This thesis considers a UAV-assisted IoT network, where an unmanned aerial vehicle (UAV) is deployed to collect status update data from various heterogeneous sensors monitoring physical processes. The UAV then transmits the collected data to a base station using LoRa (Long Range) communication, which is known for its low-power, low-cost, and long-range capabilities. However, in urban environments, the effectiveness of LoRa can be significantly compromised due to diverse physical settings, signal interference, and obstructions, making it difficult to determine the optimal locations for transferring the collected data to the base station. The primary objective of this thesis is to develop a comprehensive system that leverages a UAV to optimize data collection from sensor networks within an unknown environment, where the LoRa signal qualities of different locations are not predetermined.