Design of an Economical IoT Based Intelligent Lake Water Quality Measuring System with of the Shelf Industrial Grade Sensors
Anupreet Dube1, Jayesh Trivedi2, Yogendra Singh Solanki3, Aaditya Maheshwari4, Abhishek Sharma5
1Anupreet Dube, B.Tech, Department of Electronics and Communications, Techno India NJR Institute of Technology, Udaipur (Rajasthan), India.
2Jayesh Trivedi, B.Tech, Department of Electronics and Communications, Techno India NJR Institute of Technology, Udaipur (Rajasthan), India.
3Yogendra Singh Solanki, Assistant Professor, Department of Electronics and Communications, Techno India NJR Institute of Technology, Udaipur (Rajasthan), India.
4Aaditya Maheshwari, Techno India NJR Institute of Technology, Udaipur (Rajasthan), India.
5Abhishek Sharma, Assistant Professor, Department of Mechanical Engineering, Techno India NJR Institute of Technology, Udaipur (Rajasthan), India.
Manuscript received on 15 March 2020 | Revised Manuscript received on 22 March 2020 | Manuscript Published on 30 March 2020 | PP: 30-34 | Volume-9 Issue-3S March 2020 | Retrieval Number: C10080393S20/20©BEIESP | DOI: 10.35940/ijeat.C1008.0393S20
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The paper presents an IOT based intelligent lake water quality measuring system that comprises of low cost industrial grade sensors and off the shelf components along with signal conditioning circuits that measure the important water quality parameters such as DO, pH, TDS, and Temperature. The data is pushed onto a dedicated cloud platform in real-time and can be accessed through an online dashboard, as well as from an android application on smart phones. The system is also equipped with very important feature: the detection of abnormal dynamic variation in measured parameters and anomaly alert algorithm. The system firmware has intelligence that modulates the data transmission rate to cloud for extending the battery life, based on ambient lighting conditions and optimizes the rate in case of anomaly in water quality parameters to optimize the use of battery power. The system has two variants, the first variant has a fixed structure that can be affixed to a structure at any selected location preferably the shore, whereas the second one has a floating structure that can remain afloat on the water surface. System architecture is described and the measured water quality parameters are presented of tests conducted at multiple lakes in different weather conditions. The results have been verified with standard laboratory test results and presented here.
Keywords: IoT, Remote Sensing, Ambient Lighting Detection, Dynamic Transmission Rate, Anomaly Alert.
Scope of the Article: IoT