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Everybody Counts in Public Transport 
Improve decision making, optimise services and increase customer satisfaction 
M2M I...
Public Safety 
Traffic Management 
Energy Management 
Water Management 
Tram 
Train 
Subway 
People / Passenger Counting 
...
People Counting Applications 
•Transportation 
–Route optimisation 
–Schedule modification 
–Customer information and beha...
People Counting Applications 
•Optimise service provision 
–Allow dynamic allocation of resources to meet customer demands...
Creating Competitive Advantage 
•Service delivery needs to be flexible 
–Too much capacity = Satisfied customer but wasted...
Creating Competitive Advantage 
•Informed passengers are happy customers 
–Advance information on occupancy of approaching...
Usage based solutions Service when it is needed, where it is needed 
Zone 1 counter 
Zone 2 counter 
Historical usage data...
Why count on a continuous basis ? Is an asset really needed ? 
•This graph shows hourly plots of visits to a restroom at a...
Why count on a continuous basis ? When is service needed ? 
•Results of a three week study on a second restroom 
•Over 1,0...
Why count on a continuous basis ? 
When is service needed ? 
diff 200 
wk 2 
Average of time diff 50 wkday 
cleaner visits...
Why do we get such weekly differences ? Archive data analysis gives the ‘why’, so we can plan the ‘what if’ 
•Correlation ...
Smart City 
Smart Building 
Public Safety 
Traffic Management 
Energy Management 
Bus 
Water Management 
Public Health 
Tr...
The Basic Formula for IoT 
Implementing a full “M2M Software Stack” 
People counting is one particular instance of the use...
Vertical Market Example Use Case 
Use Case: Tram Fleet Management Optimization 
Application: 
The customer, a transportati...
Vertical Market Example Use Case 
Use Case: Train & Bus Fleet Management Optimization 
Application: 
The customer, a trans...
Vertical Market Example Use Case 
Use Case: Train & Bus Fleet Management Optimization 
Application: 
The customer, a trans...
Vertical Market Example Use Case 
Use Case: Bus Fleet Management Optimization 
Application: 
The customer, a transportatio...
Vertical Market Example Use Case 
Use Case: Taxi Queue Optimization 
Application: 
The customer was looking for a solution...
Optimizing & Improving Sanitary Services 
Optimizing & Improving Sanitary Services 
Application: 
The customer was looking...
Vertical Market Example Use Case 
Use Case: Airport Passenger Counting 
Application: 
In an Italian airport a passenger co...
Vertical Market Example Use Case 
Use Case: Retail Shop Performance Measurement 
Application: 
The customer was looking fo...
Vertical Market Example Use Case 
Use Case: Tourist Traffic Monitoring 
Application: 
The customer, the city of Venice req...
Vertical Market Example Use Case 
Use Case: Cruise Ship Passenger Counting 
Application: 
On an Italian cruise ship a pass...
www.eurotech.com 
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Everybody counts in Public Transport

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People and Passenger Counting M2M Applications for improving decision making, optimise services and increase customer satisfaction

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Everybody counts in Public Transport

  1. 1. Everybody Counts in Public Transport Improve decision making, optimise services and increase customer satisfaction M2M Innovation World Congress Marseille, September 2014
  2. 2. Public Safety Traffic Management Energy Management Water Management Tram Train Subway People / Passenger Counting Many Use Cases
  3. 3. People Counting Applications •Transportation –Route optimisation –Schedule modification –Customer information and behaviour modification –Fraud prevention and revenue protection –Regulatory compliance •Retail –Foot fall analysis to monitor sales promotions or merchandising –Deployment of staff to meet customer demand •Facilities Management –Smart energy planning –Service schedule optimisation –Compliance to building safety regulations •Tourism –Visitor numbers and queue management Why count people ?
  4. 4. People Counting Applications •Optimise service provision –Allow dynamic allocation of resources to meet customer demands •Enhance customer experience and refine customer behaviour –Encourage use of less busy assets or services –Optimise people flows in and out of assets •Reduce operating costs –Service assets based on usage rather than fixed schedules •Reduce liabilities –Evidence compliance with eg building fire regulations Why count people ?
