A development of an IoT-based temperature-TDS monitoring system for shrimp cultivation pond - Akhyar, Halil; Budianto, Arif; Rahayu, Susi; Alaydrus, Alfina Taurida; Anggriani, Ni Ketut; Wardi, Palaivia Harman; Pranahita, Dewa Dwi; Andini, Mira (ORBITA: Jurnal Pendidikan dan Ilmu Fisika, 2025)
High-quality water resources are important parameters for the sustainability of human civilization, the health of ecosystems, and the advancement of vital sectors. High-quality water is also needed for shrimp cultivation ponds. However, water-quality monitoring in the estuary is limited. In line with this, this study focuses on the design and implementation of an IoT-based TDS and temperature measurement system for estuarine water, aiming to develop an efficient, accurate, and automated prototype to support the fisheries sector in West Lombok regency. This study used a microcontroller, temperature and TDS (total dissolved solids) sensors, a wireless router, and a display. These elements were developed as a water-quality-level monitoring system based on TDS and temperature. The system was calibrated using a standard comparator before being examined under real conditions. The calibration procedure was conducted inside a controlled chamber at a water temperature of 25°C for 60 minutes, with a steady flow rate. All procedures were repeated three times and tested using a Student’s t-test. The IoT platform was tested using RSSI values with a 2s update interval. The calibration data were interpreted as a linear function between the standard and the developed system. The resulting design shows that the developed system can be installed at a shrimp cultivation pond with good performance. The designed system has a linearity of more than 90%. The system has a reliable accuracy level over 30 consecutive measurement days, resulting in the percentages of 85% to 93% (average = 91%). It can be concluded that IoT data communication via a wireless internet router performs well, with RSSI> -50 dBm for both sending and receiving. The IoT platform using ThingSpeak shows good performance (good stability), with a 2-second interval between data updates.