Bharat in Betastartup field guide
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No. 1984Opportunity areaSpace and research

AI/ML-Based Integrated heavy rainfall Early Warning and Inundation Prediction System using Satellite, Radar, observational Weather and numerical weather prediction model data.

Source

Source topic

The source proposes AI/ML heavy-rainfall warning and inundation prediction using satellite, radar, observed weather and numerical prediction data together. The saved description is topic-level and does not specify lead time, geography, model architecture or validation thresholds.

No. 528Problem statementSpace and research

Analysis of SAR imagery using various tech to include SAR & EO Imagery fusion and Metadata exploitation.

The source notes that synthetic-aperture-radar imagery remains useful at night and in bad weather but is hard to interpret without optical references and specialist knowledge. It suggests, rather than mandates, fusing SAR and electro-optical imagery, extracting changes, and using user-defined stable terrain, infrastructure or standard targets to enhance readability. It also asks for software that exposes material-related information derivable from SAR metadata while keeping observations distinguishable from enhanced or substituted content.

No. 592Problem statementSpace and research

Training Simulator for Space Activities

Develop a software simulator for periodic training on dynamic space-based contingency scenarios and for testing proposed countermeasures once they exist. The simulator should be scalable so additional feasible scenarios and their countermeasures can be incorporated over time; the page does not define scenario content or evaluation metrics.

No. 622Problem statementSpace and research

Development of an Indigenous Tool for Space Domain Training Surveillance and Operations in the Indian Air Force (IAF)

Develop an indigenous Indian Air Force tool for space-domain training, surveillance and operations. It must support user-defined volumetric scans, proximity screening around Indian satellites, conjunction and collision analysis, coverage-gap and manoeuvre detection, space-object correlation and cataloguing, re-entry assessment and rapid processing of selected sub-orbital activity. The software and hardware must run in the IAF network, accept open, high-definition ephemeris and authorised internal data, follow the required development and certification process, scale to later capabilities, remain maintained by the developer and use perpetual licensing. Sensitive operational details are intentionally omitted.