  5. 5. Creating Competitive Advantage •Service delivery needs to be flexible –Too much capacity = Satisfied customer but wasted resources –Too little capacity = Dissatisfied customer, lost revenues, lost market share –Organisations need to balance the availability of fixed and flexible resources to meet customer needs. •Combining historical and real time people counts with other data (eg weather, arena schedules) allows for prediction of near term demand and a reduction in ‘exceptional’ events •Continuous monitoring of real time data allows organisation to react to exceptional events when they do occur •Integration with ticketing data –Allows for fraud detection and revenue protection •Integration with HVAC –Balance energy costs with demand •Integration with other transport modes –Focus on customer end to end journey optimisation Integrate with other information to create knowledge
  6. 6. Creating Competitive Advantage •Informed passengers are happy customers –Advance information on occupancy of approaching buses and trains, car park capacity, length of wait at taxi ranks/check-in queues etc. allows passengers to plan their journeys more effectively. –Opportunity to offer compensatory ‘coffee voucher’ when services are disrupted, at the point of disruption –Opportunity to modify customer behaviour to better balance demand –Increase brand loyalty •Smart buildings –Modify heating and cooling in advance of room occupancy –Detected unused conference rooms –Check on room capacity violations –Move to usage based facilities management rather than time based –Repurpose underutilised spaces Integrate with other information to create knowledge
  7. 7. Usage based solutions Service when it is needed, where it is needed Zone 1 counter Zone 2 counter Historical usage data available for offline analysis, eg… •What are the patterns of use ? •How many staff/vehicles do we need, and when ? •Which assets are used most – would better signage/timetabling/routing level usage ? Real-Time alerts, eg…… •Number of users exceeded threshold since last service operation •Time elapsed since last service exceeded threshold •‘request service’ button pressed M2M Integration Platform @ ? Edge gateway
  8. 8. Why count on a continuous basis ? Is an asset really needed ? •This graph shows hourly plots of visits to a restroom at a major European hub airport, collected remotely from a single counter via cellular connection. •Average daily visitors is 502, average hourly just under 21 •Peak use is in mid afternoon to early evening, but even then is only around 50-60 per hour, weekend use is higher than midweek. 0 10 20 30 40 50 60 70 Date/hour 20-15 20-18 20-21 21-0 21-3 21-6 21-9 21-12 21-15 21-18 21-21 22-0 22-3 22-6 22-9 22-12 22-15 22-18 22-21 23-0 23-3 23-6 23-9 23-12 23-15 23-18 23-21 24-0 24-3 24-6 24-9 24-12 24-15 24-18 24-21 25-0 25-3 25-6 25-9 25-12 25-15 25-18 25-21 26-0 26-3 26-6 26-9 26-12 26-15 26-18 26-21 27-0 27-3 27-6 27-9 Usage Day-Hour Hourly usage
  9. 9. Why count on a continuous basis ? When is service needed ? •Results of a three week study on a second restroom •Over 1,000 visits per day, but significant variations 0 500 1000 1500 2000 1:1:0 1:1:16 1:2:8 1:3:0 1:3:16 1:4:8 1:5:0 1:5:16 1:6:8 1:7:0 1:7:16 2:1:8 2:2:0 2:2:16 2:3:8 2:4:0 2:4:16 2:5:8 2:6:0 2:6:16 2:7:8 3:1:0 3:1:16 3:2:8 3:3:0 3:3:16 3:4:8 3:5:0 3:5:16 3:6:8 3:7:0 3:7:16 Cumulative daily visits cumul
