Affiliation:
1. High School of Automation and Robotics, Peter the Great Saint Petersburg Polytechnic University, 195220 Saint Petersburg, Russia
2. Department of Energy and Technology, Swedish University of Agricultural Sciences, P.O. Box 7032, 750 07 Uppsala, Sweden
3. Department of Mechanical Engineering, University of Technology, Baghdad P.O. Box 19006, Iraq
Abstract
In an agricultural system, finding suitable watering, pesticides, and soil content to provide the right nutrients for the right plant remains challenging. Plants cannot speak and cannot ask for the 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 agricultural fields. 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, and humidity sensors, and the outputs were pump flow, valve opening, water level, and moisture in the sounding. The obtained results were the output of the valve opening, moisture in the sounding, pump flow rate, outflow, water level, and ADH values, which are 10.00000013 rad/s, 34.72%, 4.494%, 0.025 m3/s, 73.31 cm3, and 750 values, respectively. The outflow rate increase indicates that water is being released from the tanks, and the control signal fluctuates, indicating that the valve is opening.
Subject
Electrical and Electronic Engineering,Engineering (miscellaneous),Computer Science (miscellaneous)
Reference25 articles.
1. FAO (2018). The Future of Food and Agriculture: Alternative Pathways to 2050, Food and Agriculture Organization of the United Nations.
2. von Braun, J., Afsana, K., Fresco, L.O., and Hassan, M.H.A. (2023). Science and Innovations for Food Systems Transformation, Springer.
3. Food neophobia and its association with dietary choices and willingness to eat insects;Hopkins;Front. Nutr.,2023
4. Application of the response surface methodology (RSM) in the optimization of the fluidizing and sweetening capacities of sprouted flours of two maize varieties (Atp-Y and Coca-sr);Adebo;Cogent Food Agric.,2023
5. Application of fuzzy logics for smart agriculture: A review;Lee;Precis. Agric.,2023