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Internet of Things (IoT) enabled smart nitrate sensor for real- time water quality monitoring

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posted on 28.03.2022, 12:27 by Md Eshrat E. Alahi
Nitrate-N is a naturally occurring ionic compound that is part of nature's nitrogen cycle. Nitrates-N are readily lost to ground and surface water as a result of intensive agriculture, industrial wastes, disposal of human and animal sewage. The impact of elevated nitrate-N concentrations on water quality has been identified as a critical issue of a healthy environment for the future. Presently, water quality managers follow the traditional measurement systems that involve physically collecting the sampling water from remote sites and testing it in the laboratory. These methods are expensive, require trained people to analyse the data and produce much chemical waste. Therefore, low-cost Ion Imprinted Polymer (IIP) coated impedimetric nitrate-N sensor was developed, and the detection range of nitrate-N was 1-10 (mg/L). The selective IIP material was sensitive to nitrate-N ions in an aqueous medium, and the results are validated through standard UV-spectrometric methods. MEMS (microelectro-mechanical-system) based interdigital sensor and sensing system was also developed to measure nitrate-N, and the range was 0.01 - 0.5 (mg/L). The graphene-based low-cost sensor was also fabricated, and the sensor was characterized to measure nitrate-N in the range of 1-70 (mg/L). Temperature compensation was added for both the sensors (MEMS and Graphene) and WiFi connectivity was provisioned in the system to transfer the measured data in real time. An improved LoRa based sensing system (solar panel and rechargeable battery powered) was developed and trialled in the field successfully which can measure the nitrate-N concentration in real-time and transfer the data to IoT cloud server to overcome the limitations of lab based sensing system.


Table of Contents

1. Introduction -- 2. Literature review -- 3. Interdigitated sensing and electrochemical impedance spectroscopy -- 4. Temperature sompensation for low concentration nitrate measurement -- 5. Graphene-PDMS sensor for nitrate measurement -- 6. Selectivity of nitrate sensor -- 7. IoT enabled smart sensing system -- 8. Conclusions and future work -- Bibliography.


Thesis by publication. Bibliography: pages 125-146

Awarding Institution

Macquarie University

Degree Type

Thesis PhD


PhD, Macquarie University, Faculty of Science and Engineering, School of Engineering

Department, Centre or School

School of Engineering

Year of Award


Principal Supervisor

Subhas Chandra Mukhopadhyay

Additional Supervisor 1

Lucy Burkitt


Copyright Md Eshrat E Alahi 2018. Copyright disclaimer: http://mq.edu.au/library/copyright




1 online resource (xxviii, 146 pages) colour illustrations

Former Identifiers

mq:71508 http://hdl.handle.net/1959.14/1275094