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Special Issue Editors

Dr. Dae-Hyun Jung

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Guest Editor

Department of Smart Farm Science, Kyung Hee University, Giheung-gu, Yongin-si 17104, Republic of Korea
Interests: agricultural engineering; smart farming; AI in agriculture; IoT in agriculture

Dr. WooJae Cho

E-Mail Website
Guest Editor

Division of Agro-System Engineering, College of Agriculture and Life Science, Gyeongsang National University, Jinju 52828, Republic of Korea
Interests: smart farming

Special Issue Information

Dear Colleagues,

The advent of the Internet of Things (IoT) has brought about a paradigm shift in various sectors, and agriculture is no exception. The integration of IoT in agriculture, often referred to as smart farming or precision agriculture, has the potential to revolutionize the way we approach farming, leading to more efficient and sustainable agricultural practices.

This Special Issue delves into the topic of the Internet of Things (IoT) in agriculture, focusing on its rationale, current state, and evolution. The integration of IoT in agriculture, or smart farming, is driven by the need to increase food production efficiency and sustainability. Current applications include sensor networks for real-time monitoring, automated systems, and data-driven decision-making. The evolution of IoT in agriculture is an ongoing process, with emerging sophisticated solutions and convergence with technologies such as AI, blockchain, and 5G. Despite progress, challenges such as high costs, data privacy, lack of standardization, and the digital divide persist. This Special Issue invites contributions exploring innovative IoT technologies, applications, strategies, and future directions in smart farming that aim to advance sustainable farming systems for the future.

Dr. Dae-Hyun Jung
Dr. WooJae Cho
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Internet of Things (IoT) in agriculture
sensor networks in agriculture
smart farming
data-driven decision making
AI-driven problem solving for agriculture systems
machine learning and deep learning
blockchain and 5G technology in smart farming

Published Papers (2 papers)

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Research

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15 pages, 1656 KiB

Open AccessArticle

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

by Devangi Hitenkumar Patel, Kamya Premal Shah, Rajesh Gupta, Nilesh Kumar Jadav, Sudeep Tanwar, Bogdan Constantin Neagu, Simo Attila, Fayez Alqahtani and Amr Tolba

Agronomy 2023, 13(10), 2642; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy13102642 - 19 Oct 2023

Viewed by 1380

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. Full article

(This article belongs to the Special Issue IoT in Agriculture: Rationale, State of the Art and Evolution)

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Other

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10 pages, 501 KiB

Open AccessPerspective

Achieving the Rewards of Smart Agriculture

by Jian Zhang, Dawn Trautman, Yingnan Liu, Chunguang Bi, Wei Chen, Lijun Ou and Randy Goebel

Agronomy 2024, 14(3), 452; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy14030452 - 24 Feb 2024

Viewed by 886

Abstract

From connected sensors in soils, on animals or crops, and on drones, to various software and services that are available, “smart” technologies are changing the way farming is carried out. These technologies allow producers to look beyond what the eye can see by collecting non-traditional data and then using analytics tools to improve both food sustainability and profitability. “Smart Agriculture/farming” (SA) or “Digital Agriculture” (DA), often used interchangeably, refer to precision agriculture that is thus connected in a network of sensing and acting. It is a concept that employs modern information technologies, precision climate information, and crop/livestock developmental information to connect production variables to increase the quantity and quality of agricultural and food products. This is achieved by measuring and analyzing variables accurately, feeding the information into the cloud from edge devices, extracting trends from the various data, and subsequently providing information back to the producer in a timely manner. Smart agriculture covers many disciplines, including biology, mechanical engineering, automation, machine learning, artificial intelligence, and information technology-digital platforms. Minimum standards have been proposed for stakeholders with the aim to move toward this highly anticipated and ever-changing revolution. These foundational standards encompass the following general categories, including precise articulation of objectives, and baseline standards for the Internet of Things (IoT), including network infrastructure (e.g., stable 4G or 5G networks or a wireless local area network (WLAN) are available to end users). To sum up, SA aims to improve production efficiency, enhance the quality and quantity of agricultural products, reduce costs, and improve the environmental footprint of the industry. SA’s ecosystem should be industry self-governed and collaboratively financed. SA stakeholders and end-users’ facilities should meet standard equipment requirements, such as sensor accuracy, end data collectors, relevant industry compliant software, and trusted data analytics. The SA user is willing to be part of the SA ecosystem. This short perspective aims to summarize digital/smart agriculture concept in plain language. Full article

(This article belongs to the Special Issue IoT in Agriculture: Rationale, State of the Art and Evolution)

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