Development and application of a low cost IoT kit for real-time water quality monitoring | |
| Author | Laraib, Iqra |
| Call Number | AIT Thesis no.WM-26-09 |
| Subject(s) | Water quality--Data processing Water quality--Mathematical models Internet of Things |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Water Engineering and Management |
| Publisher | Asian Institute of Technology |
| Abstract | Water quality monitoring is essential for protecting public health, supporting aquatic ecosystems, and improving water resource management. However, conventional monitoring methods often depend on manual sampling and laboratory analysis, which can be costly, time consuming, and unsuitable for continuous field observation. This study developed and applied a low-cost Internet of Things (IoT)-based water quality monitoring kit for near-real-time assessment of surface water quality.The developed system measured five key water quality parameters such as water temperature, pH, total dissolved solids (TDS), turbidity, and dissolved oxygen (DO). These parameters were selected because they provide useful information about the physical and chemical condition of water and can be monitored using low-cost sensors. The sensors were integrated with an Arduino UNO R4 WiFi microcontroller, allowing data transmission through built-in Wi-Fi to the Arduino IoT Cloud. The system also supported direct laptop connection, providing dual display options for both cloud-based and local monitoring.Sensor calibration was carried out using standard solutions and reference instruments to improve measurement accuracy. The calibrated sensor readings were then used to calculate a modified sensor-based Water Quality Index (WQI), allowing the system to convert raw parameter values into a simple water quality score and class. The kit was tested at two pond sites within the Asian Institute of Technology campus: AIT CC pond and Somtan pond. Field measurements were compared with laboratory/reference readings, and the results showed low percentage errors, with overall MAPE values below 3%. The WQI comparison also showed close agreement between IoT-based and laboratory-based results. At AIT CC pond, the IoT based WQI was 46.71, while the laboratory-based WQI was 45.16; at Somtan pond, the IoT based WQI was 34.94, while the laboratory-based WQI was 35.92. Both IoT-based and laboratory-based WQI results classified the two sites as Poor, indicating that the developed kit produced the same final water quality class as the laboratory-based calculation.Overall, the study demonstrates that a portable, low-cost, near-real-time IoT water quality monitoring kit can be useful for rapid field screening, educational use, research applications, and preliminary water quality decision support in resource-limited settings. |
| Year | 2026 |
| Type | Thesis |
| School | Faculty of Civil and Environmental Engineering (2026) |
| Department | Other Field of Studies (No Department) |
| Academic Program/FoS | Water Engineering and Management (WEM) |
| Chairperson(s) | Sundaram, Mohana |
| Examination Committee(s) | Shrestha, Sangam;Natthachet Tangdamrongsub;Sarawut Ninsawat |
| Scholarship Donor(s) | PMU-KPCIP_AIT Scholarship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2026 |
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