Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.5
2.5
Journals
Applied Sciences
Special Issues
Smart Farming: Internet of Things (IoT)-Based Sustainable Agriculture
applsci-logo
Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Smart Farming: Internet of Things (IoT)-Based Sustainable Agriculture

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Agricultural Science and Technology".

Deadline for manuscript submissions: closed (10 August 2025) | Viewed by 535

Special Issue Editors

Prof. Dr. António Monteiro

E-Mail Website
Guest Editor
Agrarian School of Viseu, 3500-606 Viseu, Portugal
Interests: small ruminant production; precision agriculture; sustainable agriculture
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Svend Christensen

E-Mail Website
Guest Editor
Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Højbakkegaard Allé 9, DK 2630 Taastrup, Denmark
Interests: crop-weed competition; weed biology and management; biosystem technologies; precision agriculture

Special Issue Information

Dear Colleagues,

Smart agriculture is strongly linked to the Internet of Things (IoT), making it possible to collect data, even in real time, on various agricultural parameters. This technology enables farmers to make informed decisions to optimize resources, increase production efficiency and promote sustainable and resilient cropping systems. By integrating biodiversity and addressing climate change, IoT supports the development of agroecosystems that are both productive and environmentally sound.

The insights gained from IoT data, analyzed through artificial intelligence (AI), allow for precise resource management, prevention of pests and diseases and increased crop yields. These advancements contribute to sustainability by providing economic and environmental benefits, while also fostering ecosystems that enhance biodiversity and are better adapted to climate variability.

Supply chain management also benefits greatly from IoT, which increases transaction transparency and traceability, namely through blockchain technology. This is beneficial for the safety and quality of agricultural products, while promoting trust between stakeholders.

This Special Issue aims to explore innovative applications of IoT technology in agriculture and livestock production to promote sustainable practices, improve resource efficiency and build resilience to the challenges posed by climate change.

Prof. Dr. António Monteiro
Prof. Dr. Svend Christensen
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • smart farming
  • IoT
  • sustainable agriculture
  • precision agriculture
  • digital agriculture
  • sensors
  • automation
  • big data in agriculture
  • artificial intelligence

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 13514 KiB  
Article
Development of a High-Speed Time-Synchronized Crop Phenotyping System Based on Precision Time Protoco
by Runze Song, Haoyu Liu, Yueyang Hu, Man Zhang and Wenyi Sheng
Appl. Sci. 2025, 15(15), 8612; https://doi.org/10.3390/app15158612 - 4 Aug 2025
Viewed by 221
Abstract
Aiming to address the problems of asynchronous acquisition time of multiple sensors in the crop phenotype acquisition system and high cost of the acquisition equipment, this paper developed a low-cost crop phenotype synchronous acquisition system based on the PTP synchronization protocol, realizing the [...] Read more.
Aiming to address the problems of asynchronous acquisition time of multiple sensors in the crop phenotype acquisition system and high cost of the acquisition equipment, this paper developed a low-cost crop phenotype synchronous acquisition system based on the PTP synchronization protocol, realizing the synchronous acquisition of three types of crop data: visible light images, thermal infrared images, and laser point clouds. The paper innovatively proposed the Difference Structural Similarity Index Measure (DSSIM) index, combined with statistical indicators (average point number difference, average coordinate error), distribution characteristic indicators (Charm distance), and Hausdorff distance to characterize the stability of the system. After 72 consecutive hours of synchronization testing on the timing boards, it was verified that the root mean square error of the synchronization time for each timing board reached the ns level. The synchronous trigger acquisition time for crop parameters under time synchronization was controlled at the microsecond level. Using pepper as the crop sample, 133 consecutive acquisitions were conducted. The acquisition success rate for the three phenotypic data types of pepper samples was 100%, with a DSSIM of approximately 0.96. The average point number difference and average coordinate error were both about 3%, while the Charm distance and Hausdorff distance were only 1.14 mm and 5 mm. This system can provide hardware support for multi-parameter acquisition and data registration in the fast mobile crop phenotype platform, laying a reliable data foundation for crop growth monitoring, intelligent yield analysis, and prediction. Full article
(This article belongs to the Special Issue Smart Farming: Internet of Things (IoT)-Based Sustainable Agriculture)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop