Malaria remains a public health problem in Indonesia, particularly in endemic coastal regions where aquatic habitats serve as breeding sites for Anopheles larvae. This study develops a multi-point Internet of Things (IoT)-based aquatic environmental monitoring system to detect conditions that support larval development through real-time measurement of water salinity and temperature. The system employs a WQ7706D digital salinity sensor, an ESP32 microcontroller, and a low-power NRF24L01 wireless communication module. Laboratory testing indicates that the sensor achieves stable readings after a 20-second stabilization period, with salinity variation of ±0,05 ppt under steady conditions. Field implementation at two coastal water sites in Hanura Village recorded salinity ranges of 1,35–2,3 ppt and temperature ranges of 28,8–30,5°C, which potentially support larval development. The wireless communication system successfully transmitted data up to 150 m with minimal packet loss. Power consumption analysis shows a daily energy requirement of 1,794 Ah, enabling autonomous operation for 10 ± 1 days using a 12 V 20 Ah battery without recharging. The main contribution of this research is the design of an IoT-based aquatic monitoring system that integrates energy optimization, stable wireless communication, and quantitative identification of malaria larval habitat risk.