Submitted by admin on Wed, 08/10/2022 - 23:26

Lack of passenger analytics to manage airport passenger flow

Sequence Number 1 Industry Airports & Airlines Banner Lack of passenger analytics to manage airport passenger flow How 5G enabled

Utilising cameras enabled with Machine Vision (AI) developments to provide oversight of traffic flow at any given time and make proactive real-time decisions.

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 (temp / flow / 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) will analyse images in real-time (5G) for direct action to be taken 🡪 Do this for critical areas
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
Title Inform Decision Makers Icon Inform Decision Makers Description
  • Exploit XR to display passenger analytics
Title Support Decision Making Icon Support Decision Making Description
  • End of process
Application Logic
Description
  • Personal data privacy and protection is to be considered when collecting, analysing, and viewing data.
  • Assume that real-time is the norm which means that direct intervention is possible.
  • In addition to passenger data, collect data such as temperature, flow, etc.
  • Get access to as much data as possible from different sources to get improved quality of decisions.
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.
  • Focus will be at MV, however ML is required for analytics of other data types.
Description
  • MV and ML models can be developed to provide insights such as traffic flow, age ranges, transit times, waiting times, anticipated events, weather, etc.🡪 Predict the flows of passengers at the airport + impact of measures to be taken.
  • Most of the time series data are likely not time critical, therefore the data will be cloud-based.
  • All data will be stored in Enterprise data storage, provided as needed, for AI applications.
Expected benefits Key value created