Table 4.
Classification of IoE enablers of a specific industry domain application [114], according to IoE proposed taxonomy characteristics.
| Category/Dimension | Characteristics of an industry domain application (on-shelf availability application [152]) | |
|---|---|---|
| Knowledge | Explicitness |
Tacit: shoppers’ experience, staff experience | Explicit: enterprise point of sale (POS) systems and inventory systems | Implicit: algorithm and models from learning systems |
| Structure | Structured: enterprise data| Semi-structured: weather data, local events, and promotion details | Unstructured: real-time sensor data | |
| Trust | Trustful: data from enterprise systems | Untrustful: real-time data from shoppers’ sensors | |
| Outcome | Complements: Recommended action plans | Substitutes: predictive analytics to provide insights | |
| Action | Automation: stock business processes | Transformation: insights into buyers’ behavior | |
| Type | Presentation | Cyber: predictive analytics algorithm | Physical: cameras, shoppers, staff of the store, light, infra-red, and RFID sensors | Cyber-Physical: point of sale (POS) systems |
| Nature | Electronic-based: video cameras, light, infra-red, and RFID sensors | Software-based: point of sale (POS) systems | Human-based: shoppers, the staff of the store | Non-human-based: shoppers’ pets | |
| Use | Wearables: shoppers’ mobile devices | Surroundables: video cameras, infra-red sensors | Embeddable: light, RFID sensors | |
| Role | Sensor: video cameras, light, infra-red, and RFID sensors, shoppers, the staff of the store | Actuator: staff of the store who restock products or actuators to rectify problems | sensor, and actuator: staff of the store who senses and executes recommended actions | |
| Engagement | Opportunistic: shoppers | Participatory: shoppers/staff of the store | |
| Observation | Location | Coarse-grained: supply chain context | Fine-grained: store environment |
| Reach | Full: supply chain context Partial: physical store environment | |
| Mobility | Fixed: inside the store supply chain context | Mobile: shoppers’ mobile devices | |
| Time | Pull: meta-data produced and sent to the cloud | Push: forecast demands provided by systems | |
| Mode | Sense: store sensor devices | Derive: information derived from sensors |Manually provided: data provides from shoppers’ demand | |
| Capabilities | Communication | Conceptual communication: supports the execution of recommended actions and provides a novel shopping experience |
| Processing | Cloud: metadata produced | Fog/Edge: Edge: video streams processed locally | Mobile cloud: mobile devices from shoppers | |
| Storage | Device-level: processing video streams locally | Network level | Cluster level: metadata produced is sent to the cloud | |