AeroNeuro-GlobalNet: Leveraging LEO Satellite Constellations and 5G/6G Networks for Real- Time Emotional Monitoring of Transport Operators

In the pursuit of enhanced transport safety, the integration of advanced Low Earth Orbit (LEO) satellite constellations with next-generation 5G and 6G networks presents a transformative solution for real-time monitoring of emotional states in high-risk transport operators, including truck drivers and airplane pilots. This study introduces AeroNeuro-GlobalNet, a pioneering approach that leverages deep learning architectures, specifically a multi-head attention based long short-term memory (MHA-LSTM) model, to process and analyze EEG signals for emotion detection. The system aims to identify critical emotional states that could compromise safety, such as stress or fatigue, thus providing a novel form of preventive safety measure in the transportation sector. Utilizing the ubiquitous coverage and high-speed capabilities of integrated LEO satellite and terrestrial networks, AeroNeuro-GlobalNet ensures consistent, global monitoring capabilities, crucial for applications where traditional communication systems falter, such as remote air routes and cross-country trucking paths. This paper outlines the development and implementation of the emotion detection system, addresses the challenges of real-time data processing and privacy concerns, and discusses the system's integration with existing transport communication infrastructures. By facilitating continuous monitoring and immediate response capabilities, AeroNeuro-GlobalNet aims to prevent potential accidents and enhance the overall safety of transport operations, reflecting a significant step forward in the application of AI and satellite technology in critical real-world applications. The proposed framework not only enhances transport safety but also sets a foundation for future research in the integration of biometric monitoring technologies with global network infrastructures, offering a scalable solution to a wide array of safety-critical applications in various sectors.