@@ -574,9 +574,24 @@ Synchronization of Digital Twin state between edge and cloud | Not required | o
### 6.4.7 Assisted Manoeuvring for Autonomous Ships
#### 6.4.7.1 Use case Driven Deployment
### 6.4.8 Smart Shopping with Edge-AI and Cloud-IoT Integration
### 6.4.8 Smart Metaverse Shopping with Edge-AI and Cloud-IoT Integration
#### 6.4.8.1 Use case Driven Deployment
The “Smart Metaverse Shopping” use case requires the oneM2M IN-CSE deployment in the cloud to manage IoT devices and to store data from the physical retail environment. MEC hosts an AI-powered application at the network edge, close to the store, enabling real-time interpretation of user interactions within the metaverse.
The MEC App subscribes to live data from the IN-CSE and processes it to deliver immediate, personalized feedback in the virtual shopping environment (e.g., recommendations, stock alerts). Upon purchase, the system updates the IN-CSE and triggers real-world actions such as product reservation or notifications to store staff and actuators.
Optionally, an MN-CSE may be instantiated on the MEC platform to further reduce latency and improve service continuity. This hybrid deployment ensures real-time, synchronized experiences across the digital and physical retail layers.
In the following table, we will consider all the relevant operational requirement for this use case.
##### Table 6.4.8.1-1 – Operational Requirements and Platform Support for Smart Metaverse Shopping
| Operational Requirement | Support in MEC | Support in oneM2M |
| IoT platform deployment | Not directly | Supported: oneM2M IN-CSE can be deployed at cloud
Registration of IoT devices deployed in the physical store | Not required | Supported: oneM2M enables registration of industrial sensors, actuators, controllers as either IN-AEs or ADN-AE via standardized resource structures and CSFs
Registration of IoT applications | Not required | Supported: oneM2M enables registration of industrial Applications as AEs via standardized resource structures and CSFs
Real-time data ingestion from Stores (shelf inventory levels, product locations, environmental conditions) | Not required | Supported via oneM2M’s CSF and Mca interfaces
Instantiate of MN-CSE on Edge Node (If required) | MEC provides the infrastructure to host oneM2M as a service producing MEC application using Mp1 interface. Can provide support to integrate a new MEC IoT service (MEC 0xx to be defined later) inside the MEC Platform which should be more coupled with oneM2M standards. Whereas MEC IoT API (MEC033) enables minimal registration and discovery of IoT platforms. | Supported: oneM2M platform needs to include a CSF to integrate with the MEC platform
Instantiate of AE (e.g., sensor manager, analytics & controller) on Edge Node | AE can be instantiated as MEC Application on MEC Host. It can use AI models for analysing real time data and providing feedback. Virtual Store App instantiate as an MEC application/Edge Application on MEC Host. | Supported: oneM2M platform needs to include a CSF to instantiate an AE as MEC application
Low-latency control for real time data processing | Supported: MEC Apps handle time-sensitive operations with minimal delay | Supported: MN-CSE enables fast coordination through subscriptions, notifications, and data routing
