Toward Zero-Touch Provisioning in Smart Green Agriculture Driven by Mobile Sensor Stations
Smart Green Agriculture (SGA) is currently under-going a substantial transformation facilitated by the integration of cutting-edge technologies, such as 5G, Artificial Intelligence (AI), and Internet of Things (IoT) devices, including sensors and Unmanned Vehicle Area (UAV). This integration is revolutionizing agricultural practices, making them more sustainable and efficient. For instance, sensors gather crucial data like temperature, humidity, and wind levels, while UAVs capture images and videos of crop fields. These devices can seamlessly communicate via a 5 G model, reducing the need for extensive human intervention in SGA operations. We propose a system model that harmoniously coordinates and integrates various technologies in such a case. This includes leveraging UAV and its mobility to deploy a set of sensors for gathering sensing data. Our study illustrates the potential of orchestrated in integrated systems by cooperating among computing server, UAV, sensors and human. This approach is a promising solution for zero-touch system for the next generation of green agriculture. In such a case, our study demonstrates the significance of smart green agriculture driven by mobile sensors station as a viable solution for orchestration in agriculture. It also sets the stage for further advancements at the intersection of technology and sustainable farming practices, emphasizing the pivotal role of these innovations in shaping the future of agriculture.
Authors
- Tuong Tri Nguyen (ORCID: https://orcid.org/0000-0002-1379-0131)
- S. M. Ahsan Kazmi (ORCID: https://orcid.org/0000-0001-7138-8258)
- Khang Truong (ORCID: https://orcid.org/0000-0003-2046-8367)
- Tri Nguyen Dang (ORCID: https://orcid.org/0000-0003-0188-1535)
Institutions
- University of the West of England (GB)
- Hue University (VN)
Publication Details
- Published
- 2025-01-15
- DOI
- https://doi.org/10.1109/icoin63865.2025.10992906
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00