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Smart Agriculture: Cloud Data Control Platform
This special issue belongs to the section “Precision and Digital Agriculture“.
Special Issue Information
Dear Colleagues,
Welcome to this Special Issue on “Smart Agriculture: Cloud Data Control Platform”. The agricultural sector is undergoing a profound digital transformation, driven by IoT devices, sensors, robotics, and drones that generate unprecedented volumes of agronomic data. This shift to smart agriculture promises enhanced productivity, sustainability and resource efficiency, thus turning farms into intelligent, data-enabled ecosystems capable of feeding a growing world. However, harnessing this data deluge is a significant challenge. Cloud data control platforms provide the critical infrastructure for collecting, storing, processing, and analyzing farm data in real-time. They enable automated irrigation, precise fertilizer dosing, early disease warnings, smart livestock monitoring, and predictive crop management bringing data-driven decision-making directly to the field.
This Special Issue aims to explore innovative cloud architectures, data control mechanisms and automation solutions that improve productivity and sustainability. Contributions highlighting benefits for farmers, agronomists and stakeholders (i.e., improved crop performance, soil health and reduced input waste) are encouraged. The scope includes platform design, data interoperability, real-time analytics, edge–cloud collaboration and practical applications across crop production and field-management systems.
We invite studies that showcase innovative cloud data control platforms in agriculture, integrating technologies such as machine learning (ML), remote sensing, and AI-driven decision support systems. Submissions addressing secure data traceability, agricultural dataspaces and real-time analytics that enhance productivity, sustainability, or resource efficiency are particularly encouraged. Work demonstrating practical deployment or measurable benefits in real-world agricultural settings is highly valued.
We welcome original research articles, reviews, technical reports, and case studies focusing on the design, development, and application of cloud-based platforms. Manuscripts that provide field validation, system performance evaluation, user-centric interfaces, or multidisciplinary approaches bridging ICT and agronomy are especially relevant. Contributions should illustrate how cloud platforms can convert agricultural data into actionable insights, supporting smarter, data-driven decision-making on the farm.
Dr. Mino Sportelli
Dr. Alexander Kocian
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 250 words) can be sent to the Editorial Office for assessment.
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 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 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
- precision agriculture
- crop monitoring
- soil and water management
- cloud-based data platforms
- IoT in agriculture
- real-time farm analytics
- AI-driven decision support systems
- agricultural dataspaces
- data traceability
- smart farming systems
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