The main objective of Soil Prediction and Fertility Suggestion is to accurately predict soil characteristics and nutrient levels to provide farmers with tailored recommendations for optimizing crop productivity. The main objective of Crop Prediction and Plant Disease Detection is to utilize machine learning techniques to forecast crop yields and identify plant diseases early, enabling proactive measures for maximizing agricultural productivity and minimizing crop losses.
Economy contributes the most for the productivity of the agriculture. In agricultural field, the disease in plants is more common and the detection of disease in plants has become more feasible due to the above reason. These days's plant disease detection has acquired enlarging scrutiny in shrivelling crops of large and various fields. Farmers undergo significant hassles in chop and changing from one disease administer principle to a different one. We can identify or spotting the tomato leaf diseases for detection for surveillance and monitoring experts is the standard approach for detection. The plants get seriously affected if the proper control hasn't been taken and this represents the quality of the pants the production of the plants will be affected.
Keywords: Soil- RandomForestClassifier, DecisionTreeClassifier, SVC, Logistic Regression, GaussianNB and MLPClassifier.
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SOFTWARE FRONT END REQUIREMENTS
H/W CONFIGURATION:
Processor- I3/Intel Processor
Hard Disk- 160GB
Key Board- Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
RAM- 8GB
S/W CONFIGURATION
Operating System: Windows 7/8/10
Server side Script: HTML, CSS, Bootstrap & JS
Programming Language: Python
Libraries: Flask, Pandas, Mysql.connector, Os, Smtplib, Numpy
IDE/Workbench: PyCharm
Technology: Python 3.6+
Server Deployment: Xampp Server