REAL-TIME IOT-BASED MONITORING AND ENVIRONMENTAL RISK ASSESSMENT OF NAEGLERIA FOWLERI IN SWIMMING POOL WATER

Abstract

Naegleria fowleri, commonly known as the brain-eating amoeba, poses a serious and often fatal threat to human health in warm, poorly sanitized swimming pools. Direct pathogen detection is complicated, time-consuming, and expensive, making continuous environmental monitoring potentially valuable for identifying changing environmental conditions before they require operational intervention. A smart Internet of Things (IoT) based pool water quality monitoring system was developed using a physical sensor node equipped with four sensors: pH, temperature, water level, and chlorine. Data collected by an Arduino Uno microcontroller was transmitted via an ESP8266 Wi-Fi module to a centralized cloud platform. A threshold-based risk evaluation engine processed combined readings in real time to assess environmental risk conditions. The system was installed and tested under pool conditions for 10 to 15 days. The suggested model was used to classify the conditions in terms of risk based on the combination of temperature and free chlorine levels. While the system is configured to detect high-risk conditions when chlorine drops below 0.5 ppm, this threshold was not reached during the trial period. The results demonstrate the potential value of evaluating multiple parameters simultaneously for identifying environmental warning conditions. The proposed Aqua-Intel system is a scalable, cost-effective IoT solution that shifts the paradigm from reactive pathogen testing to proactive environmental risk assessment, supporting proactive swimming-pool water monitoring and risk assessment.