Renewable Energy Re-Distribution via Multiscale IoT for 6G-Oriented Green Highway Management

While recent works on investigating renewable energy sources for powering the highway offer promising solutions for sustainable environments, they are often impeded by unequal distribution of sources across the region due to variations in solar exposure and road intensity that electromagnetically and mechanically generate the energy. By exploiting viable gathering of massive renewable energy data using the Internet of Things (IoT), this paper proposes a framework for improved highway-energy management based on the unmanned aerial vehicle-assisted wireless energy re-distribution of the harvested renewable energy. Combining both massive low-rate sensing with high-speed 6G-envisioned transmission for data aggregation, the IoT architecture is of multi-scale, consisting of: i) global data exchange and analytics for energy mapping, re-distribution planning and forecasting, and ii) local data sensing and processing at individual highway lampposts for micro-energy management. The feasibility of the networked energy system is analyzed via analytical cost-reliability analyses. The cost analysis demonstrates the cost-effectiveness through the lowest Requirement of Energy and Cost of Energy for the setup and maintenance. The reliability analysis reveals the energy plus (E $+$ ) feature of the system in certain conditions with enhanced reliability in adverse weathers that impact energy generation. With multi-scale data connectivity to intelligently manage standalone renewable energy, this work puts forward a viable idea of 6G use cases with massively networked energy sensors with a vision of achieving super-connected and intelligence-equipped highways.