Design and Implementation of an IoT-Based Indoor Monitoring and Warning System

Abstract

This study designs and implements an Internet of Things (IoT) indoor monitoring, control, and warning system for smart-warehouse scenarios. The system centers on an ESP32 gateway that aggregates multiple-sensor data via Inter-Integrated Circuit (I²C), Serial Peripheral Interface (SPI), and a low-power nRF24L01 mesh network, enabling distributed nodes for environment sensing and equipment control. Security and personalization are enhanced via on-device face detection/recognition for access control and role-based permissions. A cloud backend provides real-time data synchronization, event logging, and remote actuation, whereas a responsive web interface supports cross-platform supervision and configuration. A modular hardware–software architecture is described that emphasizes interoperability and cybersecurity through authenticated messaging, secure key provisioning, and adherence to embedded and web standards. A prototype was developed and evaluated in a warehouse-like testbed in Vietnam, assessing end-to-end latency, alert delivery reliability, recognition accuracy, node power budget, and Radio Frequency (RF) link robustness under typical indoor obstructions. Results demonstrate reliable data acquisition, responsive closed-loop control, and stable multi-device operation with seamless cloud integration, indicating suitability for day-to-day warehouse operations such as secure entry, device management, and environmental compliance.