The construction industry is on the path to digital transformation. One of the main challenges in this process is inspecting, assessing, and maintaining civil infrastructures and construction elements. However, Artificial Intelligence (AI) and Unmanned Aerial Vehicles (UAVs) can support the tedious and time-consuming work inspection processes. This article presents an innovative object detection-based system which enables the detection and geo-referencing of different traffic signs from RGB images captured by a drone’s onboard camera, thus improving the realization of road element inventories in civil infrastructures. The computer vision component follows the typical methodology for a deep-learning-based SW: dataset creation, election and training of the most accurate object detection model, and testing. The result is the creation of a new dataset with a wider variety of traffic signs and an object detection-based system using Faster R-CNN to enable the detection and geo-location of traffic signs from drone-captured images. Despite some significant challenges, such as the lack of drone-captured images with labeled traffic signs and the imbalance in the number of images for traffic signal detection, the computer vision component allows for the accurate detection of traffic signs from UAV images.

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This paper outlines the results evidenced by WellCo (GA nº: 769765), an European project funded by the European Commission within its H2020 programme under the personalised medicine call. The aim of this project was to develop and validate how ICT technologies may engage people to adopt healthier behaviour choices that improve their wellbeing status for as long as possible. Using data from wearable devices and AI-based algorithms, WellCo assesses the status of the user in terms of wellbeing and the risk of CVD. Using this information, WellCo develops an affective-aware coach that empowers users in the process of change of behaviour through the provision of interventions tailored to their current mood and life context. These motivational activities ranged from recommendations, goals to achieve, interactions with people in the social network, tips from experts and supporting groups suggested by the platform and adapted to their needs. The project has been validated with ageing people in Italy, Denmark and Spain. Despite the COVID-19 situation, results are very promising in terms of the possibilities that ICT technologies have for health promotion and set the basis for further research in this direction.