TrialsNet

This case will be implemented in two areas within the Greek Cluster: the Athens International Airport and the public infrastructure provided by DAEM in the Municipality of Athens. The solution will utilise data from various sources, such as municipal vehicles, weather information, security cameras, drones and robots, to assess the structural health of buildings, pavements, and roads. The data collected will allow for more efficient and effective proactive management of public infrastructure assets, leading to cost savings and improved operations and services.

Augmented Reality (AR) will allow construction workers to have an on-site view of buildings or other assets blueprints and receive live bidirectional communications with remote experts who can provide assistance and video instructions. Remotely controlled or unmanned vehicles will reduce risk and accelerate the building process. AI techniques, such as Neural Networks (NN) and Deep Learning (DL), will be used to assess the state of public infrastructure assets, produce alerts and suggestions for city authorities, improve workers’ safety, and schedule predictive maintenance. Digital Twins of public construction sites will validate complicated technical plans without wasting physical resources.