CROFED - Crop and Fertilizer Recommendation and Disease diagnosis system using Machine Learning and Internet of Things.
Author(s):
Taranjeet Singh, Saurabh Anand, Siddhesh Mahajan, Anmol Sehgal, Pranoti Kavimandan
Keywords:
Crop Recommendation System, Fertilisers Recommendation System, Crop Disease Detection, NPK Ratio, XG Boost, CNN.
Abstract
The major problems that the farmers of our country are currently facing includes Crop Failure, Lack of adequate knowledge, Crop damage due to ignorance/carelessness, Lack of professional assistance, Inaccessibility to agro-tech solutions. CROFED will help the farmers to deal with these problems by providing following aids: Crop Recommendation system, Fertiliser suggestion system, Crop Disease Detection System. We will develop an IOT device that will examine the quality of soil and can also detect crop diseases on scanning the leaves of the crops. Soil testing is significant since it allows for the determination of soil fertility and hence crop prediction.Soil pH is a measure of the acidity and alkalinity in soils. pH levels range from 0 to 14, with 7 being neutral, below 7 acidic and above 7 alkaline. We have proposed a system which will have a device which gives pH value and we will estimate Nitrogen (N), Phosphorus (P) and Potassium (K) from the pH of that soil. We are using Machine Learning classification algorithm to predict suitable crops based on the values we get from our device and we will also provide suitable fertilisers required for that land. We believe this will help the farmers in producing greater yield of crops and crop damage can also be prevented to a larger extent.
Article Details
Unique Paper ID: 155991

Publication Volume & Issue: Volume 9, Issue 2

Page(s): 660 - 667
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