Author : Bhagyashree Lambture and Miss. Revati M Wahul

In 2050, the global population is estimated to be about 9.7 billion, as a result of which there will be great food demand. In order to meet these needs, it is necessary to increase the existing system of agriculture. It’s fine, according to the traditional way of agriculture, but still it won’t meet the world’s entire requirements. Here applications of data mining techniques in estimation of yields and climate change are called to help the farmer make decisions for farming and gain the required economic return. A major problem that can be overcome based on past experience is the problem of yield estimation. Therefore, a brief study of crop yield prediction is proposed using CNN methodology. Using Google API to access crop production patterns in response to climatic conditions such as rainfall, temperature, relative humidity, evaporation and sunshine etc. Crop prediction is a pre-condition, and prediction of disease is a post-condition for the collection of data from a field or area from a weather parameter sample. It lets farmers improve quality in decision making. And using the software means farmers have crops with high yields.

Keywords: Smart Agriculture, Google API , CNN algorithm , IoT in agriculture