IoT-Based Intelligent Home Control System Using Raspberry Pi and Home Assistant Platform: Design and Implementation
Keywords:
IoT; Raspberry Pi; Home Assistant; MQTT; smart home; home automation; PIR sensor; Zigbee; edge computing.Abstract
The rapid proliferation of low-cost single-board computers and wireless sensor technologies has made intelligent home automation systems accessible to individual households, small enterprises, and research laboratories alike. This paper presents the complete design, hardware integration, software configuration, and performance evaluation of an IoT-based intelligent home control system built on a Raspberry Pi 4B single-board computer running the Home Assistant (HA) open-source platform. The system integrates a heterogeneous set of sensors and actuators—including DHT22 temperature/humidity sensors, HC-SR501 passive infrared (PIR) motion detectors, BH1750 ambient light sensors, MQ-135 air quality modules, WS2812B addressable LED strips, a four-channel relay board for appliance switching, an MFRC522 RFID access control reader, and a Zigbee coordinator for mesh-networked third-party smart devices—into a unified, locally processed automation platform. All inter-device communication is handled via the MQTT lightweight messaging protocol, enabling sub-15 ms latency on the local area network. Home Assistant's YAML-based automation engine orchestrates 47 distinct automation rules covering climate control, lighting scenes, occupancy-driven switching, air quality alerts, access logging, and energy management. A web-based Lovelace dashboard and a companion mobile application provide remote monitoring and manual override capability over both LAN and WAN via a secure Nabu Casa cloud tunnel. A 30-day continuous deployment evaluation demonstrated a system uptime of 718.4 hours (99.8%), a mean MQTT message latency of 12.4 ms on LAN and 187 ms over WAN, sensor measurement accuracies within manufacturer-specified tolerances, and a peak CPU utilization of 58.3% under concurrent automation load—well within the Raspberry Pi 4B's sustained operating envelope. The paper provides a fully documented, reproducible implementation blueprint suitable for academic research, student projects, and real-world deployment.
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