FoEMS: Fog computing facilitated low-cost open-source building energy management system for the smart home automation applications

Published: 23 September 2022| Version 2 | DOI: 10.17632/sbsgh2tmrk.2
Kaiser Habib,
, Aini Hussain


FoEMS: The lighting, heating, ventilation, and air conditioning systems are the power-hungry consumer in building infrastructures that require efficient management to achieve optimum energy consumption. This study developed an open-source cost-effective three-tier fog computing-based building energy management system (FoEMS) to limit the home appliance's power consumption. FoEMS incorporates a gateway at the network edge to locally control connected loads autonomously based on the occupant and ambient statuses from the occupancy and sensor nodes. Also, selectively transfers event statuses to the cloud and Telegram Messenger for remote supervision of the building's indoor ambiance and take faster mitigation action against possible event occurrences. Such scheduled communication reduces network traffic and provides a wireless solution for content access at low latency. FoEMS performance has been validated by integrating with two existing clouds and characterized through several experiments. The analyses showed energy consumption reduced by 33%, with an average of 90% packet receive efficiency at 1.84% CPU usage, 2.37W power consumption, and 0.0885s data transfer response time with the open-source/proprietary web services. This integrated approach offers real-time remote supervision, aggregated data management of the building ambiance through different web technologies, and controls appliances autonomously based on occupancy to reduce unnecessary energy consumption with maximum occupant comfort. @ Bill of Materials: Bill of Materials: Cost estimation and material source of the hardware required to develop FoEMS nodes. Requirement Analysis: Hardware requirements and scopes to develop the FoEMS nodes. @ Design Files summary: Actuator Node Schematic.jpeg: Circuit diagram to assemble the actuator node. Arduino firmware, required library, and payload to develop the actuator node. Gateway UART Interfacing.jpeg: Connection scheme of HC-12 RF-transceiver module with the Intel NUC deployed gateway node. Gateway controller application for ARM-32-bit RPi, Windows 32-bit and 64-bit platform. MessagePacketStructure.jpeg: Message packet frame structure for data exchange via RF-433.4 MHz channel. Occupancy Node Schematic.jpeg: Circuit diagram to assemble the occupancy node. Arduino firmware, required library, and payload to develop the occupancy node. Sensor Node Schematic.jpeg: Circuit diagram to assemble the wireless sensor node. Arduino firmware, required library, and payload to develop the sensor node. Web Request Format: Prescribed web request URI structure of the ThingSpeak and ThingsSentral Platforms.



Universiti Kebangsaan Malaysia


Intelligent Building Energy Management System, Fog Computing