Comparative Analysis of Filtering Techniques for Efficient Data Aggregation in Smart Hydroponic Systems - Qomariyah, Nurul; Putra, Septafiansyah Dwi; Asrowardi, Imam (Politeknik Negeri Bengkalis, 2024)
The rapid evolution of digital technologies has transformed traditional agriculture into a more efficient andintelligent system. This study focuses on the development of a data aggregation strategy in Smart Hydroponic Systems tooptimize network consumption without sacrificing data accuracy. By utilizing Threshold Filtering and Delta-BasedFiltering techniques, significant reductions in data transmission were achieved while maintaining essential temperaturemonitoring capabilities. Experimental results demonstrated that both techniques effectively reduced data points andoptimized bandwidth usage, particularly in temperature-stable environments. This research contributes to theadvancement of sustainable digital agriculture by providing an efficient approach to managing network resources in IoTbasedhydroponicsystems.