Deep Learning based Smart Agriculture Crop Prediction
| Main Authors: | Dr T. Bhaskar, Aniket Dhanwate, Prashant Kale, Gurudatt Kayastha, Ganesh Khairnar |
|---|---|
| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2021
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4817777 |
Daftar Isi:
- India is country where 70% of the population is dependent on agriculture. For development of the country this sector of the population has to be developed. But there are many problems facing the agriculture sector from water scarcity, environmental disasters and lack of proper knowledge of the crops and how to cultivate them. So, to really bring India from a developing country status to developed one we need to understand the farmers concerns and help them using today’s technologies. So, we thought of designing a system which will help farmers understand which crop to grow and help them with the crops stages and what kind of seeds, manures and other cultivation techniques can be used with a specific crop. So, our agricultural frame work will be a combination of cloud computing, mobile computing, desktop computing and artificial intelligence together to achieve prosperity of farmers. In our system a farmer will first register using a mobile ap- plication designed for him. From the mobile he will send his location coordinates with the soil type. The parameters will be sent to cloud. These parameters sent by the farmer will be downloaded on the server side for prediction. On the server side which will be a desktop application will have a training dataset with parameters such as latitude, longitude, avg. rainfall, avg. temp, soil type, avg yield of various crops such as wheat, rice etc. Then a deep learning architecture will be created using embedding, GRU, RNN, Dense and Dropout layers. The architecture will be trained using training dataset with three yield classes low, medium and high. The parameters received from farmers will be passed to trained model which will return prediction. The prediction will be for each crop type i.e., whether the crop comes under low, medium or high yield type. The crops under each yield type will be up- loaded to farmer’s account. The farmer will receive an alert notification so that he can login to his account and view crops with yield types. Thus, farmer can grow his desired crop. Thus, by using our new smart agricultural frame work a farmer can increase yield of his crop by getting better insights on which crop to grow and tips on how to grow it.