Open Access Open Access  Restricted Access Subscription or Fee Access

ML Based Agro Solution

Vinay Suresh Kumar Jain, Prathamesh Baliram Khedwan, Ashish Siddappa Mankani, Anuradha Dandawate

Abstract


Nowadays, in India, the climatic conditions change rapidly. Sometimes the climate is cold, sometimes it turns out to be humid. In such drastic conditions, farmers are unable to decide which crop we must grow in that particular season according to that climate. This becomes a tedious task for the farmers during decision making. Also, it becomes difficult for the farmers to detect what kind of disease has happened to the crops grown by him. Also, it is difficult for the farmers to find the vendors who could take their products and sell them in a good price. Even though, the farmer gets a particular vendor, he could not find profits by selling products to that particular vendor. To overcome all these problems, we would be designing a system known as-one to one stop solution for crop guidance in which farmers would get solutions to all the above-mentioned problems. The interface provided by us will be efficiently helpful to the farmers to boost their productivity which would also boost up the agriculture industry in India. Machine learning, like crop management, allows for precise forecast and assessment of agriculture variables in order to maximise the market prosperity of animal production systems like cow and egg production.


Full Text:

PDF

References


Crop yield prediction using Agro Algorithm in Hadoop‖ by Ashwani Kumar Kushwaha, Sweta Bhattachrya, a paper from IRACST-International Journal of Computer Science and Information Technology & Security (IJCSITS).

Identification of Plant Disease using Image Processing Technique‖ by AbiramiDevaraj, Karunya Rathan, Sarvepalli Jaahnavi and K Indira, a paper from International Conference on Communication and Signal Processing. April 4 2019

A survey on data mining techniques for crop yield prediction‖ by Ramesh A Medar, Vijay S Rajpurohit, a paper from International Journal of Advance Research in Computer Science and Management Studies 2 (9), 59–64, 2014

A survey on rainfall prediction using artificial neural network‖ by Deepak Ranjan Nayak, Amitav Mahapatra, Pranati Mishra, a paper from International Journal of Computer Applications 72 (16), 2013

A study on various data mining techniques for crop yield prediction‖, an IEEE conference paper by Yogeshgandge, Sandhya.

Crop prediction using predictive analytics‖, an IEEE conference paper by P. S. Vijayabaskar, R. Sreemathi, E. Keertanaa.

Fast and Accurate Detection and Classification of Plant Diseases: https://youtu.be/0g-UFpdMi-w

Badage A. Crop disease detection using machine learning: Indian agriculture. Int. Res. J. Eng. Technol. 2018 Sep;5(9):866–9.

Rashid M, Bari BS, Yusup Y, Kamaruddin MA, Khan N. A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction. IEEE Access. 2021 Apr 22;9:63406–39.

Marino R, Wisultschew C, Otero A, Lanza-Gutierrez JM, Portilla J, de la Torre E. A machine-learning-based distributed system for fault diagnosis with scalable detection quality in industrial IoT. IEEE Internet of Things Journal. 2020 Sep 23;8(6):4339–52.


Refbacks

  • There are currently no refbacks.