Application of IoT and Machine Learning in Agriculture
Rajendra Sonu Dhamnak
Department of Computer Application, ASM IMCOST
University of Mumbai,
Mumbai, India, and Pin-400068
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Abstract — Agriculture is one of the major resources of economic system in the united states. Precision Agriculture is already in implementation in other international locations however there is a need to put in force, improve and evolve IoT(Internet of Things) and cloud computing technology for better production of the crop. There is a steady increase in demand with populace growth. Modernization in agriculture reduces dependency on man or woman human exertions and land. The era allows operational devising and speeds up verdict making on Farms. IoT permits us to accumulate surrounding facts, stock it, concoct it and disseminate the information. The adoption of cloud computing has gone through a big upward push in need and might continue to grow within the coming destiny with stepped forward cloud hosting and processing dexterities. AI(Artificial Intelligence) and IoT is a tremendous lead as a method to expanded productiveness. The records via IoT gadgets is made available publicly for research purposes as facts sets and is processed and examined for further prediction related to the crop being produced. The Traditional Technique of farming does now not contain any system which include seed choice, soil evaluation, weather analysis, plant life evaluation, Nutrient evaluation if these kind of elements are taken in care, this all might bring a drastic change in the society. The System additionally has a block-chain based delivery system to make certain right distribution with none wastage. Though the pen-paper lifestyle is difficult to be replaced however minimizes a lot of paintings, furthermore the evaluation of guide work required can also be analyzed. A extra complex method to IoT merchandise in agriculture can be represented via the so-referred to as farm productivity control systems. They generally include several agriculture IoT gadgets and sensors, mounted at the premises in addition to a effective dashboard with analytical competencies and in- built accounting/reporting functions. In addition to the indexed IoT agriculture use instances, a few outstanding possibilities consist of automobile tracking (or even automation), storage management, logistics, etc.
Keywords — Internet of Things(IoT), Artificial Intelligence(AI), Machine Learning(ML), Smart Agriculture.