Modifying Hata-Davidson Propagation Model for Remote Sensing in Complex Environments Using a Multifactional Drone

Area of Science:

• Engineering
• Computer Science
• Disaster Management

Background:

• Drones integrated with the Internet of Things (IoT) enhance safety and smart living.
• Drones are crucial for mobile remote sensing in search-and-rescue (SAR) operations.
• Efficient drone operations can significantly improve survival rates for victims.

Purpose of the Study:

• To modify the Hata-Davidson empirical propagation model for drone-based SAR in complex terrains.
• To improve radio frequency (RF) connectivity and coverage footprint for SAR drones.
• To enhance the timely performance of SAR operations using strip search patterns.

Main Methods:

• A drone equipped with a thermal camera, microcontroller, GPS, and weather sensors was utilized.
• The Hata-Davidson model was modified using a least squares tuning algorithm with drone RF measurement data.
• Both software simulations and hardware implementations were considered in model development.

Main Results:

• The modified model improved RF connectivity between drones and local authorities.
• Enhanced coverage footprint led to more effective wider SAR operations.
• The modified Hata-Davidson model demonstrated superior performance compared to other empirical models via RMSE validation.

Conclusions:

• The modified Hata-Davidson model offers improved performance for drone-based SAR.
• The model aids in timely identification and location of missing persons using thermal imaging and GPS.
• This research contributes to making human life safer through advanced drone technology.