Deteksi Duplikasi Data pada Sistem Pemantauan Kualitas Udara Berbasis IoT
Abstract
The increasing volume of data on the Internet of things (IoT)-based systems has driven the need for efficiency in data management, particularly in air quality monitoring systems. One approach to address this challenge is data duplication detection, which works to eliminate redundant data to reduce storage requirements and power consumption. This study aims to develop an IoT-based air quality monitoring system incorporating a data duplication detection method as part of an effort to support the green IoT concept. The methodology involved a comparative analysis between systems with and without the implementation of data duplication detection, accompanied by a comprehensive evaluation of system performance. The data tested included the size of transmitted data and device power consumption during the transmission process. Testing was conducted under real operational conditions over a 24-hour period. The results indicate that the implementation of data duplication detection successfully reduced the size of transmitted data from 56 bytes to 11–44 bytes, depending on the level of data redundancy. Power consumption was reduced by 1.59% to 3.84% compared to the system without data duplication detection. This method was also proven not to affect the accuracy of the displayed data, thereby maintaining the system’s functional requirements. In conclusion, the implementation of the data duplication detection method in an IoT-based air quality monitoring system not only optimizes data transmission processes but also supports energy efficiency in line with the principles of green IoT. This research provides a significant contribution to the development of more sustainable and energy-efficient IoT systems.
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