Implementation of Huffman Compression for Optimizing Sensor Data Delivery in IoT Monitoring Systems
DOI:
https://doi.org/10.55537/cosie.v5i1.1355Keywords:
Kompresi Huffman, Optimasi Pengiriman Data, Jaringan Wireless Terbatas, Protokol ZigBee, Internet of Things (IoT)Abstract
Real-time data transmission in Internet of Things (IoT) environments often faces limitations in bandwidth and energy efficiency, leading to latency during continuous data transfer. This study conducts a ZigBee-based simulation using Python to evaluate data compression efficiency in IoT sensor communication systems. The transmitted data are collected from four types of sensors temperature, pressure, humidity, and vibration with a total of 100 records generated randomly to represent ideal industrial environmental conditions. The Huffman Compression method is applied to reduce the size of sensor measurement data before transmission. Simulation results show that the total data length was reduced from 27,632 bits to 13,385 bits, achieving a 51.56% reduction. Consequently, the average transmission time decreased from 0.11053s to 0.0535s, and energy consumption dropped from 0.001382 J to 0.000669 J. In addition, bandwidth usage was reduced from 27.63kb to 13.38kb. These results indicate that applying Huffman Compression can significantly enhance transmission efficiency, reduce energy consumption, and optimize bandwidth utilization in ZigBee-based IoT communication systems.
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Copyright (c) 2025 M Khalil Gibran, Mhd Ikhsan Rifki, Afandi Sahputra, Ahmad Taufik Al Afkari Siahaan
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