A Low-Cost Unmanned Surface Vehicle for Pervasive Water Quality Monitoring

This article discusses the architecture of a low-cost unmanned surface vehicle (USV) to be employed for the collection of crucial parameters about water quality in rivers, lakes, or sea. The vehicle, called water environmental mobile observer (WeMo), has been realized exploiting off-the-shelf components and is provided with a modular array of sensors to measure chemical and physical parameters as well as to perform bathymetry. The low-cost requirement is crucial since the vehicle is expected to be replicated in large quantities and then used for pervasive monitoring operations by providing it to local communities, administrations, or even private stakeholders, in order to set up a sort of 'social sensor network.' In this sense, data analytics tools have also been introduced in order to automatically drive the vehicle along desired and suitable trajectories and to process the collected data. These data can be used to estimate the parameters of a mathematical model describing the ecological status of the monitored system. In particular, we apply an estimation procedure to a simple mathematical model of oxygen concentration in the water with explicit dependence on biophysical inputs. The estimation provides very satisfying performances, indeed the relative square error is less than 4 cdot 10^{-2}. Moreover, once the vehicle is moving along a given trajectory, the status in the spatial domain can be reconstructed also in nonmonitored locations. The whole article aims then at developing a complete monitoring ecosystem covering all the tasks of data collection, storage, and analysis.