Towards the application of UAS forroad maintenance at the Norvik Port

Abstract: One of the vital processes for the maintenance of infrastructure is the collection of information about the inventory and current state of the infrastructure. Such activities are mostly done manually by the inspector in the field. However, Unmanned Aerial Vehicles (UAV) offer the possibilities to improving the accuracy, precision, and efficiency of those tasks. The present dissertation focusses on the evaluation of the requirements and possibilities for the incorporation of UAV in the assessment of port infrastructure, with an emphasis on pavement infrastructure. The first step to reach the goal of the research was the elaboration of an extensive literature review where the leading practices and trends for the use of Unmanned Aerial Systems (UAS) were identified. Based on the literature review, it was possible to propose a roadmap for the implementation of the UAS in the assessment of port infrastructure. The roadmap was implemented in a case study for the Norvik port in Stockholm while the restrictions and information allowed. This research produced several key findings. First, it was possible to recognize the lack of precise definitions in the pavement assessment, the faults in the current manual collection of pavement distresses and the voids in an investigation regarding the recognition of pavement defects different than cracking as some of the critical problems in the area. Additionally, the current applications like bridge and structural inspection, and available technologies like LiDAR or visual sensors were identified along with its improvement opportunities and restrictions. The key steps for the implementation of a UAS for assessing infrastructure were formulated as the identification of the needs and critical parameters, the selection of the UAS components, mainly the UAV and sensor, and the postprocessing of the data. The main conclusion drawn from the research is that it is possible to use UAS to assess the state of the infrastructure. However, not all UAS are suitable for all situations or necessities. The selection of the UA, according to the needs and limitations of the project, plays a vital role regarding the viability of implementation of a UAS for monitoring port infrastructure. The sufficiency of a UAS is closely related on its capability to acquire the information of the selected structures, with the required quality, and overcome the limitations, challenges, and restrictions of the site of application. As a way forward, the most important element to address is the implementation of Machine Learning (ML) techniques and Artificial Intelligence (AI) to extract the relevant features of the data automatically.