source explicitly excludes building an entirely new system and asks for measurable improvements in transcription accuracy.

No. 274Problem statementPublic services

Develop an AI/ML-driven system for granular monitoring, logging and analysis of the existing auto-routing system

Monitor and analyse existing grievance auto-routing to identify misdirected cases and compare agency redressal performance. The source asks that repeated complaints by habitual complainants not distort rankings. A possible web/mobile dashboard is for DARPG and relevant officials, informed by the existing GRAI ranking framework.

No. 275Problem statementPublic services

Develop UI/UX solutions to improve adoption and usability (by Government Agencies/Officers) of DARPG portal/tool such as Tree Dashboard and IGMS website.

Improve the usability and adoption of DARPG tools such as the Tree Dashboard and IGMS website by government agencies and officers. The source asks for UI/UX work on existing tools, rather than a new citizen grievance platform.