WAVE: Water Analysis and Visualization Engine for Ajman (UAE)

202211472 Fatemeh Ahmad Shenasi 

202220174 Hajar Mamoun Omar Abdel-Rahim 

202211481 Khadija Abdulla Mohammed Aljanaahi 

202211620 Mahrah Khalifa Alkawwar Alnuaimi 

202111169 Saman Nadeem 

This project presents the design, development, and evaluation of an IoT-based water quality monitoring system intended for deployment across Ajman and the UAE to enable real-time, city-wide monitoring. The system integrates smart sensing hardware, a web-based dashboard, and a cross-platform mobile application to continuously monitor, record, and visualize water quality data.

The hardware layer is built on an Arduino UNO R4 WiFi microcontroller connected to sensors measuring pH, total dissolved solids (TDS), turbidity, and temperature. Sensor data is transmitted via WiFi to a Firebase Realtime Database for cloud storage and synchronization. The platform features real-time dashboards, historical data visualization, an interactive heatmap for spatial analysis, and configurable alert thresholds. A Flutter-based mobile application allows users to remotely access data, receive notifications, and track alerts, with role-based access control for administrators, operators, and end users.

System testing demonstrated reliable data transmission with acceptable latency. Multi-channel alerts are triggered when readings exceed predefined thresholds, with notifications delivered through dashboard and mobile devices. The architecture is scalable and largely validated, with partial use of simulated sensor data pending full deployment. The project supports data-driven water quality management and aligns with UAE digital transformation initiatives and Ajman Vision 2030.