Digital Agriculture: An Approach to Balance the Water Level using Ambient Intelligence in Cloud - S Kanaga Suba Raja, Valarmathi K, Akhila Balasubramanian, Amrita Mohanta, Abirami S (International Journal of Advanced Science and Technology, 2020)
Crop Production in agriculture depends majorly on the amount of water it requires for providing higher yield. The main source of water to the agriculture land is rain water and irrigation from well, tanks and canals which cannot be monitored properly. Every year there are several cases of mass crop destruction reported due to unseasonal rains which financially affects majority of the farmers. Crops cannot survive and grow when water is insufficient while excess water affects the plant roots and disrupts the pH – level, electrical conductivity, dissolved oxygen level of water in the soil by making it acidic. This causes the crops to suffocate which ultimately results in crop wastage. Our proposed system resolves this issue by properly balancing the water consumed by the crop through Ambient Intelligence (AmI). This is achieved by adding proper measure of necessary fertilizers that balances the pH level and dissolved oxygen level of the soil thereby making it suitable for the crop. Machine Learning techniques are therefore employed to predict the stability and the proper amount of fertilizers that are required by the crop under various circumstances to make the water level stable. The crop that is being taken into account is rice.