The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies
Abstract
This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs.
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Citations
Cites
1 retracted
Leng, K., Bi, Y., Jing, L., Fu, H.-C., & Van Nieuwenhuyse, I. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.04.061 · Cited by 397
RetractedInternet of Things: A Survey on Enabling Technologies, Protocols, and Applications
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2444095 · Cited by 8,630
Fog computing and its role in the internet of things
Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012) · Proceedings of the first edition of the MCC workshop on Mobile cloud computing · doi:10.1145/2342509.2342513 · Cited by 6,244
The Constrained Application Protocol (CoAP)
Shelby, Z., Hartke, K., & Bormann, C. (2014) · doi:10.17487/rfc7252 · Cited by 2,605 · cited 1×
“[229] IoT-based smart agriculture monitoring system - GPS - Sensors: soil moisture, temperature, PIR - Actuator: buzzer, relay - GSM - Wi-Fi N/A N/A - Android application for monitoring and control (+) Sensors and microcontroller interfaced successfully (–) Service layer (Cloud, AI, etc.”
MethodBlockchain-based traceability in Agri-Food supply chain management: A practical implementation
Caro, M. P., Ali, M. S., Vecchio, M., & Giaffreda, R. (2018) · 2018 IoT Vertical and Topical Summit on Agriculture - Tuscany (IOT Tuscany) · doi:10.1109/iot-tuscany.2018.8373021 · Cited by 861
How blockchain improves the supply chain: Case study alimentary supply chain
Casado-Vara, R., Prieto, J., la Prieta, F. D., & Corchado, J. M. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2018.07.193 · Cited by 450
Makhdoom, I., Zhou, I., Abolhasan, M., Lipman, J., & Ni, W. (2020) · Computers & Security · doi:10.1016/j.cose.2019.101653 · Cited by 325
Fast implementation of real-time fruit detection in apple orchards using deep learning
Kang, H., & Chen, C. (2020) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2019.105108 · Cited by 243
Cited by
Enhancing smart farming through the applications of Agriculture 4.0 technologies
Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2022) · International Journal of Intelligent Networks · doi:10.1016/j.ijin.2022.09.004 · Cited by 573
IoT-Enabled Smart Agriculture: Architecture, Applications, and Challenges
Quy, V. K., Hau, N. V., Anh, D. V., Quy, N. M., Ban, N. T., Lanza, S., Randazzo, G., & Muzirafuti, A. (2022) · Applied Sciences · doi:10.3390/app12073396 · Cited by 458
Deep Learning-Based Intrusion Detection for Distributed Denial of Service Attack in Agriculture 4.0
Ferrag, M. A., Shu, L., Djallel, H., & Choo, K.-K. R. (2021) · Electronics · doi:10.3390/electronics10111257 · Cited by 253
Self-citationA Systematic Survey on the Role of Cloud, Fog, and Edge Computing Combination in Smart Agriculture
Kalyani, Y., & Collier, R. (2021) · Sensors · doi:10.3390/s21175922 · Cited by 228
Detecting Vulnerability on IoT Device Firmware: A Survey
Feng, X., Zhu, X., Han, Q.-L., Zhou, W., Wen, S., & Xiang, Y. (2023) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2022.105860 · Cited by 185
Metadata
- Authors
- Friha, O., Ferrag, M. A., Shu, L., Maglaras, L., & Wang, X.
- Venue
- IEEE/CAA Journal of Automatica Sinica
- Published
- 2021-04
- Volume
- 8
- Issue
- 4
- Pages
- 718-752
- ISSN
- 2329-9266 (ISSN-L)
- 2329-9274
- OpenAlex
- W3138616181
- Cited by
- 633
- References
- 8
- FWCI
- 56.39
- Type
- journal article
- Language
- en
- Open access
- closed
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- Friha, O., Ferrag, M. A., Shu, L., Maglaras, L., & Wang, X. (2021). Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies. IEEE/CAA Journal of Automatica Sinica. https://doi.org/10.1109/jas.2021.1003925
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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