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Almeida, Pedro Gabriel de Faria Lapa Barbosa de
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- Pavement Inspection in Transport Infrastructures Using Unmanned Aerial Vehicles (UAVs)Publication . Feitosa, Ianca; Santos, Bertha; Almeida, Pedro Gabriel deThe growing demand for the transportation of goods and people has led to an increasing reliance on transportation infrastructure, which, in turn, subjects the pavements to high traffic volumes. In order to maintain adequate service and safety standards for users, it is essential to establish effective maintenance strategies that ensure the preservation of pavement conditions. As a result, emerging innovations in pavement surface inspection methods, surpassing traditional techniques in terms of inspection and data processing speed and accuracy, have garnered significant attention. One such groundbreaking innovation in inspection systems that has been tested and used in recent years to assess infrastructure condition is the use of unmanned aerial vehicles (UAVs). This study aims to present a critical open-access literature review on the use of UAVs in the inspection of transportation infrastructure pavement in order to assess the type of equipment used, the technology involved, applicability conditions, data processing, and future evolution. The analysis of relevant literature suggests that the integration of intelligent technologies substantially enhances the accuracy of data collection and the detection of pavement distress. Furthermore, it is evident that most applications and research efforts are oriented towards exploring image processing techniques for the creation of 3D pavement models and distress detection and classification.
- Validation of an indirect data collection method to assess airport pavement conditionPublication . Santos, Bertha; Almeida, Pedro Gabriel De; Feitosa, Ianca; Lima, DéboraIn this study the authors compare two methods for airport asphalt pavement distress data collection applied on the main runway of Amílcar Cabral international airport, located at Sal Island in Cape Verde. The two methods used for testing were traditional visual inspection (on-foot) and an indirect method using a vehicle equipped with image capture and recording, lasers and geolocation devices (in-vehicle inspection). The aim of this research is to contribute to the validation of the proposed low-cost in-vehicle pavement distress inspection system with semiautomatic data processing in order to be considered in the implementation of the pavement condition assessment component of airport pavement management systems (APMS). This is a particularly important component as from the collected distress data it is possible to assess the condition of the pavements and define intervention strategies. Validation of the indirect data collection method is evaluated by statistical comparison of the collected distress data and pavement condition index (PCI) obtained from both methods. Statistically non-significant differences between the result sets validate the proposed indirect method, however the analysis evidenced two aspects that need improvement in the proposed system, namely the quality of the captured images to identify distresses with lower severity level and inspector training for proper allocation of severity levels during image analysis. This results in significant advantages considering that the total amount of the runway pavement area is inspected. Inspection time is reduced and data collection cost can be reduced. Processing and results visualization on GIS environment allows revaluation of the dataset on the in-vehicle method. Data interpretation and measurements quality control becomes simpler and faster.