  10. 10. Why count on a continuous basis ? When is service needed ? diff 200 wk 2 Average of time diff 50 wkday cleaner visits Monday Tuesday Wednesday Thursday Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday Saturday Sunday 1 08:55:14 08:36:47 08:58:22 09:05:25 09:04:16 09:12:15 07:29:35 08:55:14 08:36:47 08:58:22 09:05:25 09:04:16 09:12:15 07:29:35 2 02:02:24 03:07:02 03:07:31 02:36:36 02:58:48 02:32:29 03:02:28 10:57:38 11:43:49 12:05:53 11:42:01 12:03:04 11:44:44 10:32:03 3 01:46:05 02:33:45 02:56:31 02:17:40 02:44:28 01:40:22 02:35:25 12:43:43 14:17:34 15:02:24 13:59:41 14:47:32 13:25:06 13:07:28 4 02:31:33 02:57:23 03:52:27 02:55:23 03:18:12 01:28:29 02:34:15 15:15:16 17:14:57 18:54:51 16:55:04 18:05:44 14:53:35 15:41:43 5 03:39:46 04:00:50 03:04:43 01:20:09 03:18:05 18:55:02 21:15:47 00:00:00 19:59:47 00:00:00 16:13:44 18:59:48 6 01:26:11 00:00:00 00:00:00 00:00:00 17:39:55 00:00:00 7 01:48:20 19:28:15 8 03:02:00 22:30:15 00:00:00 If we assume a service every 200 visits, then the schedules look like this : diff 200 wk 1 Average of time diff 50 wkday cleaner visits Monday Tuesday Wednesday Thursday Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday Saturday Sunday 1 08:32:31 08:12:59 08:56:24 09:15:57 09:17:34 08:32:40 08:47:48 08:32:31 08:12:59 08:56:24 09:15:57 09:17:34 08:32:40 08:47:48 2 02:52:26 03:09:20 03:03:44 03:17:24 02:48:25 02:35:24 02:51:09 11:24:57 11:22:19 12:00:08 12:33:21 12:05:59 11:08:04 11:38:57 3 02:09:31 02:47:35 03:18:59 03:32:21 02:29:19 02:48:10 01:56:04 13:34:28 14:09:54 15:19:07 16:05:42 14:35:18 13:56:14 13:35:01 4 03:13:37 03:14:33 04:15:07 04:10:03 03:06:12 03:04:27 02:50:37 16:48:05 17:24:27 19:34:14 20:15:45 17:41:30 17:00:41 16:25:38 5 05:10:33 03:08:34 00:00:00 00:00:00 00:00:00 00:00:00 00:00:00 22:11:14 19:34:12 00:00:00 00:00:00 diff 200 wk 3 Average of time diff 50 wkday cleaner visits Monday Tuesday Wednesday Thursday Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday Saturday Sunday 1 08:31:29 08:51:40 08:37:41 06:23:44 08:04:03 08:38:09 09:01:12 08:31:29 08:51:40 08:37:41 06:23:44 08:04:03 08:38:09 09:01:12 2 02:25:35 02:34:48 02:08:59 02:50:42 02:50:06 02:28:27 03:10:30 10:57:04 11:26:28 10:46:40 09:14:26 10:54:09 11:06:36 12:11:42 3 02:09:47 02:13:35 02:14:49 02:07:37 02:18:07 02:19:19 02:46:00 13:06:51 13:40:03 13:01:29 11:22:03 13:12:16 13:25:55 14:57:42 4 02:28:47 02:42:15 01:56:05 01:56:24 02:14:20 03:04:28 02:37:02 15:35:38 16:22:18 14:57:34 13:18:27 15:26:36 16:30:23 17:34:44 5 03:06:58 04:16:47 01:47:57 01:56:25 02:28:38 04:43:01 18:42:36 20:39:05 16:45:31 15:14:52 17:55:14 21:13:24 00:00:00 6 01:52:13 02:10:13 00:00:00 00:00:00 18:37:44 17:25:05 00:00:00 00:00:00 7 02:22:37 03:00:13 21:00:21 20:25:18 00:00:00 00:00:00 There are significant differences day to day and week to week – real time monitoring is crucial when moving to a usage based model if we are to balance our fixed and flexible workforces
  11. 11. Why do we get such weekly differences ? Archive data analysis gives the ‘why’, so we can plan the ‘what if’ •Correlation with gate allocations ? •Correlation with public holidays ? •Correlation with local sport / business events ? •Correlation with other assets out of service ? •Correlation with flight schedule changes ? •Correlation with restaurant menus ? If you can work out the dependencies, then you can optimise ! 1 0,0 20,0 40,0 60,0 80,0 100,0 120,0 0 2 4 6 8 10 12 14 16 18 20 22 1 2 3 4 5 6 7 1 0,0 50,0 100,0 150,0 200,0 0 3 6 9 12 15 18 21 1 2 3 4 5 6 7 1 0,0 50,0 100,0 150,0 0 3 6 9 12 15 18 21 1 2 3 4 5 6 7 WK 1 WK 2 WK 3
  12. 12. Smart City Smart Building Public Safety Traffic Management Energy Management Bus Water Management Public Health Tram Train Metro Subway Remote Monitoring Fitness Machines The Internet of Things M2M Applications Everywhere Logistics Medical Transportation Public Transport Rail Metering Air Conditions Elderly Living Waste Management Value Transport Smart City Environmental Smart Grid First Responders Green Houses Sports Medical Application Cool Chain Monitoring Vending Reverse Vending Industrial Ticketing Smart Buildings Irrigation Signage Automatic Vehicle Location Remote Monitoring Retail Energy Monitoring Medical Elderly Living Green Houses Cool Chain Monitoring Agriculture Retail
