The world's oldest and most active profession is agriculture. There is an urgent need for society as a whole to think creatively and discover new effective answers to farming, utilizing lesser land for producing more plants and increasing the yield of the cultivated land because the world's population is constantly growing and land is becoming scarcer. In order to produce healthy crops, monitor soil, control pests, manage burgeoning states, arrange farmer data, lessen volume of work, and proceed to a variety of farming activities throughout the total food supply chain, farming is growing into artificial intelligence technology on a global scale.
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Agriculture automation is a significant issue and a changing problem for every location. Worldwide population is expanding quickly, and this growth in population is causing a tremendous expansion in the need for food. Farmers must employ more toxic pesticides in greater quantities in order to injure the soil since their traditional techniques are unable to meet the expanding demand. The ground still isn't fertile as a result, and this has a significant impact on agriculture. Crop pests, a shortage of storehouse, pesticide regulation, plant supervision, irrigation, and water management are a few areas that have an impact on agricultural difficulties. All of this will be trumped by artificial intelligence.
With much fewer meteorological data, two ANN models were constructed by (Liew, Y.W., et al., 2022) to predict soil moisture in Paddy regions. All models have been validated and put to the test via examination of observed soil and estimated soil humidity values. In order to replicate the spatial surface water flow, ANNs have been constructed in the (Onu, C.E. et al. 2022) study on neuro-drip irrigation systems. For the irrigation system to function properly, the distribution of water at the soil's bottom layers is crucial. In this situation, ANNs provide a forecast which is helpful to the user and prompts a quick decision-generating technique.
Embedded intelligence analytics (EI), a recent discipline, was established by (Bonetti, F., et al., 2022). The agricultural embedded intelligence includes smart planting, smart field production, smart irrigation, and complex greenhouses. Many industries rely on agriculture for a country to be able to develop these emerging technologies in the agricultural sector.