Ph.D. Dissertation Defense at the College of Information Technology on
"Energy-Efficient Data Gathering and Device Localization Using an Unmanned Aerial Vehicle in IoT Network"


Duhaa Fadill Abbas
The Department of Information Networks at the College of Information Technology hosted the Ph.D. dissertation on "Energy-Efficient Data Gathering and Device Localization Using an Unmanned Aerial Vehicle in IoT Network" defense of candidate Soha Abdulhussein Abdulzahra Kashash, supervised by Dr. Ali Kadhem Mohammed, on Tuesday, May 13, 2025, at 9:00 a.m., in the Conference Hall of the College.

The dissertation presents an integrated framework aimed at enhancing data collection and accurate device localization in Internet of Things (IoT) networks supported by unmanned aerial vehicles (UAVs). The proposed system incorporates a two-phase localization technique that leverages the L-BFGS-B algorithm along with RSSI, TOA, and AOA indicators to improve positioning accuracy. Additionally, it introduces the FONIC protocol, which employs fuzzy logic and the PeSOA algorithm to efficiently select cluster heads in an energy-aware manner.

A hybrid path planning approach is also utilized, combining greedy algorithms, cubic interpolation, and redundant path isolation to minimize energy consumption. Simulation results demonstrated significant improvements, achieving a 59% reduction in energy consumption, a 49.7% decrease in flight time, and notable enhancements in localization accuracy and network lifespan.