全程計畫以2年期執行，第1(110)年先完成臺中港區4,700公頃之高精度三維及正射底圖，接著由整合載具控制與取像邏輯之分析，建構無人機飛航作業之軟體流程，並基於該流程取得穩健影像資訊來源進行特徵辨識，最後建置系統整合平台將相關功能納入；第2(111)年則延續第1年成果，藉由3種改正方法的測試精進影像匹配方法，可轉至同視角與前期影像進行比較。此外，透過與其他無人機研發團隊所共同測試的跟隨技術、自動路徑規劃技術，無人機可成功沿著所規畫路徑飛行，同時可隨著車輛進行穩定飛行，定期蒐集的影像進行分析判識。在物件辨識方面，除原中突堤標的物缺漏視覺化呈現外，更提出PCI指標進行北堤路路面評估，成果也獲得相關可行性之驗證。此整合方案可應用於港區的巡檢任務，追蹤港區土地使用狀況以及特定設施之安全穩定性。

The study was intended to be implemented in two years. In the first year, a high-resolution 3D orthophoto map of the 4,700-ha port area was generated. That is followed by making the software process for UAV flight route planning by integrating UAV control and image acquisition logic; the details of robust images captured by that process will be put to image feature matching. Finally, a platform for system integration will be implemented. The second year followed the results of the first year, some improvements were done. Firstly, three correction methods were utilized to improve the performance of image matching. Furthermore, the UAV can successfully fly along the planned path, fly stably with the vehicle, and regularly collect images for further analysis.In terms of object identification, we presented the result in a visual way. Meanwhile, the PCI index was proposed to evaluate the road surface and the results were also verified successfully. Those methods and results can be applied in the patrol tasks of the port, tracking the condition of land use and the security of certain facilities.