## 4 6G Convergence with Green AI Perspective in Terrestrial and Non-Terrestrial Applications
### Application 3: Green-AI-Enabled 6G Epidemic Prevention Service  
_Definition: Green-AI-Enabled 6G Epidemic Prevention Service_, represented as _GreenAI-6G-EPreS_, is a service supported by 6G infrastructure and _Green AI_ perspective, which advocates epidemic prevention service including environmentally friendly medical item delivery, inexpensive epidemic prevention visit, suitable epidemic prevention map creation with the reduced data and the diminished number of training experiments and communications.  
_System Goal:_ For _GreenAI-6G-EPreS_, the first objective is to reduce environmentally measured factors such as carbon emission by any vehicles and over-sprayed disinfectant, which can be harmful to green circumstances including low carbon emission usage, reduced cost of data processing, reduction in spent resources and environmental hygiene. The second goal is to shorten the cost of hardware and software that can be utilized for system process and implementation for epidemic prevention and disease outbreak suppression. Lastly, the third aim is to economize the massive number of training experiments and underlying simulations for _GreenAI-6G-EPreS_.  
_Operation:_ At early stage, the environmentally friendly evaluation criterion of carbon emission, air pollution is verified as numerical values and then those values are distributed to all entities including users, AI agents, UAVs, mobile robots, autonomous vehicles and smart devices by 6G-supported communications. Furthermore, those entities identify both public area and private area. While public region is accessed by all kinds of components, private area requires only components with access permission. For medical item delivery of epidemic prevention, AI agents determine which UAVs, vehicles or mobile robots deliver light-weighted items and heavy-weighted item selectively to requested locations to fulfill environmental standard like low carbon emission, saved electricity usage. Basically, epidemic prevention visit covers non-face-to-face visit to specific locations to be served, which are supported by mobile robots on the ground side to deliver a small size of medical items. When the epidemic prevention visit by the cooperation of UAVs and mobile robots is proceeded, the environmental standard should be satisfied for carbon emission by any delivery vehicles, disinfectant sprayed by UAVs in the air. Furthermore, for contributing 6G-assisted epidemic visit tasks such as quarantine, screening test and notifications, non-contact prescriptions, the reduced expense of hardware and software is necessary. In addition, when AI agents calculate the trajectory of delivery and epidemic prevention visit, system recovery from malfunctions, the estimations and outcomes should be gained by economic number of training experiments and reduced relevant information at AI agents, not excessively massive training data sets and information for required measurement.  
Figure 5 shows the proposed applications of _GreenAI-6G-VEmoBAR_, _GreenAI-6G-VEmoFLOWMAP_, _GreenAI-6G-EPreS Green AI_ view. It aims to achieve maximum efficiency, maximum environmental protection, and minimum expense for those applications.