Passenger Dwell Time Analysis at Copenhagen Airport Esben Kolind, Senior Business Analyst, Copenhagen Airports Kevin O'Sullivan Lead Engineer, SITA Lab
Agenda About Copenhagen Airports and SITA Lab Using Wi-Fi data in CPH what are the possibilities? Scoping of SITA Lab project SITA Airport Geolocation Platform Vision Technical aspects Device accuracy Zoning Path finding Using and validating Wi-Fi data Next steps 3
Copenhagen Airport (CPH) Largest airport in the Nordic countries with 22,7 million passengers in 2011 (#16 in Europe) 140 destinations served Best airport in Northern Europe 2011 Most efficient airport in Europe 2011 Europe s Best Airport Shopping Experience 2011 (125 shops and restaurants) Biggest workplace in Denmark (22.000 employees) 800 Wi-Fi access points in the terminals Free membership of CPH loyalty scheme CPH Advantage gives free Wi-Fi access
SITA Lab SITA are global supplier of IT services and products to Air Transport Industry SITA Lab is a strategic research group at SITA Mobile Technologies BIG DATA NFC Tablet devices at airport & onboard Augmented Reality Indoor Geo Location 5
Using Wi-Fi data in CPH 6
What can we do with Wi-Fi data in CPH? What routes do the passengers take through the airport? Real-time tracking Crowded areas and busy periods How does passenger behaviour change? Over the day? By season? By airline? What is the effect of new infrastructure? How much time do passengers spend in different areas? When do departing passengers show up? Combine with flight data You are in the wrong end of the airport. Go to gate now! Indoor navigation Behaviour of frequent flyers Combine with loyalty program We know you like fashion, and there is a great offer in the shop on your left right now
Initial scope of SITA Lab project Collect historical data Focus on passenger dwell times and passenger counts Different zones of the airport Passenger classification (departure/arrival/transfer) Different time periods and granularity Reporting Graphs and tables Export functionality
Business goals Increased insight into passenger behaviour Use knowledge for master planning, manning of facilities, design of processes, selection of shops etc. More data and higher accuracy lead to better analysis (and better decisions) Reduce the need for costly, manual surveys Passenger counts Questionnaires (Where have you been? How long time did you spend there?)
Initial questions Penetration How much data will we get? Accuracy 5 m? 10 m? 50 m? Accurate enough to locate a passenger in a specific gate? Shop? Even a queue? Frequency Accurate observations every 5 seconds on the entire route? Partial routes? Random, scattered observations?
Technical aspects of CPH Pilot 11
Solution Overview 3 Cisco Advanced Location Analytics Location Engine Analytics Engine 1 location data MSE Wi Fi Location Data Additional Data 2 Controllers 4 -BCBP -Bluetooth -People counts -Other data sources Access Points wireless network SITA Passenger Flow Monitoring
Device Detection
Device accuracy Example 1
Device accuracy Example 2
Device accuracy Example 3
Zone marking Example 1
Path finding
Zone marking Example 2
Using and validating Wi-Fi data 20
Reporting interface Filters Date and time Passenger types Airport zones Granularity Output Table Graphs Export
Dwell time distributions
Validation of Wi-Fi data Existing waiting time system installed at Central Security Check (CSC) Based on active bluetooth devices Records entrance and exit from security area Entry: Virtual gates Exit: Nodes installed in security doorways
Dwell times at CSC
Device counts at CSC
What s next? 26
Cisco Connected Mobile Experiences with SITA Passenger Flow Monitoring for Airports 27
Solution Overview 3 Cisco Advanced Location Analytics Location Engine Analytics Engine 1 location data MSE Wi Fi Location Data Additional Data 2 Controllers 4 -BCBP -Bluetooth -People counts -Other data sources Access Points wireless network SITA Passenger Flow Monitoring
Solution Overview Going Forward Cisco s Wi-Fi infrastructure with MSE Cisco s Advanced Location Analytics Focused on horizontal analytics, e.g. applicable to malls, urban areas, as well as airports Cisco s Mobile Concierge SITA s Airport iflow passenger flow monitoring platform Air Travel Industry Extensions to Analytics Airline Gate and Airport Security Tracking and Resource Management Interfaces to FIDS (Flight Information Display Systems) and AODB (Airport Operations Database) for flight specific statistical analysis Integration of other data sources and airport systems BCBP (Bar Code Boarding Pass) tracking, security queue times via Bluetooth, with links to FIDS and resource management (staffing) systems, as well as other 3 rd party data sources 3 rd party mobile application providers, e.g. Meridian
Which duty free region had the most traffic last week? Icon colors = number of devices per region Data rules and filters for date, time, path
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