Design and Implementation of a Low Cost IoT-Based System for Enhanced Visual Feedback, Alert Systems, and Server Environment Tracking

Abstract

In modern data centers, maintaining stable environmental conditions is critical to ensuring system reliability and energy efficiency. This paper presents EcoARIoT, a real-time, edge-enabled monitoring system that combines IoT sensor networks with mobile based Augmented Reality (AR) to enhance diagnostics and technician decision making. Each ESP32-based sensor node captures temperature, humidity, gas, voltage, and current readings, transmitting data securely to Firebase via HTTPS. A cross-platform Flutter application displays the data through interactive dashboards and spatial AR overlays. During a 72-hour live deployment at the AL-Nahrain university/College of Information Engineering’s microdata center, EcoARIoT achieved a mean response latency below 1.5 seconds and over 95% data consistency. The system generated 112 alert events, with a detection precision of 97.3%, and reduced physical technician interventions by 41.2%, demonstrating tangible operational impact.Compared to existing solutions, EcoARIoT emphasizes energy efficiency via dynamic ESP32 sleep cycles and uses threshold- and trend-based sensing logic for proactive alerts. These results confirm the system’s viability as a scalable and sustainable prototype for intelligent data center monitoring.