Submitted by admin on Wed, 08/10/2022 - 22:32

Lack of proper baggage handling

Sequence Number 3 Industry Airports & Airlines Banner Lack of proper baggage handling How 5G enabled

Knowing the locations & statuses of all luggage at an airport and being able to predict the real-time flow and arrival timings.

Data Flows
Title Devices Icon Devices Description
  • Various types of cameras at all critical locations
  • Real-time image data to be collected as well as other sensor data (belts motion, status, etc)
Title Connectivity Icon Connectivity Description
  • Images transmitted to edge and enterprise storage
  • Develop MV models driven by analytics needs
Title Edge Compute Icon Edge Compute Description
  • AI (MV) to analyse images in (5G) real-time so direct action to be taken
  • Real-time ML applied in other areas such as belts status
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
  • Automated processes by default
  • Predictive maintenance is relevant here
Title Inform Decision Makers Icon Inform Decision Makers Description
  • Report potential future failure
Title Support Decision Making Icon Support Decision Making Description
  • Predict potential bottlenecks and alternate plan for optimised flow
Application Logic
Description
  • Assume that real-time (5G) is the norm which means that direct intervention is possible.
  • In addition to passenger data, collect data such as operating temperature, belts status, rotating equipment, etc. 🡪 All inputs for predictive maintenance.
Description
  • All AI (ML and MV) models will be developed through a joint effort of SME and data scientists.
  • Development of these models will be iterative (will require time) to achieve an appropriate quality level.
  • Both MV and ML AI models will be adopted at identified critical equipment, as it provides different improvements in baggage handling:
  • Speed of the individual suite cases
  • Stability and reliability of the baggage facility set up at the airport
Description
  • MV and ML models will assist to provide alerts for predictive maintenance.
  • All data will be stored in Enterprise data storage, provided as needed for AI applications.
  • ML can also be used to perform prediction of baggage loads, enabling decisions to maximise throughput.
Expected benefits Key value created