Blockchain-Based Crop Recommendation System for Precision Farming in IoT Environment

Author:

Patel Devangi Hitenkumar1,Shah Kamya Premal1,Gupta Rajesh1,Jadav Nilesh Kumar1ORCID,Tanwar Sudeep1ORCID,Neagu Bogdan Constantin2ORCID,Attila Simo3ORCID,Alqahtani Fayez4ORCID,Tolba Amr5ORCID

Affiliation:

1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India

2. Power Engineering Department, Gheorghe Asachi Technical University of Iasi, 700050 Iasi, Romania

3. Power Systems Department, Politehnica University Timisoara, 300223 Timisoara, Romania

4. Software Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 11437, Saudi Arabia

5. Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia

Abstract

In agriculture, soil is a vital element that decides the quality and yield of agricultural produce. Soil consists of various nutrients such as nitrogen (N), phosphorous (P), potassium (K), the potential of hydrogen (pH), and water content. Nitrogen is responsible for building chlorophyll, which helps produce proteins and thus directly contributes to plant growth and development. Phosphorous is needed to develop root systems and flowers, whereas potassium helps increase disease resistance. Each of these play a role in crop cultivation. Thus, in this research paper, considering the fact that soil health will provide farmers with the best selection of crops that are compatible with their farm’s soil nutrients, we propose an algorithm for recommending a set of suitable crops based on various soil attributes. These soil nutrients can be collected in real-time using soil sensors, such as N, P, K, and pH, and humidity sensors. They can be deployed in farms where the cultivation takes place. These sensor readings would then be transferred to the blockchain layer, thereby validating the data and ensuring it is tamper-proof and evident. The crop recommendation model uses data from these sensors in real-time, increasing the results’ accuracy. The last stage leads us to display these results via a user dashboard, which helps the farmers to keep in check with their farm’s practices, and their sensor states from remote locations.

Funder

King Saud University

Publisher

MDPI AG

Subject

Agronomy and Crop Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Hyperledger Fabric in Precision Agriculture: A Study on Data Integrity and Availability;2024 International Conference on Computer, Information and Telecommunication Systems (CITS);2024-07-17

2. The New Agricultural Revolution;Advances in Business Strategy and Competitive Advantage;2024-06-30

3. Comprehensive Analysis of Artificial Intelligence based Crop Recommendation and Soil Analysis;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17

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