Fuzzy logic model in Real-time growth recommendation to improve agriculture production

Abstract

Many Filipino farmers are currently associated with manual farmland, including includes soil preparing, seeding, and reaping, according to the India Laboratory for Post-Harvest Advancement & Machineries (PhilMech). Individuals are compelled to participate in Precision Farming as a result of this. That's a modern agriculture approach that relies on a variety of technology such as sensors and application programs. As just a result, a research study was conducted to solve the problems of traditional field cultivating with Crop Monitoring technology. Even though current technology allows again for identification of plant or organic fertilizers and pathogens, neither one of these research suggested commodities be grown based also on soil's condition. The goal of this project was to develop stand-alone agricultural recommendation equipment that might assess soil properties & offer a selection of generic commodities from a library. The pH level, soil humidity, soil conditions, & soil quality were all monitored using various sensors. A next stage would have been to create a fuzzy logic technique for plant recommendations following building a system for pH, soil quality, soil humidity, and temperature monitoring. This Philippine Commission for Agricultural & Resources Research Center Agricultural Recommendations dataset was utilized to create the membership function parameters for the fuzzy inference system framework. This dataset included min and max temperatures, pH, soil humidity, and soil nutrient information for each of the 30 commodities that are regularly grown in the United States. These fuzzy criteria also were developed to determine whether a product is terrible, good, or excellent to grow on a particular natural soil. This gadget improved agriculture production accuracy, which boosted profitability for landowners by allowing them to better utilize existing assets. Both real environmental state and much more sophisticated sensor technology can be explored for future upgrades towards this investigation.