Prototype Implementation of Neural Networks based Agricultural Farm Monitoring and Rain Prediction

Artificial Neural Network acts as a human brain to monitor and predict the weather condition in an agricultural farm. The weather data of the farm such as temperature, humidity, rainfall status and soil moisture sensor values are being monitored Based on the monitored data, the weather is being predicted and irrigation process is carried out automatically. Weather forecasting is an awful endeavour since it is an unbroken, multidimensional, effective, disorderly procedure that employs an IoT of data or information. The primary purpose is to determine how well our proposed soft computing Neural Network technique works well. This research will aid in the prediction of rain fall occurrences based on current temperature and humidity levels. Artificial Neural Networks offer a mechanism for resolving a variety of non-linear problems that are difficult to handle using traditional methods. Artificial Neural Networks may build a connection between the inputs and outputs without requiring any internal processing. As a result, the above-mentioned qualities of Artificial Neural Networks can be inferred to be appropriate for weather forecasting under scrutiny.