Brief Encounters. Sensing, Modeling and Visualizing Urban Mobility and Copresence Networks

Transcription

1 Brief Encounters Sensing, Modeling and Visualizing Urban Mobility and Copresence Networks Vassilis Kostakos Madeira Interactive Technologies Institute University of Madeira Eamonn O Neill 1, Alan Penn 2, George Roussos 3, Dikaios Papadongonas 3 1 University of Bath, 2 UCL, 3 Birkbeck College

2 Outline Motivation Data Collection Analysis & Visualisation Results Slide 2

3 Motivation Traditional HCI System = Computer + Human Formal descriptions of this system Models (Human processor model) Fitt s law System = Computer + Human + Location Technology is increasingly mobile Seek tools, techniques and models to describe and predict the system Slide 3

4 Data collection Slide 4

5 Scanner time Slide 5

6 Slide 6

7 Collected data 12 months unique devices unique data points Slide 7

8 Analysis & Visualisation Slide 8

9 Main concepts Sessions Trails Encounters Slide 9

10 Location 1 2 Encounter Session Scanner Location 2 Location 3 time Slide 10

11 Slide 11

12 Slide 12

13 length slope Slide 13

14 Flow of people Transient Bluetooth Activity (session < 90 sec.) City Gate University Gate Devices Hour of day Slide 14 December 15, 2009

15 B C E D A Slide 15

16 Scanner time Slide 16

17 Scanner time Slide 17

18 time Slide 18

19 Slide 19

20 Slide 20

21 Slide 21

22 Slide 22

23 Results Slide 23

24 a = 2.5 Probability of encountering more than 10 people is Slide 24

25 Presence Duration Frequency Frequency Sessions Nodes How much time people spend at a location a=1.9 How many times people visited a location a=2.6 Encounters Links How much time any two people spend together a=2.3 How often any two people meet each other a=2.7 Slide 25

26 Slide 26

27 Presence Duration Frequency Frequency Encounters Links Sessions Nodes Slide 27

28 Implications From a static observer s perspective, people s movement and encounter patterns are highly regular but different across locations A static observer may be a public display, a locationbased service, a bus stop, a shop Our model can be tuned to reflect different locations and cities Slide 28

29 Using theory... Stress-test a design by considering the frequency of people s visits the duration of their visits Quantify the differences between two locations Funchal vs. Atlanta? Slide 29

30 Using the tools... Automate observations in the wild Explore people s trails in the city What trails do couples leave on a Friday night? or groups of friends? Develop attention span interfaces posters, displays, speakers, and mobile devices adapt presentation based on visitors patterns Slide 30

31 The end Questions? Vassilis Kostakos Slide 31

32 Privacy Bluetooth can be turned off Should be turned on if there exist potential benefits Build systems that provide such benefits Each Bluetooth device has a unique hexadecimal ID Associate this ID with a person s identity VISA, RFID ticket, IMEI : stored in a database Bluetooth: not stored centrally Slide 32

33 Slide 33

34 20 Avenida - Recovery 15 Floods Devices seen Thu, Feb 18, 2010 Fri, Feb 19, 2010 Sat, Feb 20, 2010 Sun, Feb 21, 2010 Mon, Feb 22, 2010 Tue, Feb 23, 2010 Wed, Feb 24, 2010 Thu, Feb 25, 2010 Fri, Feb 26, 2010 Sat, Feb 27, 2010 Sun, Feb 28, 2010 Mon, Mar 1, 2010 Tue, Mar 2, 2010 Wed, Mar 3, 2010 Thu, Mar 4, 2010 Fri, Mar 5, 2010 Sat, Mar 6, 2010 Sun, Mar 7, 2010 Mon, Mar 8, 2010 Tue, Mar 9, 2010 Wed, Mar 10, 2010 Thu, Mar 11, 2010 Fri, Mar 12, 2010 Sat, Mar 13, 2010 Sun, Mar 14, 2010 Mon, Mar 15, 2010 Tue, Mar 16, 2010 Wed, Mar 17, 2010 Thu, Mar 18, 2010 Fri, Mar 19, 2010 Slide 34