This paper investigates the factor of tuning variable parameter for Single Input Fuzzy Logic Controller (SIFLC) to improve the performances of depth control for the underwater Remotely Operated Vehicle (ROV). This study and investigates will focus on the number of rules in SIFLC, lookup table, slope of a linear equation, and also model reference to give optimum performances of depth control without overshoot in system response and faster rise time and settling time. The variable parameter for SIFLC is tuned by Particle Swarm Optimization (PSO) algorithm. The investigation focused on the number of rules will be reduced, SIFLC parameter reduced, represented lookup table as a linear control surface method to represent the inference engine of FLC. The investigation on model reference also covered in this paper. The current of model reference will give the best system response for depth control. The slope of linear equation either in positive and negative values and come up from conventional FLC then will simplify into SIFLC. The results obtained the number of rules, the slope of linear equations and model reference will be affecting the results of system performances.

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Quadrotor has emerged as a popular testbed for Unmanned Aerial Vehicle (UAV) research due to its simplicity in construction and maintenance, and its vertical take-off, landing and hovering capabilities. It is a flying rotorcraft that has four lift-generating propellers; two of the propellers rotate clockwise and the other two rotate counter-clockwise. This paper presents modeling and system identification for auto-stabilization of a quadrotor system through the implementation of Extended Kalman Filter (EKF). EKF has known to be typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems. In this paper, two main processes are highlighted; dynamic modeling of the quadrotor and the implementation of EKF algorithms. The aim is to obtain a more accurate dynamic modelby identify and estimate the needed parameters for thequadrotor. The obtained results demonstrate the performances of EKF based on the flight test applied to the quadrotor system.

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The goal of this paper is to review the implementation of an Internet of Things (IoT)-based system in the precision agriculture sector. Each year, farmers suffer enormous losses as a result of insect infestations and a lack of equipment to manage the farm effectively. The selected article summarises the recommended systematic equipment and approach for implementing an IoT in smart farming. This review's purpose is to identify and discuss the significant devices, cloud platforms, communication protocols, and data processing methodologies. This review highlights an updated technology for agricultural smart management by revising every area, such as crop field data and application utilization. By customizing their technology spending decisions, agriculture stakeholders can better protect the environment and increase food production in a way that meets future global demand. Last but not least, the contribution of this research is that the use of IoT in the agricultural sector helps to improve sensing and monitoring of production, including farm resource usage, animal behavior, crop growth, and food processing. Also, it provides a better understanding of the individual agricultural circumstances, such as environmental and weather conditions, the growth of weeds, pests, and diseases.