Abstract
Water quality in rural areas is difficult to monitor due to lack of connectivity from different water laboratories. In other areas, location-based real-time water quality data collection is a tedious job and highly dependent on human intervention. The presented paper introduces a low-cost battery operated smartphone-based embedded system design to measure different water quality parameters in various remote locations. Developed system measures pH, total dissolved salt (TDS) and temperature of the water samples using off the shelf available sensors. Measured pH and TDS dataset have been used to derive other water quality parameters using standard mathematical relationships such as salinity, oxygen reduction potential and conductivity. Front-end readout interface circuit has been designed and interfaced with 8-bit microcontroller along with classical Bluetooth module for measurement, data acquisition, and logging purpose. A dedicated smartphone-based application offers analysis and cloud data storage possibilities. It also provides facility to analyze water quality data with location information on Google map for quick judgment and easy understanding. The developed smartphone-based application provides the facility of auto-calibration feature for rapid and on-site usage. Developed smartphone-based application also opens up the possibility to share the data and warnings using different options such as SMS, WhatsApp and E-mail. Overall device has dimensions of 11.0 × 8.0 × 4.0 (in cm), weighs 350 g and runs with 9-V rechargeable battery. Obtained results have been validated with standard water quality measurement system from Eutech Instruments, and it has been observed that measured and calculated parameters are acceptable according to Indian water quality standards. Various statistical and artificial neural network-based modeling techniques have been used to convert measured water quality parameters to a single water quality index for easy and rapid judgment. The developed water quality measurement system has been used for multiple applications to explore the utility of the system such as instant water quality judgment and real-time water quality analysis of different water sources. One of the other explored applications is the real-time water quality monitoring of small ponds and lakes.
Highlights
Location-based remote water quality monitoring and data collection have been always a great challenge for different water laboratories and public health engineering departments (PHED)
Few efforts have been observed in the direction of converting multiple water quality parameters into a single water quality index using rule-based fuzzy model Roveda et al (2010) and neural network Gorashi and Abdullah (2012)
Presented work has been compared with past literature (Table 2), and it has been found that smartphone-based water quality measurement system could be a low-cost tool for location-based water quality measurement as well as it could be used in each Indian water quality measurement laboratory
Summary
Location-based remote water quality monitoring and data collection have been always a great challenge for different water laboratories and public health engineering departments (PHED). Presented work introduces a handheld smartphone-based device to analyze the water quality along with location information of testing sites in different applications. This device requires low power and uses smartphone for data storage and analysis. Dedicated Android application stores water quality parameters on the smartphone, transfers to the cloud with location information, predicts water quality index in real-time and provides facility to integrate water quality data with Google map for rapid judgment and analysis at district, state and country level. An embedded processing unit has been designed and developed to acquire the data from off the shelf available sensors imported from Toshcon Corporation & Ltd. Measured pH and TDS dataset have been used to predict other water quality parameters such as salinity, conductivity and ORP using standard mathematical models.
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