Analysis of Crop Detection Based on Various Soil Testing Methods

Agriculture has the largest contribution in the GDP of our country. But still the farmer’s don’t get worth price of the crops. It is mostly happens due to improper irrigation or inappropriate crops selection or also sometimes the crop yield is less than that of expected. By analyzing the soil and atmosphere at particular region best crop in order to have more crop yield and the net crop yield can be predict. This prediction will help the farmers to choose appropriate crops for their farm according to the soil type, temperature, humidity, water level, spacing depth, soil PH, season, fertilizer and months. The objective of this study is to develop a methodological framework to define the accuracy requirements for early estimators of cropland area, crop area and crop yield in Senegal. These requirements are made according to (i) the inter-annual variability and the trend of historical data, (ii) the calendar of official statistics data collection, and (iii) the time at which early estimations of cropland area, crop area and crop yield can theoretically be available. All this can be done using the smart phones and IOT devices. Farmers can get the required data or information as well as monitor his agriculture sector. IOT connects the whole world with the help of sensors, acutators and other embedded devices. There lies an urgent need for using IOT in agriculture which makes it more reliable for farmers.