An enhanced system design of IoT-based smart office
DOI:
https://doi.org/10.4314/jobasr.v4i2.36Keywords:
Internet of Things (IoT), Smart Office Systems, Energy Efficiency, Automated Control, Sensor NetworksAbstract
This study presents an enhanced system design for an Internet of Things (IoT)-based smart office system aimed at improving workplace efficiency, security, and energy management. The proposed system integrates intelligent sensors, automated controls, and real-time data processing to monitor office conditions such as lighting, temperature, device usage, and access control. By using interconnected IoT devices and cloud- and edge-computing architectures, the system enables automatic adjustments, remote monitoring, and timely decision-making. The design also focuses on reducing energy waste, improving employee comfort, and strengthening office security through advanced smart authentication and alert mechanisms. Results obtained from system evaluation show that the enhanced IoT-based smart office design provides faster response times, better resource management, and more reliable automation compared to conventional office systems. This study presents an enhanced system design for an IoT-based smart office, aimed at improving energy efficiency, security, and user comfort through automated monitoring and control of devices. A prototype implementation was developed using IoT sensors, actuators, and a centralized control platform, with experiments conducted to evaluate system performance in a real office environment. Results indicate a 20% reduction in energy consumption, a 15% improvement in response time for automated controls, and enhanced security through real-time access monitoring. The study contributes by proposing an integrated smart office framework that combines environmental monitoring, automated device management, and user-centric control, offering a scalable and cost-effective solution for modern workplaces. These findings demonstrate the potential of IoT integration to optimize operational efficiency and inform future research on intelligent office environments.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.