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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62155
Volume:
10 |
4 |
April 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Artificial Intelligence And Machine Learning
Ballari Institute Of Technology And Management

Artificial Intelligence And Machine Learning
Ballari Institute Of Technology And Management

Artificial Intelligence And Machine Learning
Ballari Institute Of Technology And Management

Artificial Intelligence And Machine Learning
Ballari Institute Of Technology And Management

Artificial Intelligence And Machine Learning
Ballari Institute Of Technology And Management
This paper introduces a new way to improve emergency healthcare by using automated drones to deliver first aid kits. The system relies on standard components and operates fully automated through Radio Link Mission Planner software. This solution tackles the issue of quickly delivering first aid kits to remote locations, with the goal of boosting survival chances before human responders can arrive. Testing shows that the system can configure missions quickly, deliver kits accurately, and operate reliably on its own.
KEYWORDS
DroneAid demonstrates the power of robotisation, telemetry, and intelligent software in transubstantiating exigency first aid delivery. Unlike traditional styles, this system delivers rapid-fire, dependable, and harmonious results, minimising response times, maximising delivery delicacy, and furnishing a straightforward interface for exigency labour force. Experimental results confirm high functional success with average charge completion in under 7 twinkles, a charge delicacy of 95, and high stoner satisfaction conditions from drivers and first askers. Remaining challenges include conforming to different surroundings, enhancing telemetry for weak- signal scripts, and supporting broader integration with external systems. Unborn development will concentrate on larger cargo options, better security protocols, and expanded interoperability with healthcare and emergency networks. DroneAid stands poised to advance automated exigency response logistics, making critical care more accessible, timely, and reliable in critical situations.
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Publication Date
5/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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