International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023
p-ISSN: 2395-0072
www.irjet.net
Kissan Konnect – A Smart Farming App Atharva Kathane1, Amol Mali2, Manthan Pawar3, Harsh Khairajani4, Dr. Rohini Temkar5 1,2,3,4Dept. of Computer Engineering, VESIT Affiliated To The University Of Mumbai, Maharashtra, India
5Professor, Dept. of Computer Engineering, VESIT Affiliated To The University Of Mumbai, Maharashtra, India
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Abstract— Agriculture is the basic economic backbone of every country. India being the developing country has agriculture as its main occupation. Almost 50% of the population has agriculture as their main occupation. The idea is to develop an application that will be useful for farmers and reduce their dependencies. Farmers today follow traditional agriculture cultivation methods. Cultivating same crop repeatedly and that results in degradation of the soil quality. To solve such issues and more we have developed web application. The Application will recommend the best crop to be yielded according to the weather, soil type, rainfall, temperature, humidity and pH. Another important feature that has been implemented is the disease detection module. The proposed machine learning model will scan the images uploaded by the farmers and diagnose the disease. Some farmers do not own the modern tools due to the cost. The proposed solution for that problem is the "tool rental module". In this way the application is able to make significant contribution to the lives of the farmers and increase the crop cultivation
intelligently recommend the crop that can be cultivated and would be the most profitable. Farmers use chemicals and pesticides to keep the insects at a bay. But when overused, it may damage the crop. Unknowingly the yield of the crop is affected. Leaves are one of the most sensitive parts of the plant from where we can first detect the symptoms of disease. It is necessary to begin monitoring the crops from a very early stage of their life cycle till the time they are ready to be harvested. Initially plants were observed and monitored to prevent diseases using traditional naked eye observation which is a time-intensive technique and requires very careful observation. Mostly, the symptoms of the diseases can be seen on the leaves, the stem or the fruits. Most of the time, leaves of the plant are considered for the detection of disease. Many times farmers do have enough and adequate knowledge about the crops and the diseases from which the crops are at risk. With new breeds of crop, new diseases are also being discovered. By using our system the farmers can effectively increase their yield and protect the crops from diseases without having to visit any expert. A web application named Kissan Konnect-Smart Farming Solution was developed. The proposed system has various smart farming solutions which can be utilized from anywhere & anytime. The services include Crop prediction which will take input parameters like soil pH, rainfall, air humidity, air temperature and soil humidity of the land and using Random Forest Classifier. The ML model will help predict the best suitable crop to be cultivated considering all these aspects. Also, the web application offers a service that will assist farmers in detecting the disease that has affected the crop. The photographs that the farmer has submitted for diagnosis were used. The uploaded photos will be compared to the database, and the module will identify the disease using a machine learning model. Also, the website will offer a possible treatment for the identified illness. Plant Disease Recognition service [2] will use image processing for model construction and after taking the image input of the affected leaf it will accurately diagnose the disease. The proposed system also provides a service where farmers can rent tools from nearby farmers instead of buying them. This will help in reducing the cultivation cost. Reaching the tools will be simpler because they will be displayed depending on location. Email and phone numbers are available for contact. The news feed service will keep the farmers updated about new methods, technology, agriculture related. Farmers will benefit from the weather forecast function by being informed of both present and upcoming weather forecasts so they may be ready for upcoming circumstances. For this rest
Keywords—Agriculture, Crop prediction, Plant disease detection, Soil, Image processing
INTRODUCTION Around half of the population in India has agriculture as an occupation. Agriculture has a major role in the overall economic growth and development of our country. With consistent growth and population increase, recent studies indicate a need to increase food production to 70 to 90% by 2050. Thus, adopting a new age method in certain agricultural activities with the help of the latest technologies and softwares will prove to be very beneficial for the farmers and the consumers. Prior crop prediction algorithms came into action, the same task was performed on the basis of farmers’ past experiences and intuitions for a particular location. The yield could be harmed by improper crop rotations and unplanned use of specific soil nutrients. Considering all these problems, we are planning to design our system which will act as a remedy and satisfy certain agricultural needs. This paper presents a system that will recommend the appropriate crop for a particular land, based on different parameters like weather, soil type, rainfall, temperature, humidity and pH. Hence by utilizing our system, farmers will be able to cultivate profitable crops which will actually yield in large numbers and prove beneficial over the long term too. Our system will
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