Bharat in Betastartup field guide
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No. 1405Problem statementPublic services

A deployable AI-powered autonomous drone that aids search-and-rescue operations by detecting people and hazards, thereby improving responder safety and reducing victim discovery time.

Source

Source summary

Develop an autonomous disaster-response drone with RGB/thermal sensing and onboard AI for finding people and environmental hazards when connectivity is absent. Map affected areas, report risks and share prioritised insights with responders. Suggested components include GNSS-denied navigation/SLAM, obstacle avoidance, IMU/GPS fusion, geotagged survivor/hazard maps and a command dashboard; the source allows some or all of that component list. Core local inference/offline resilience should remain explicit.

No. 668Problem statementPublic services

Fire Fighting Drone for High-Rise buildings

The challenge proposes a drone to deliver firefighting foam at heights conventional vehicles cannot reach. Stated targets include delivery at 90 metres, a 60-litre-per-minute foam rate, a supporting vehicle with water and foam tanks for at least 20 minutes of firefighting, 45 minutes of flight endurance and 150 kg payload capacity. Optical and infrared cameras support remote viewing. A pump and integrated controls are required, with deployment from cold by two people within five minutes. These are proposed requirements, not validated performance.

No. 675Problem statementPublic services

UAS-Borne NBC Detection Capabilities along with ALS equipped UAS (modular)

Develop a modular UAS with two roles: real-time detection and identification of nuclear, biological and chemical hazards, and a roll-on/roll-off airborne life-saving module for search and rescue. The source requires portable, reliable payloads using onboard power without interference. The rescue configuration needs encrypted communications, relay support, autonomous/GPS-denied navigation, night and harsh-weather operation, at least two hours endurance and integration with existing rescue systems.

No. 737Problem statementPublic services

Development of an embedded solution for real -time image analysis using AI

Develop an embedded AI module that recognises flame or smoke in images and generates an alarm for a fire-detection/control system. The source emphasises economical use of hardware resources and integration of a prototype into a larger future system. Detection performance is not demonstrated by the brief.