IoT Based WSN Ground Water Monitoring System with Cloud-Based Monitoring as a Service (Maas) and Prediction using Machine Learning
B. Lalithadevi1, Akash Yadav2, Aditya Pandey3, Mahesh Adhikari4

1B Lalithadevi*, AP, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
2Akash Yadav, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
3Aditya Pandey, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.
4Mahesh Adhikari, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India.

Manuscript received on October 19, 2019. | Revised Manuscript received on 27 October, 2019. | Manuscript published on November 10, 2019. | PP: 816-821 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4316119119/2019©BEIESP | DOI: 10.35940/ijitee.A4316.119119
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Abstract: The main source of water in the Indian Subcontinent is Groundwater. It is also the most rapidly depleting resource due to various reasons such as rampant unchecked irrigation and exploitation of groundwater by industries and other organizations. The current system is limited by short communication range, high power consumption and the system monitors only the water level and the report is available only to the consumer i.e. it is a single-user system. Due to the unavailability of a centralized system to monitor and prevent overuse of water resources, sudden water crises have become a major issue in India. This project aims at implementing an IoT (Internet of things) based water monitoring system that monitors the water level and the quality of groundwater and updates real-time data to the database. This system is designed to monitor the groundwater level of an entire village or a town. It updates the people and the concerned government authorities in case of any decrease in water level and water quality below the threshold value, and also monitors the water consumption during a period and predicts exhaustion time. This system predicts the availability of water in the future based on current demand and usage and the recharge rate using machine learning algorithms. The data collected and the analysis of the data is made available in a Public Cloud. The modules are based on Raspberry Pi Zero, sensor nodes and LoRa (Long Range) Module or Wi-Fi module according to the network requirement for connectivity
Keywords:  Internet of Things, Water Resource Monitoring, Agriculture, Smart village, Smart city, Wireless Sensors net- Work, Environmental Monitoring, Cloud.
Scope of the Article: Internet of Things