Novel Adaptive Hysteresis Regime and Data Fusion on Crisp Logic in IoT-based Terrarium System for Improving Plant Growth Rate

In the present, autonomous environmental supervision and management are still insufficient. The approach of independent parameter controlling emerges to restraining plant growth and resource inefficiency. Developing a new method to control environmental parameters for accelerating plant growth should be deployed to satisfy the optimum condition and resource efficiency. In this paper, we propose a novel advanced crisp logic-based integrated with adaptive hysteresis control and data fusion algorithm to adapt the behaviour of each plant parameter in a certain condition. The objective of the proposed system is to control each plant parameter into the optimum regime while considering the coupling relationship between them. The measurement results show that our proposed system has a more sustained optimum condition and faster change into the desired grade of membership by adapting the hysteresis regime. Based on the measurements, the proposed system produces an optimum condition that are more sustain and stable and produce accelerated plant growth by 35.33%.