An Automated and Integrated Sensing System for Road Monitoring using UAV Images and an Optimized R-CNN DOI Open Access

Vincenzo Barrile,

Francesco Scopelliti,

Emanuela Genovese

et al.

WSEAS TRANSACTIONS ON SIGNAL PROCESSING, Journal Year: 2025, Volume and Issue: 21, P. 31 - 40

Published: April 7, 2025

One of the most relevant, but at same time time-consuming and costly, aspects infrastructure system is monitoring road infrastructures, often subject to deterioration that compromises their use. Current systems consist individual reports or use human resources that, through equipped vehicles, have purpose carrying out a reconnaissance process, which characterized by errors uncertainties. In this context, aim work was experiment implement an experimental innovative Automated Integrated Sensing System (AISS) for infrastructures. This system, starting from Remote images Unmanned Aerial Vehicles (UAVs), uses Mask R-CNN neural network identify cracks. information, together with other included in database, then used Geographical Information (GIS) relative visualization. therefore proposes methodology implementation helps policy makers determining urgent interventions. fact, categorization severity degradation user-friendly visualization, allow us make decisions based on data.

Language: Английский

Optimizing Drone Control for Wind Turbine Inspection DOI Open Access

Chabir Amal,

Aicha Abid,

Ben Hmed Mouna

et al.

WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL, Journal Year: 2025, Volume and Issue: 20, P. 72 - 80

Published: April 7, 2025

The paper discusses using drones for monitoring and diagnosis of issues related to wind turbine performance. drone system helps find out why turbines aren't working as well they should. It can spot problems like broken parts or weather issues. Plus, it keeps an eye on birds around the turbines, checking nests structures. Using this makes maintenance environmental checks much easier cheaper, it's also safer than old ways. To make sure works perfectly, we used MATLAB create a model it, both PID FOPID controllers control drone. Turns out, controller is more accurate does better job keeping stable regular controller.

Language: Английский

Citations

0
An Automated and Integrated Sensing System for Road Monitoring using UAV Images and an Optimized R-CNN DOI Open Access

Vincenzo Barrile,

Francesco Scopelliti,

Emanuela Genovese

et al.

WSEAS TRANSACTIONS ON SIGNAL PROCESSING, Journal Year: 2025, Volume and Issue: 21, P. 31 - 40

Published: April 7, 2025

One of the most relevant, but at same time time-consuming and costly, aspects infrastructure system is monitoring road infrastructures, often subject to deterioration that compromises their use. Current systems consist individual reports or use human resources that, through equipped vehicles, have purpose carrying out a reconnaissance process, which characterized by errors uncertainties. In this context, aim work was experiment implement an experimental innovative Automated Integrated Sensing System (AISS) for infrastructures. This system, starting from Remote images Unmanned Aerial Vehicles (UAVs), uses Mask R-CNN neural network identify cracks. information, together with other included in database, then used Geographical Information (GIS) relative visualization. therefore proposes methodology implementation helps policy makers determining urgent interventions. fact, categorization severity degradation user-friendly visualization, allow us make decisions based on data.

Language: Английский

Citations

0