In this paper the design, development, and validation of a set of low-power low-cost sensor systems intended for environmental monitoring and visitor tracking in cultural heritage sites are shown. These systems have been deployed in five pilot cases in four different countries in Europe inside the European ARGUS project. Two different approaches have been defined in the design: the static systems installed in fixed positions and the dynamic systems installed in a moving robot, i.e., a quadruped robot or a drone. The Baltanás pilot site has served as the primary testing platform, enabling accelerated prototyping and iterative improvement before deployment across additional pilot locations. This paper presents the design criteria, system architectures, and performance evaluation of these sensor networks, including thermal–humidity probes, volumetric water content sensors, wind measurement systems, pollution monitors, and two generations of visitor counting devices.

In this paper the design, development, and validation of a set of low power, low-cost sensor systems intended for environmental monitoring and visitor tracking in cultural heritage sites is shown. These systems have been deployed in 5 pilot cases in 4 different countries in Europe inside the European ARGUS project. Two different approaches have been defined in the design: the static systems installed in fixed positions and the dynamic systems installed in a moving robot i.e., a quadruped robot or a drone. The Baltanás pilot site has served as the primary testing platform, enabling accelerated prototyping and iterative improvement before deployment across additional pilot locations. This paper presents the design criteria, system architectures, and performance evaluation of these sensor networks, including thermal–humidity probes, volumetric water content sensors, wind measurement systems, pollution monitors, and two generations of visitor counting devices.

The aeronautic industry faces a critical challenge: achieving safe, reliable, and affordable air transport with near-zero emissions. The introduction of carbon fiber–reinforced polymers (CFRPs) has significantly reduced aircraft weight and, consequently, fuel consumption and CO₂ emissions. However, the long manufacturing cycles required for CFRP structures still limit their application in high-rate aircraft production. Addressing this limitation requires advanced manufacturing technologies that enable faster and more energy-efficient composite processing. This study presents the design and development of a monitoring system for studying and optimizing the CFRP curing process. The system integrates temperature and ultrasonic transmission measurements to provide real-time insight into the material’s internal state. Custom ultrasonic transducers, capable of operating up to 180 °C, were developed to track variations in ultrasonic propagation during curing. Experimental tests on CFRP specimens revealed that internal temperature distribution and ultrasonic parameters depend on the curing method and laminate configuration. Different ultrasonic techniques were evaluated to identify the most effective approach for correlating ultrasonic responses with the degree of cure. The proposed monitoring system enables adaptive control of the curing process, reducing energy consumption and cycle time while ensuring part quality in advanced composite manufacturing.

Unmanned aerial vehicles (UAVs) equipped with lightweight gas sensors offer a promising approach for greenhouse-gas emission monitoring. However, airflow generated by multirotor propellers can disturb the atmosphere and influence measured gas concentrations. This study investigates rotor-induced downwash effects on vehicle exhaust plume measurements using experimental and numerical approaches. Experiments were conducted with a stationary diesel vehicle at idle, while a propeller system reproduced UAV downwash at rotor-sensor separation distances of 0.5–5.5 m above a fixed CO₂ sensor. A low-cost Feather-based sensing platform was evaluated against a commercial IoTSens monitoring station. CFD simulations were performed in OpenFOAM^® using a compressible multi-species solver, Large Eddy Simulation (LES), and a Multiple Reference Frame (MRF) approach. Experiments showed CO₂ reductions of up to 52.7%, while CFD predicted reductions of 50.4–88.5%. Both approaches showed decreasing rotor-wake influence with increasing separation distance, with strongest effects below approximately 2–3 m. Experimentally, downwash effects became weak between 3.5 and 5.5 m, consistent with reduced plume–wake interaction predicted by CFD. These findings highlight the importance of accounting for rotor-induced downwash when designing UAV-based gas monitoring missions.