Smartphone-based System for water quality analysis

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.

Institutional specifics of IT-platforms in the management of urban water resources

“…− Various methods, models and algorithms of machine learning based on AI can be used in the IMS of WR, in particular, in predicting water quality and identifying pollution sources [7]; analysis of the efficiency of water use [8]; forecasting various desalination technologies [9]; aquifer management [10], etc. Advances in AI and machine learning methods can complement satellite and ground-based observations in WR monitoring, thereby providing decision support in the IMS of WR.…”

Estimation of photocatalytic degradation rate using smartphone based analysis

“…Smartphone technology has not yet reached its evolutionary peak. Smartphones provide many opportunities to improve medical diagnostics, chemical analysis and environmental control [1]. For that reason, smartphones attract increasing attention of researchers.…”

Caracterização e Mitigação da Influência da Temperatura na Fonte de Luz de Biossensores de Ressonância de Plasmons de Superfı́cie Baseados em Smartphones

“…Dentre as diversas aplicações existentes com smartphones pode-se citar: biossensores baseados em Ressonância de Plasmon de Superfície (RPS) (Souza Filho et al, 2014;Preechaburana et al, 2012) , detecção do pesticida glifosato utilizando biossensor RPS (d. Silva Freire et al, 2019),análise de interações cinéticas entre proteínas , um sensor de temperatura (Lu et al, 2019), a detecção de anticorpos da hepatite C utilizando potenciostato eletroquímico (Aronoff-Spencer et al, 2016), análise de qualidade daágua (Srivastava et al, 2018), detecção deácido lático no suor ou saliva (Roda et al, 2014), facilitação de imunoensaios através do biossensor GMR (Choi et al, 2016).…”