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Development of Semi-Autonomous Drone Systems for Efficient Delivery of Medical Supplies in Remote and Disaster Affected Areas

Author

Listed:
  • A Praveena
  • Allwin Suresh
  • Ajay Kumar
  • Guna M
  • Guruprasath K

Abstract

This project presents the design and development of a semi-autonomous drone system that integrates advanced technologies to enhance its operational efficiency, adaptability, and functionality. The system incorporates multiple components, including an LCD display for real-time data monitoring, a GSM module for remote communication, and a GPS module for autonomous navigation. A key innovation in this system is the human identification feature, which utilizes wireless cameras and image processing techniques to detect and track individuals within the drone’s operational range. The system offers dual-mode operation, allowing for both manual control via a joystick and autonomous flight through GPS-based waypoint navigation. The wireless camera integration enhances real-time monitoring by capturing live video feeds, which are processed to recognize human subjects, making it suitable for applications such as surveillance, security, search and rescue, and crowd monitoring. The GSM functionality enables the system to send status updates, alerts, or emergency notifications via SMS, ensuring efficient remote communication. By combining manual operation, autonomous flight, and AI-driven human identification, this project demonstrates a versatile, efficient, and intelligent drone system. The integration of these technologies creates a cost-effective and adaptable solution that can be deployed in various real-world scenarios requiring real-time situational awareness, human recognition, and precision navigation.

Suggested Citation

  • A Praveena & Allwin Suresh & Ajay Kumar & Guna M & Guruprasath K, 2025. "Development of Semi-Autonomous Drone Systems for Efficient Delivery of Medical Supplies in Remote and Disaster Affected Areas," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 12(2), pages 197-211, April.
  • Handle: RePEc:etm:ijsrst:v12:y2025:i2:id:645
    DOI: 10.32628/IJSRST25122213
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