Journal of Agricultural Engineering
  • Year: 2026
  • Volume: 63
  • Issue: 1

Development and Field Evaluation of an IoT-based Smart Groundwater Monitoring System

  • Author:
  • Baldeep S. Tiwana1, Samanpreet Kaur Baweja2,*, Amina Raheja2, Susanta Das1, Derminder Singh3
  • Total Page Count: 9
  • Page Number: 110 to 118

1Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, Florida, USA

2Department of Soil and Water Engineering, Punjab Agricultural University, Ludhiana, Punjab, India

3Department of Electrical Engineering and Information Technology, Punjab Agricultural University, Ludhiana, Punjab, India

*Corresponding Author’s E-mail Address: samanpreet@pau.edu

Online Published on 24 April, 2026.

Abstract

It is crucial to accurately measure spatio-temporal changes in groundwater levels to address the issue of fast-depleting water table at a rate of 54 cm year-1 in Punjab state of India. The advent of Internet of Things (IoT) and sensor-based technology offers a feasible solution for real-time monitoring of groundwater levels. In this study, an IoT-based Smart Groundwater Monitoring System (SGWMS) is developed to enable real-time groundwater monitoring. The SGWMS comprises of two units, the data acquisition unit (DAU) and the data transfer unit (DTU), which work together to detect and measure the groundwater depth from ground surface. Unlike a conventional water-level indicator (WLI) that requires field personnel, SGWMS performs time-scheduled measurements and uploads time-stamped groundwater depth to the ThingSpeak cloud platform using Global System for Mobile (GSM) communications/General Packet Radio Service (GPRS) communication. The system is installed at an observation well and the sensing probe is lowered only during each measurement cycle to detect water contact and estimate depth, and then retracted to a fixed position, enabling repeated measurements with improved temporal resolution compared with periodic manual monitoring. Field evaluation of the developed system was performed by comparing observations recorded by SGWMS at three wells in Ludhiana with observations recorded by a water-level indicator over a depth ranging from 33 to 36 m. The system demonstrated a close agreement with the indicator-recorded groundwater levels (root mean square error ~0.024-0.069 m) with no statistically significant difference between two observations (paired t-test, p < 0.05) after introducing a correction factor to avoid systematic overestimation caused by mechanical stopping lag. The developed prototype costs approximately Rs. 12,100, which is lower than the available water-level indicator (Rs. 25,000), while additionally providing automated logging. With the potential to replicate this prototype, it offers an innovative solution to tackle the pressing issue of declining groundwater resources in Punjab.

Keywords

Arduino Uno, Data acquisition unit, Internet of Things (IoT), ThingSpeak