My research interests focus on the QoS of wireless and mobile networks. Technologies such as 5G and Industry 5.0 introduce new research challenges in terms of optimisation, quality of service, privacy and artificial intelligence applications.
Digital Twin is an intelligent and constantly evolving system that emphasizes the high-fidelity virtual model of the physical object. Digital Twins are closely involved in the development of Industry 4.0 and Industry 5.0. Artificial Intelligence techniques are needed to optimise the data treatment that will be used and transmitted to the digital twins’ systems, this data is mostly transmitted by wireless network technologies such as 4G, 5G, LoraWan etc.
Intelligent systems need the aforementioned fields to work together. In order to perform this complicated task, several research challenges have been identified in terms of data optimisation, digital twins modelling, privacy and quality of service.
Delay Tolerant Networks are used in scenarios where no coverage areas have intermittent gateway presence. In the case where a ship is located in a sea isolated area, sensors do not stop collecting ocean information; however, the transmission will not be done until a gateway presence is detected. In these scenarios real-time transmissions are not needed. For this scenario LoRaWAN Communications has already been proposed.
Since the LoRAWAN approach seems to be the best option for having a delay-tolerant maritime mesh network, this solution needs to perform a multi-hop transmission until packets get to a 5G gateway. Unfortunately, LoRaWAN does not support multi-hop routing; therefore, using 100% LoRaWAN nodes is not a plug and play solution.
Therefore, this project focuses on testing routing solutions for LoRAWAN transmission applied to coastal scenarios.
This project is carried out in collaboration with La Rochelle University.