# Floating Photovoltaic Plant Monitoring: A Review of Requirements and Feasible Technologies
## 6 A Case Study for an FPV Autonomous Monitoring System  
The environmental impact of FPV involves complex interactions between physical, chemical, and ecological components of the water body and ecosystems [71]. The monitoring system can be based on configurations made of (1) fixed sensors or (2) mobile sensors, or a hybrid configuration that combines the two. Configuration 1 can be achieved with multiparametric probes (see Section 4) moored to floating systems (FPV or buoy) with fixed x, y, and z. Most of the literature on WQM in FPVis based on this strategy [61; 69; 87]. Fouling (the accumulation of microorganisms, plants, algae, or small animals on wetted surfaces) [30] has always been a problem when devices are submerged for extended periods. Modern multiparameter probes (configuration 1) have addressed this problem with different antifouling devices depending on the technology employed by the sensor. Ultraviolet light [140] prevents biofouling formation on the water conductivity cell. Optical sensors, such as dissolved oxygen and turbidimeters, can instead be kept efficient with electromechanical systems such as wipers that keep the glass clean. These antifouling devices significantly increase the energy requirements of the multiprobe, but can allow its use for longer periods of operation, even in the harshest ambient conditions [141; 142; 143; 144]. This is the case of static positioning, with the availability of electrical energy as in the proposed monitoring system. Furthermore, they reduce sensing drift phenomena and thus contribute to maintaining accuracy requirements. Camera traps in fixed positions could be useful for registering the movements of animals, like in [145], which can also help to reduce the O&M cost burden by controlling interactions with living beings. [PERSON] and co-authors [144] calibrate the sensors before and after deployment and, assuming linear drift, correct the final data time series. Generally, small corrections within the accuracy specified by the manufacturer are required. More effective algorithms can be implemented for non-linear drift compensation in the case of e-tongue usage. The remote management of these probes in terms of anti-vandalism, anti-theft (possibly sharing those of the FPV if present), and real-time control of the quality of the acquired data would be an added value. Machine learning algorithms could alert remote management in case of suspect data patterns (malfunctions, unexpected events, need for sensor calibration, etc.) and can be trained to recognize specific events and conditions with environmental significance. A hybrid sensor configuration can be achieved by combining configuration 1 (fixed position of the sensor in x and y) with a controlled winch to guarantee mobility of the sensors along z. A similar approach was followed by Vlaswinkel in 2023 [68] which manually controlled the winch. A further improvement to this hybrid solution can be obtained by managing the winch in a remote and automated manner. Configuration 1 and its variation would have a good degree of autonomy and a relatively low rate of human intervention. Configuration 2 can be achieved using single carriers with the appropriate sensors integrated onboard (multiprobe, cameras, etc. ); ROV and AUV can guarantee the movement of sensors in x, y, and z. Sensors to be used in motion must be calibrated following a different procedure [146]. Vehicles could be equipped with water and/or sediment sampling devices [147] to obtain biotic parameters of interest from laboratory analyses (e.g., microscopic plankton). [PERSON] and coauthors [69] field-tested an ROV with sensors and cameras in various pilot applications in the Netherlands. The aquatic ecology was analyzed assessing the presence of fish, aquatic plants, or other aquatic organisms, identifying fish communities, and characterizing local habitats (e.g., stock assessment). [PERSON] and coauthors [148], through deep learning on images from a 360-degree panoramic camera, identified fish in real time.