Submitted by admin on Thu, 08/18/2022 - 00:41

Inefficient delivery process and resource planning

Sequence Number 2 Industry Logistics Banner Inefficient delivery process and resource planning How 5G enabled

Use of multiple sensors to track packages and delivery trucks in real time, using AI/ML, to optimise for prioritisation.

Data Flows
Title Devices Icon Devices Description
  • Sensors (own and third-party) deployed to track delivery vehicles, routes, weather, ESG, traffic and conditions of packages and temperature
Title Connectivity Icon Connectivity Description
  • Data transmitted to edge and enterprise storage
Title Edge Compute Icon Edge Compute Description
  • Not time critical at present, however this is expected to change in the future
Title Cloud Compute & Storage Icon Cloud Compute & Storage Description
  • All data is stored in enterprise data storage, where data ownership belongs to the company
Title Applications & Services Icon Applications & Services Description
  • Non-critical MV / ML models execution
  • Most AI will be done here since initially it is not time critical but that will change over time
Title Inform Decision Makers Icon Inform Decision Makers Description
  • AI models to provide recommendations to optimise parcel distribution, driving routes, and predict need for additional resources
Title Support Decision Making Icon Support Decision Making Description
  • End of process
Application Logic
Description
  • Sensors deployed on vehicles and critical packages will provide data to track parcel from warehouse to delivery.
  • Other data should be collected such as resource availability and utilisation of all delivery centres.
  • Environmental requirements such as temperature of the goods.
  • Collect HSSE-related data.
Description
  • Data collected will provide views such as:
  • Ed-to-end delivery time
  • Conditions of packages in transit,
  • Utilisation of vehicles (vehicle usage and storage capacity of vehicle)
  • Delivery centre utilisation
  • AI (ML) model developed by SME and data scientists as a team to provide insights and recommendations.
Description
  • AI Models could provide various recommendations based on historical data collected, such as:
  • Changes in parcel route in distribution centres
  • Driver routes and vehicle utilisation changes for optimum efficiency
  • Predict resource needs (vehicles, drivers) during seasonal periods and act accordingly
  • Changes due to traffic
  • Company rules around traffic (such as for FEDEX, no left turns in the route)
Expected benefits Key value created