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Exploring the Potential of Rural Drone Operations Centres
In the digital age, rural communities often face challenges accessing advanced technologies that can enhance productivity and modernize services. The XGain project tackles this issue head-on by developing a digital tool to support rural stakeholders with technology mix proposals and a detailed assessment for implementing their digitalized services. As part of the validation process of the technology mixes the KFT can produce, the use case implemented by i2CAT – a drone operations centre— explores how a hub where rural stakeholders can access state-of-the-art drone capabilities and digital tools could impact the local community.
This centre is envisioned as a place for training and education, where users could learn about drone operation, explore regulatory requirements, and understand how these devices can transform rural industries like agriculture and environmental monitoring. More than a learning facility, the drone operations centre would also provide testing grounds for innovative drone services, enabling local users to experiment with solutions tailored to their needs. Here, i2CAT implements a technical setup featuring a private 5G network with edge processing capacities to validate the concept of equipping drones with 5G technology for enhanced capacities.
From Concept to Reality: Design and Validation Challenges
Building a functional and robust drone centre is no small feat. One critical challenge is ensuring the technology infrastructure is up to supporting diverse drone services. To address this, the 5G Coebre Lab in Mora la Nova, Catalonia, was chosen as a testbed to validate the centre’s design. Its wide indoor space features the perfect testing and playground for a drone-based scenario. Figure 1 shows the indoor space.
Figure 1: Wide indoor space in the CoebreLab 5G for use case deployments
At the heart of the validation process of the space and the 5G technology was the creation of an end-to-end testing scenario. A typical use case was designed where a drone equipped with a camera would record video data, transmit it over a 5G network, and then process it at the edge for real-time insights. This scenario allows the replication of key elements of drone services, such as live video streaming and edge-based object detection, which are essential for crop monitoring and surveillance applications. Figure 2 shows the logical diagram with the infrastructure elements and the deployed services temporarily set up in the CoebreLab 5G for validation.
Figure 2: End-to-end validation scenario of a drone-based use case
One key challenge in designing the use case was ensuring the components could work together to provide the necessary end-to-end connectivity. For example, the drone-mounted hardware, including a video capture device and processing unit, needed to reliably transmit data over the 5G network to the edge server, where advanced applications such as real-time video analysis were hosted. Designing a flexible system required selecting versatile hardware custom-off-the-shelve equipment and integrating it to allow for easy reconfiguration or upgrades, with sufficient flexibility to adopt alternative end-to-end data flows, e.g., with different cameras or drone hardware. These considerations added complexity to the integration process but were essential for creating a robust solution and allowed the team to perform a representative testing and validation process.
One of the most important considerations during this validation process was testing the 5G network capacities for data transmission and edge processing capacities for a flying drone. Ensuring seamless connectivity required careful analysis of how to position the station to maximize performance across the entire operational area. Early tests revealed that proximity to the base station was crucial for maintaining high reliability, particularly for real-time video transmission. Even in the worst case, i.e., placing the 5G small cell far away from the drone flight area, a good performance performance consistency could be achieved with minor caveats. This insight will impact the final deployment strategy to ensure consistent performance during live operations.
Another challenge was designing a validation process to assess connectivity and computing infrastructure under realistic conditions. Testing included the transmission of high-definition video streams from the drone to an edge processing device. This allowed the team to measure how well the system could handle data-intensive tasks while maintaining low latency—a critical requirement for many drone-based applications. The results were promising, demonstrating the robustness of the infrastructure and identifying areas for further optimization.
Regarding the end-to-end service validation, a key aspect of being validated was whether the video generated in the drone and transmitted over the 5G network would reach the edge compute node without losses and minor delays and be processed there in real-time with an object detection algorithm: MOTCAM.
Laying the Groundwork for 2025
These tests mark a significant milestone in preparing for the final use case deployment in the warehouse for implementing a demonstration in front of the public audience. The results validate the technology choices made so far and highlight the importance of iterative improvements in system design. With this groundwork in place, the team is now focused on fine-tuning the setup to address the challenges identified during testing, e.g. optimizing the 5G configurations for more stability and fine-tuning the object detection software.
The final goal is to showcase the use case in 2025, demonstrating how cutting-edge technologies like 5G and edge computing could help to implement a cutting-edge drone centre. We want to show to the rural community how offering a space where stakeholders can access and test advanced tools, such a center could help to bridge the digital divide and empower rural communities with transformative capabilities.
