Integration of Machine Learning and IoT System for Monitoring Different Parameters and Optimizing farming

Abstract

Agriculture or farming is something from which any country can rule in the world. Many countries are developing new techniques for farming. In this paper, we have introduced a better tool for growing plants considering Hydroponics, the base of the system. From this, one can produce better plants in their home as well. While growing plant some factor consideration is important like temperature, humidity, nutrient content in the soil or soil moisture. With proper supervision, these factors are controlled. We implemented a Machine Learning setup in the field. All sensors(pH Sensor, DHT 11 Sensor, DS18B20 Sensor) sensing their respective parameters which are required to observe for monitoring of plants. All the data collected from different sensors are saved in a text file which is converted into a CSV file for machine learning algorithm and also this text file is sent to Thingspeak server for monitoring purpose which aggregate, visualize and analyse live data streams in the cloud. In urban areas due to the development everywhere, there has been a lot of land shortage and in rural areas due to lack of knowledge, even today, the old farming technique is used which takes much time and much water. The technique introduced in this paper can solve the problems of the farmers in rural areas as well as in urban areas.