Water pollution monitoring is crucial for environmental protection, playing a key role in safeguarding ecosystems, protecting public health and promoting sustainable development. However, traditional methods face challenges related to accessibility, real-time analysis and spatial coverage. In this study, we developed a sensor-integrated advanced deployment system for mapping water pollutant parameters. For this, a new voltametric nitrate monitoring sensor is developed using a screen-printing method. Here, for the sensor, the active electrode is composed of a Cu₂O-graphene composite paste, a printed Ag|AgCl reference electrode, and a carbon-based printed counter electrode, all integrated onto a single polyester flexible substrate. The developed sensor exhibits a sensitivity of 3.41 µA/µM within the range of 0 to 0.5 µM of NaNO3. The repeatability, selectivity analysis and performance of various bending angles (0-40 degrees) reveal its implementation in water pollution monitoring. The performances also reveal the possibility of large-scale manufacturing of printed sensors in environmental pollution monitoring. To improve sensor deployment strategies and optimize data acquisition for real-time water quality monitoring, the sensor was incorporated into a remotely operated vehicle (ROV) and tested at different depths and locations in a water container. The ROV, with its advanced navigation and adaptability, can offer an efficient solution for detecting chemical pollutants, mapping hydrothermal plumes, and autonomously adjusting missions based on in situ measurements. The developed system demonstrates the potential of low-energy electrochemical sensors for environmental monitoring applications. This study contributes to advancing ROV-based sensor networks for tracking pollution sources and optimizing water quality assessment in dynamic aquatic environments.
Citation
Markapudi, P. R., Beg, M., Kadara, R. O., Paul, F., Kerrouche, A., See, C. H., & Manjakkal, L. (online). Nitrate Pollution Mapping for Reservoirs Using Flexible Sensors Integrated with Underwater Robot. IEEE Internet of Things Journal, https://doi.org/10.1109/JIOT.2025.3588067
