POTNET: Online Potable Water Quality Monitoring Network for Overhead Water Tanks in Rural Water Supply Schemes in India

Background: Monitoring the quality of potable water is a challenging endeavor due to the significant sources of contaminants, the majority of which are human-induced. Limited access to drinking water owing to acceleration in industrialization, urbanization in consort with growing inhabitants, unprocessed sewage discharge and industrial toxic effluents causes different life-threatening diseases. Manual water quality monitoring techniques vividly aggravate quality deterioration. Considering the significance of the automatic water quality monitoring system, we need an in-situ, realtime, continuous surveillance system to ascertain the quality of potable water. Wireless Sensor Network (WSN) motivated us for a practical water quality monitoring system due to their continuous, real-time, and adaptive infrastructure to provide an early alert in hazardous conditions. Objective: To design and implement an online potable water quality monitoring network for rural water supply schemes in Nagapattinam district, Tamilnadu, India, to sense physiochemical parameters of potable water such as pH, turbidity, conductivity and temperature. Methods: Online POTable water quality monitoring NETwork (POTNET) integrates the reimbursements of WSN and different information and communication technologies for data acquisition, data processing, and data visualization. The core hardware of POTNET contains off-the-shelf sensors (i.e., electrodes), a microcontroller, a data transmission system, a customized buoyage, and a sink node. It senses physiochemical parameters of potable water such as pH, turbidity, conductivity, and temperature in a pre-programmed time interval. Furthermore, it enables cloud storage for gathered information and generates an alert to the preregistered user via mobile phones when there is a deviation of quality measures from threshold values. Results: The system was implemented in three overhead tanks for seven days in order to validate the stability of the buoy and efficiency of energy source, storage, and data transmission. It senses physiochemical parameters of potable water such as pH, turbidity, conductivity, and temperature in its pre-defined interval of 30 minutes. To check the system accuracy, the measured data values from developed sensors were compared with the observed data values using a commercial multiparameter water checker, the Horiba® probe. Measured data were sent through the transceivers to the base station for data logging in a suitable format for ease of data visualization and utilization. Conclusion: Extensive experimental results reveal that our POTNET can be employed for potable water quality surveillance to help consumers or concern authorities to make a sound decision by providing appropriate and real-time data.

Optimal water quality monitoring network during road construction using Bayes and Entropy theories

<p>The spatial variation of road construction runoff, and environmental impacts on both the terrestrial and aquatic environment necessitate the monitoring of receiving water quality. The paper proposed an integrated methodology for spatial optimization of the water quality monitoring network (WQMN) using information-theoretic techniques, including the concepts of the Transinformation entropy (TE) and the value of information (VOI). First, based on the correlation analysis, the most significant water quality parameters were selected. Then, using the Canadian Council of Ministers of the Environment (CCME) method, the water quality index (WQI) was computed in each potential monitoring station. After that, the VOI and TE for all potential stations were calculated. To achieve an optimal network among potential stations, the NSGA-II multi-objective optimization model was developed considering three objective functions, including i) minimizing the number of stations, ii) maximizing the VOI in the selected network, and iii) minimizing TE by the selected nodes. The optimization model resulted in a set of optimal solutions for WQMNs, called Pareto-front. Finally, two multi-criteria decision-making models including TOPSIS and PROMETHEE were utilized for choosing the best solution on the Pareto-front space considering various weighing scenarios assigned to objectives. The applicability of the presented methodology was assessed in a WQMN of a road construction site (33 km) in E18 highway, south of Norway. The selected solutions by TOPSIS and PROMETHEE models present the WQMN with maximum VOI and minimum TE among 33, and 28 potential stations, respectively.</p>