  13. 13. The Basic Formula for IoT Implementing a full “M2M Software Stack” People counting is one particular instance of the use of Eurotechs M2M integration platform, the Everyware Cloud. It acts as an intermediate system between distributed devices and the applications interacting with them, abstracting the detail of the underlying protocols and communications architecture. Everyware Cloud is conceptually like an Operating System for the Internet of Things, enabling the transfer of device data to and from Enterprise applications independently of any other language, platform or OS Once this architecture is in place, it can be used to enable practically any type of remote sensor or system to interact with enterprise applications and other stakeholders @ Enterprise Service Bus for M2M Device Data Integration Platform •Data Management •Device Management •Data Storage •Real-Time Data Delivery •Real-Time Analytics •Archive data via REST APIs •Rule based event triggers •Publish & Subscribe •Secure •Scalable Everyware Software Framework •JAVA based application framework •Device Management •Connectivity Management •Application Management •Field data acquisition •Available on Eurotech and for third party hardware Devices, Sensors, Legacy systems Enterprise Applications
  14. 14. Vertical Market Example Use Case Use Case: Tram Fleet Management Optimization Application: The customer, a transportation company based in Italy (Tramvie Venete Bergamasche (TEB), Bergamo,), wanted to accomplish a fleet management optimization by tuning the time table with particular attention to school students fluxes. The solution consists of providing several trams with Eurotech’s Passenger Counters and one DynaCOR per vehicle. This combination enables passenger counting with associated GPS positioning, doors opening/closing events and collection of other information with regards to the route. Information is available for the customer through a web application that leverages Eurotech’s Everyware Cloud platform. Key Success Factors: PCN features & technology (e.g. stereoscopic vision) Complete set of building blocks offered Complete end-to-end solution Short development time Easily integration with web app performance, flexibility and simplicity of data treatment (storage, download, accessibility, analysis) Product: DynaCOR with PCN-1000 Passenger Counter HW / SW Development Services Support
  15. 15. Vertical Market Example Use Case Use Case: Train & Bus Fleet Management Optimization Application: The customer, a transportation company based in Italy (Trentino Transporti), wanted to accomplish a fleet management optimization (route optimization, time table optimization by gathering attendance statistics) for their train and buses . The solution is based on Eurotech’s Passenger Counters. Key Success Factors: PCN features & technology Rugged design Precision (stereoscopic vision) Flexible mounting system (adjustable angles) Protected front maintenance panel (USB) Product: PCN-1000 Passenger Counter
  16. 16. Vertical Market Example Use Case Use Case: Train & Bus Fleet Management Optimization Application: The customer, a transportation company based in Portugal, wanted to accomplish a fleet management optimization (route optimization, time table optimization by gathering attendance statistics) for their tramways and urban buses . The solution is based on Eurotech’s Passenger Counters. Key Success Factors: PCN features & technology Rugged design Precision (stereoscopic vision) Flexible mounting system (adjustable angles) Protected front maintenance panel (USB) Product: PCN-1000 Passenger Counter
  17. 17. Vertical Market Example Use Case Use Case: Bus Fleet Management Optimization Application: The customer, a transportation company based in Portugal wanted to accomplish a fleet management optimization (route optimization, time table optimization by gathering attendance statistics) for their tramways and urban buses . The solution is based on Eurotech’s Passenger Counters. Key Success Factors: PCN features & technology Rugged design Precision (stereoscopic vision) Flexible mounting system (adjustable angles) Protected front maintenance panel (USB) Product: PCN-1000 Passenger Counter
