Smart Farming 2.0: IoT and Edge AI for Precision Crop Management and Sustainability

Topic Information

Dear Colleagues,

To design and implement an edge AI-enabled IoT framework that enables the precise, real-time monitoring and management of crop health, optimizing resource efficiency and advancing sustainable agricultural practices across diverse environments. 

This interdisciplinary research will accomplish the following objectives:

1. Technology Development

- Create low-cost IoT sensor nodes with edge computing capabilities to collect and process multispectral, soil, and environmental data locally, minimizing cloud dependency. 
- Develop lightweight machine learning models for decentralized anomaly detection, disease prediction, and nutrient deficiency identification.

2. Application and Scalability

- Test the system across varied crops (e.g., cereals, horticulture) and geographies (arid, tropical) to ensure adaptability.
- Integrate with existing farming practices, such as irrigation systems and drone-based monitoring, for seamless adoption.

3. Socioeconomic Impact

- Evaluate reductions in chemical/water usage, yield improvements, and cost savings for small-scale farmers.
- Partner with agricultural cooperatives to assess barriers to technology adoption and co-design user-friendly interfaces.

4. Sustainability Metrics

- Quantify environmental benefits (e.g., carbon footprint reduction, soil health preservation) and align outcomes with UN Sustainable Development Goals (SDGs 2, 12, 13).

Why It Is Novel and Relevant

- Multi-disciplinary fusion: combines agronomy, edge AI, IoT, and socioeconomics to address food security and climate resilience.
- Edge-first innovation: prioritizes decentralized, energy-efficient computing to empower rural and resource-limited settings.
- Real-world impact: bridges the gap between cutting-edge tech and practical farming needs, fostering equitable access to precision agriculture.

Dr. Chiang Liang Kok
Dr. Teck Kheng Lee
Dr. Howard Tang
Prof. Dr. Fanyi Meng
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Electronics electronics	2.6	5.3	2012	16.4 Days	CHF 2400	Submit
IoT IoT	-	8.5	2020	27.8 Days	CHF 1200	Submit
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400	Submit
AgriEngineering agriengineering	3.0	4.7	2019	21.8 Days	CHF 1600	Submit
AI Sensors aisens	-	-	2025	15.0 days *	CHF 1000	Submit

* Median value for all MDPI journals in the second half of 2024.

Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.

MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:

1. Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
2. Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
3. Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
4. Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
5. Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers