Retracted: IoT Based Agriculture Robot Using Neural Networks

摘要

In our country food crisis is one of major concerns. That is due to lack of new age technologies. The food crisis in our country is due to climate change, lack of soil nutrients, decline in pollinators, plant disease and wastage of water in traditional methods of irrigation leads to water clogging on topsoil. The proposed model overcomes the problems, which helps in the increase of efficiency in crop irrigation. This leads to a reduction in energy of Labor and water consumption. This model helps us to find the disease by observing symptoms on the leaves by using new age technologies like Neural Networks for diseased and healthy plant leaves collected under control condition and we train them by using conventional neural network. This system uses Raspberry pi microcontroller. To create a feasible and low cost implemented model, YL-69 soil moisture sensor is used to detect the soil moisture from time to time. To detect the temperature and humidity DHT11 is used. Using Neural Networks, we classify the leaf disease and we label the disease this method is known as Supervised Learning. We detect the disease that in plants by using MATLAB analysis. By using this system there will be increase in food production and helps farmers to visit the farm less frequently and to focus on the other activities or even maintain several farms with a variety of crops. The robot developed in this work is semi- automatic which helps to detect the leaf disease.