  18. 18. Vertical Market Example Use Case Use Case: Taxi Queue Optimization Application: The customer was looking for a solution that would allow him to improve the customer service and the utilization of available taxi capacity. The basic concept was to create at taxi stands queues where waiting passengers would be automatically counted. The data would then be used to automatically route the closest available taxis to the taxi stands where passengers are waiting. Key Success Factors: Short time to market due to EDC approach ESF for natively connecting PCN Simple Product: ReliGATE 50-21 with PCN-1000 Passenger Counter
  19. 19. Optimizing & Improving Sanitary Services Optimizing & Improving Sanitary Services Application: The customer was looking for a way to optimize and improve the sanitary services in public buildings. The system is used to monitor restrooms attendance in order to dispatch cleaners according to the precise needs (number of visitors) rather than on a time schedule Key Success Factors: PCN features & technology (e.g. stereoscopic vision) Complete set of building blocks offered Complete end-to-end solution Short development time performance, flexibility and simplicity of data treatment (storage, download, accessibility, analysis) Product: DynaCOR with DynaPCN-10-20 Passenger Counter HW / SW Development Services Support
  20. 20. Vertical Market Example Use Case Use Case: Airport Passenger Counting Application: In an Italian airport a passenger counting application was installed to monitor people flow at airport gates and boundaries. The system provides statistics on waiting time, level of service, gate and passport check post openings Key Success Factors: PCN features & technology Rugged design Precision (stereoscopic vision) Flexible mounting system (adjustable angles) Product: PCN-1000 Passenger Counter
  21. 21. Vertical Market Example Use Case Use Case: Retail Shop Performance Measurement Application: The customer was looking for a solution that would allow measurement of the performance of individual shops of a chain (franchising). Data is regarding people entering and leaving shops are correlated with the customer interactions including financial transactions, contracts sold or support cases worked on. Similar installations with other customers are used to provide statistics and ROI calculations on ads in magazines, TVs, radios against customer attendance and daily takings Key Success Factors: Short time to market due to EDC approach ESF for natively connecting PCN Simple Product: ReliGATE 50-21 with PCN-1000 Passenger Counter
  22. 22. Vertical Market Example Use Case Use Case: Tourist Traffic Monitoring Application: The customer, the city of Venice required a system that counts people in some of the strategic spots and embarkation platforms. The system collects statistics for the city’s ship public transportation service and touristic spots attendance. Key Success Factors: PCN features & technology (e.g. stereoscopic vision) Complete set of building blocks offered Complete end-to-end solution Short development time Easily integration with web app performance, flexibility and simplicity of data treatment (storage, download, accessibility, analysis) Product: DynaCOR with PCN-1000 Passenger Counter HW / SW Development Services Support
  23. 23. Vertical Market Example Use Case Use Case: Cruise Ship Passenger Counting Application: On an Italian cruise ship a passenger counting application was installed to count the passengers getting on and off the ship when visiting ports. This application is used to double-check the number of people on-board. The solution is based on Eurotech’s Passenger Counters. Key Success Factors: PCN features & technology Rugged design Precision (stereoscopic vision) Flexible mounting system (adjustable angles) Protected front maintenance panel (USB) Product: PCN-1000 Passenger Counter
  24. 24. www.eurotech.com Thank You!

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