E-Agri Kit using Deep Learning and Machine Learning
Objective
By combining Deep Learning and Machine Learning approaches, the E-Agri Kit aims to revolutionize agriculture. The kit intends to improve agricultural procedures, improve the accuracy of yield forecast, optimize resource allocation, and enable early disease diagnosis in crops by utilizing the potential of modern technologies. It enables farmers to make informed decisions through data-driven insights, improving crop quality, reducing resource waste, and enhancing sustainability. The E-Agri Kit aims to equip farmers with simple-to-use technologies that offer real-time monitoring, analysis, and recommendations so they can respond to shifting market needs and environmental conditions. The ultimate goal of modernizing agriculture is to increase its productivity, efficiency, and resilience in the face of obstacles, hence enhancing food security and the standard of living for rural communities.
Abstract
Our paper presents an agriculture aid application which is developed and designed to help the farmers. As Agriculture was the key development in the rise of sedentary human civilization, whereby farming of domesticated species created food surpluses that enabled people to live in cities. And it will be difficult for a person to identify every crop just by looking at the leaves and along with that selling the crop for a suitable and affordable prices is difficult to a farmer. Where to overcome this all problems we are creating an application where we are developing an algorithm that detects the type of crop by giving the leaf input image and also creating a platform where an investor can invest into a crop by funding into a crop which is given by a farmer and where farmer can sell their crops to buyers with the rates that which are suitable with the crop.
KEYWORDS: Agriculture, Deep learning, Investment, Farmers, selling.NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
SOFTWARE FRONT END REQUIREMENTS
H/W CONFIGURATION:
RAM: 8GB, 64 bit os.
Processor: I3/Intel processor
Hard Disk Capacity: 128 GB +
S/W CONFIGURATION:
Technology: Python, Application.
Libraries: Pandas, Numpy, Tensorflow, OS.
Version: Python 3.6+
Server side scripts: HTML, CSS, JS
Frame works: Flask
IDE: Pycharm
Database: MySQL
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