在這篇論文，我們使用無人機 (UAV) 從地面物聯網設備收集數據。每個設備都有一定量的數據可以在特定的時間範圍內發送到無人機。
我們的目標是規劃無人機的飛行路徑，收集物聯網設備的數據，最大化無人機可以獲得的利潤。由於此一問題是一個NP-hard的問題， 我們提出一個三階段的啟發式算法來解決這個問題。
在第一階段，我們解決旅行推銷員問題（Traveling-Salesman Problem, TSP) 以找到無人機的飛行軌跡。 在第二階段，我們提出一個演算法，對於不能滿足時間限制的設備，我們可以改變無人機收集資料的順序或將物聯網設備從飛行軌跡中移除。
第三階段，降低第二階段獲得的無人機飛行距離。
模擬結果顯示，所提出的算法在總獲利和執行時間方面優於一些基線的方法。

In this thesis, we use unmanned aerial vehicles (UAVs) to collect data from IoT devices on the ground. Each device has an amount of data that can be sent to the UAV during a specific time window.
Our objective is to maximize the total profit that the UAV can collect the data from the IoT devices. Since the problem is NP-hard, we propose a heuristic algorithm in three stages to solve the problem.
We solve the Traveling-Salesman Problem (TSP) problem in the first stage to find the UAV's flying trajectory. In the second stage, we propose an algorithm to change the visiting order or remove IoT devices from the flying trajectory if we cannot satisfy their time constraints.
In the third stage, we improve the UAV's flying distance established in the second stage.
The simulation results show that the proposed algorithms outperform some baselines in terms of total profit and execution time.

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