International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
“Plant Disease Detection by Using Deep LearningAlgorithm with Product, Price Recommendation and Crop prediction.” Shinde Saurabh1, Zambare Sanket2, Borate Sambhaji3, Prof. Gavali .A.B.4 Student of S. B. Patil College of Engineering, Indapur, Pune-413106, MH, India. Professor, S. B. Patil College of Engineering, Indapur, Pune-413106, MH, India. ---------------------------------------------------------------------***--------------------------------------------------------------------1, 2, 3
4Assistant
Abstract - In India, agriculture has come to be an important
source of economic development. The farmer selects a suitable crop based totally at the sort of soil, climate condition of the location, and economic cost. The agriculture industries started attempting to find new strategies to increase the manufacturing of food because of the increasing population, adjustments in climate and on the spot deep mastering with convolutional neural networks has performed amazing fulfillment in the classification of diverse plant sicknesses. In this examine, a ramification of neuron-wise and layer-wise visualization techniques are carried out the usage of a CNN, educated with a publicly available plant disorder photo dataset. We show neural networks can seize colors, textures of lesions specific to respective diseases on diagnosis. Key Words: Crops Prediction, Soil Detection, Medicine, Disease detection
1. INTRODUCTION In general, agriculture is the spine of India and additionally performs an critical function in Indian financial system by means of offering a certain percent of home product to make certain the meals security. However now-a-days, meals production and prediction is getting depleted because of unnatural climatic changes, so that you can adversely have an effect on the financial system of farmers via getting a poor yield and additionally assist the farmers to stay less acquainted in forecasting the destiny plants. This research work allows the newbie farmer in this sort of way to manual them for sowing the motive-capable crops by way of deploying system studying, one of the advanced technologies in crop prediction and disease prediction. CNN algorithm places forth in the way to attain it. The seed facts of the plants are amassed here, with the appropriate parameters like "temperature, humidity and moisture" content material, which enables the vegetation to attain and a hit increase. The users are endorsed to go into parameters like temperature and their region will be taken automatically in this application that allows you to begin the prediction Procedure. Also software will recommend medicine for leaf disease and display its rate. 1.1 Project Scope
1.2 Methodologies of problem solving We planned to design a module so that someone with no planning experience could use and get information about soil and plant diseases. It proposed a program to predict plant and leaf diseases. It also indicates the cure for the disease and its value. 1.2 Motivation of the project Modern technology have enabled human society to provide sufficient food to feed extra than 7 billion humans but, food security continues to be jeopardized due to a ramification of factors which includes weather change, pollinator decline, crop plant illnesses, and others. Crop Plant illnesses now not only pose an international threat to Food protection, however they can also have disastrous effects for smallholder farmers whose livelihoods depend upon healthy crops. Moreover, most people of hungry human beings (50 percentage) stay in smallholder farming households, making smallholder farmers mainly prone to pathogen-associated disruptions in meals deliver.
2. SOFTWARE REQUIREMENT AND SPECIFICATIONS 2.1 Assumption and dependencies
|
Impact Factor value: 7.529
|
Assumption:
As we give input image of plant system shoulddetect the disease on crop.
Dependencies:
We are totally depend on CNN model. 2.2 Functional Requirement
System Feature 1(Functional Requirement)
Crop disease should be detect using CNN algorithm.
"Agricultural departments wants to automate the detecting the yield plants from eligibility method (real time)".To
© 2022, IRJET
automate this technique with the aid of show the prediction result in internet utility or computer application. To optimize the work to implement in artificial Intelligence environment.
System Feature 2(Functional Requirement) Dataset is trained and tested properly
ISO 9001:2008 Certified Journal
|
Page 1925