Automatic Farm Covering System in Unfavorable Conditions Using Machine Learning and IoT

Swati Nawange; Dr. Dilip Khairnar; Prashant Titare; Akash Palhade; Hemant Patil

CALL FOR PAPERS : Dec-2023

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25-Dec-23

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Automatic Farm Covering System in Unfavorable Conditions Using Machine Learning and IoT

Author(s):

Swati Nawange , D Y Patil College of Engineering, Akurdi, Pune; Dr. Dilip Khairnar, D Y Patil College of Engineering, Akurdi, Pune; Prashant Titare, D Y Patil College of Engineering, Akurdi, Pune; Akash Palhade, D Y Patil College of Engineering, Akurdi, Pune; Hemant Patil, D Y Patil College of Engineering, Akurdi, Pune

Keywords:

Random Forest Classifier, DHT 11, Automation, Soil, and Moisture Sensor, Data Modelling

Abstract:

India is the country where 70% of the population depends on farming. Farming is the primary resource income in rural parts of India. As the population is increasing day by day, the need for huge Raw materials is also required for processing food. So there will be a huge constraint on the farming sector. Nowadays, due to global warming and other drastically changing environmental conditions like heavy rains, the crops get damaged at the yielding stage and cause a significant loss to the farmers. There is also a need for advanced farming adaption techniques in the fast-changing technology world. Every farmer believes in good results at yielding stage and excellent quality. For fulfilling the above conditions, an Automatic farm covering system in unfavourable Conditions and parallel a Smart irrigation system is developed. These will help to reduce effects at the yielding stage also provides irrigation smartly. The project consists of Raspberry Pi as a controller, three different sensors (DHT 11, humidity, moisture, soil) as input. The output is connected to Raspberry Pi which consisting Driver IC and high torque DC motor, valve. The output is activated by the developed App. It takes required inputs from the user, uploads them to the server. It has a client-server architecture. The raspberry pi processes data as per intelligence given to it by the Machine Learning model. Machine Learning algorithm (Random forests Classifier) works on sensor data for predicting the mechanism of automatic ON / OFF system. The predicted result is given as output to the Motor driver and Valve for Automatic ON and Off purposes. The farmer can able to do an Automatic Shut/Open system by using an App (Mobile application controlled through Internet). All processes such as irrigation, covering the system in unfavourable conditions can be held remotely with the help of App and a Smart automation system.