Smart mechatronics system in agriculture can be traced back to the mid-1980s, when research into automated fruit harvesting systems began in Japan, Europe, and the United States. Since then, impressive advances have been made smart mechatronics systems. Furthermore, smart mechatronics systems are promising areas, as results, we were intrigued to learn more about them. Consequently, the purpose of this study was to examine the smart mechatronic systems that have been applied to agricultural areas so far, with inspiration from smart mechatronic system in other sectors. To get an overview of the current state of the art, benefits and drawbacks of the smart mechatronics systems, various approaches were investigated. Moreover, smart mechatronic modules, and various networks applied in agriculture processing were examined. Finally, we were explored how the data retrieved using the one-way analysis of variance related to each other. The result showed that there were strong related keywords for different journals. The virtually limited use of sophisticated mechatronics in the agricultural industry, and at the same time, the low production rate, the demand for food security has fallen dramatically. Therefore, the application of smart mechatronics system in agricultural sectors would be taken into consideration in order to overcome these issues.

In an agricultural system, finding suitable watering, pesticide, and soil content to provide the right nutrients for the right plant is a mystery so far. Plants cannot speak and cannot ask which food they require. These problems can be addressed by applying intelligent (fuzzy logic) controllers to IoT devices in order to enhance communication between crops, ground mobile robots, aerial robots, and the entire farm system. The application of fuzzy logic in agriculture is a promising technology that can be used to optimize crop yields and reduce water usage. It was developed based on language and the air properties in the agricultural fields were formulated. The entire system was simulated in the MATLAB/SIMULINK environment with Cisco Packet Tracer integration. The inputs for the system were soil moisture sensors, temperature sensors, humidity sensors, and outputs were pump flow, valve opening, water level, and moisture in sounding. The obtained results were the output of opening valve, moisture in sound, pump flow rate, outflows, water level, and ADH values, which are 10.00000013 rad/sec, 34.72%, 4.494%, 0.025 m^3/sec, 73.31 cm^3, and 750 values respectively. The outflow rate increase indicates that the water is released from the tanks, and the control signal fluctuates, indicating that the valve is opening.

Wheeled mobile robot dynamics and suitable controller design are challenging but rewarding fields of study. By understanding the dynamics of wheeled mobile robots, it could be possible to design suitable hybrid control schemes for wheeled mobile robots. Since hybrid control schemes involve combining individual control methods to create a more effective overall control strategy. This can be done in a variety of ways, such as using fuzzy linear quadratic Gaussian control. We were therefore inspired to create dynamic models and their controller designs for the wheeled mobile robot by examining the dynamics of the wheeled mobile robot. The novelty of the current paper is to hybridize the different control schemes for wheeled mobile robots in order to get better performance. Entire systems models were simulated in a MATLAB/SIMULINK environment. The results obtained for the settling time response by FLQG were 87.1% over LQG; this study compared the effectiveness of current and previous FLQG controllers in external disturbances and found peak amplitude improvements of 71.25%. Therefore, the proposed controller is suitable for use with the wheeled mobile robot.