Advancements in agricultural decision support systems: A data fusion approach - Zulkefli, Nur Al Aswad; Mohamed Kassim, Anuar; Yaacob, Mohd Rusdy; Abd Aziz, Muhammad As Shakirin; Awangku Jaya, Awangku Khairul Ridzwan; Ngadiron, Zuraidah; Yasuno, Takashi (ZES Rokman Resources, 2024)
At the forefront of precision agriculture, this paper presents an advanced decision support system that integrates a focused dataset from soil sensors measuring pH, temperature, electrical conductivity, and humidity. This research is centered on a rock melon farm, where the aforementioned soil parameters are critical for crop success. By leveraging MQTT for efficient data transmission and Grafana for intuitive data visualization, the system offers real-time insights that guide critical farming decisions. The study demonstrates how this selective data fusion approach can significantly improve the accuracy of soil health assessments, which in turn can lead to enhanced crop yields and reduced operational expenses. The findings provide valuable contributions to the field of agronomy, particularly in the cultivation of rock melons, by offering a refined method for managing agricultural inputs. The practical application of this system is exemplified in its use within a rock melon farming context, proving its versatility and effectiveness in supporting farmers with precise, data-informed strategies to maximize resource efficiency and economic returns.