Data Compression Algorithms for Improving Real-Time Monitoring and Automation in IoT-Enabled Smart Homes

Ali Oveysikian

doi:10.63053/ijset.55

Authors

Ali Oveysikian PhD student, Department of computer science and engineering, Tarbiat Modares university, Tehran, Iran

DOI:

https://doi.org/10.63053/ijset.55

Keywords:

Data Compression, Internet of Things, Smart home, Data transmission, Energy Consumption

Abstract

The rapid proliferation of Internet of Things (IoT)-enabled devices has revolutionized modern smart homes, offering advanced automation, real-time monitoring, and enhanced user convenience. However, this growth has brought forth challenges, particularly concerning the energy consumption of these devices. Smart sensors, as fundamental components of IoT ecosystems, continuously generate vast amounts of data, requiring efficient transmission and processing. The energy-intensive nature of data communication in IoT devices highlights the need for innovative approaches to optimize their energy efficiency without compromising performance. This paper aims to evaluate the impact of data compression on the energy consumption and latency associated with data transmission in smart sensors within smart homes. To achieve this, the performance of various compression algorithms in compressing data generated by sensor nodes is evaluated. This evaluation is conducted with the aim of reducing data volume, improving transmission efficiency, and lowering the energy consumption of communication systems. The experimental results demonstrate that utilizing data compression techniques can significantly contribute to reducing energy consumption. By extending this process to all sensor nodes in smart home systems, a more substantial reduction in energy consumption can be anticipated. Such optimizations pave the way for more sustainable IoT ecosystems, balancing technological advancements with environmental concerns.

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