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Water studies in the scope of agriculture have adopted Internet of Things (IoT) to become a new big data collection methodology. This research aimed to deliver a method in water quality categorization. The research methodology for this study used a combination of water quality parameter measurement with two integrated IoT water sensors (turbidity and TDS sensor) and manual categorization. Based on the water categorization standard, the measured turbidity and TDS were matched to one water category. In the sensor precision test, the integrated IoT water sensors showed 94.40% for the turbidity sensor and 97.95% for the TDS sensor. Compared to other water samples, drinking water was successfully distinguished with valid categorization. Other water samples namely groundwater, tea, and coffee showed invalid remarks.

Water quality, data categorization, Internet of Things, water sensors