Smartphone as a Road Sensor. Mark Shtern York University Adaptive System Research Lab

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1 Smartphone as a Road Sensor Mark Shtern mark@cse.yorku.ca York University Adaptive System Research Lab

2 Negative Factors Impacting the Driving Experience Road conditions Traffic accidents Human factor -> 93% Traffic jams Parking Scarcity Locating 2

3 Possible Avenues for Improvement Personalized notification Traffic conditions Road conditions Collision avoidance notification Intelligent route planners Traffic sensors 3

4 Existing Sensors Road traffic monitoring Cameras, Traffic light, Vehicle Counter, Traffic Speed Weather conditions Social media (?) limited to information about highways 4

5 Wish List Inexpensive maintenance Easy for mass-deployment Mobile sensor 5

6 Smartphone Several built-in sensors GPS (Position, Speed) Gyroscope Accelerometer Compass Personal device Popular device 6

7 Smartphone as a Road Sensor Road conditions assessment Adaptive route planner Personalized traffic notification Collision avoidances notification Optimization fuel consumption Parking assistance Traffic conditions 7

8 Challenges (Non-technical) User acceptance Privacy/Trust Human interaction Mobile phones and driving safety Data ownership Regulations Personal Information Protection and Electronic Documents Act Path planner on local roads Accountability 8

9 Challenges (Technical) Functional High volume of data Large number of online users (mobile devices) Real-time Human interaction Non-functional Privacy/Security Several popular incompatible smart phone models 9

10 Envisioned Smart Transportation Platform 10

11 Features Cloud based application server Data storage Communication Real-time notification Security/Privacy/Trust Intelligent content delivery Auto-scalable Support mobile and desktop users RAPID development 11

12 Past Attempt AppScale/Google AppEngine Frontend HTML5 Web Application Backend Google SQL/MySQL AppScale/Google AppEngine Real-time Socket (HTML5), XMPP 12

13 Past Attempt (continued) Advantages Write once, run anywhere Existing technology Several traffic applications have developed Auto-scalable Disadvantages Limited development model Relational database may fail to meet our big data requirements Mobile device may not be fully HTML5 compliance 13

14 Current Attemp Native Mobile App Frontend JavaScript PhoneGap platform ( Backend J2EE MangoDB Real-time AJAX, Comet technique ( 14

15 Native Mobile App Advantages Flexible development model/enterprise Application MangoDB Real-time Big data/easy scale-out Scalable Enabled Support for many mobile OSs ios, Android, Blackberry, Windows Phone, WebOS, Bada and Symbian 15

16 Status Development State Initial implementation Map Data On/Off Mark bad road Store data on device Store data on server Collecting data Bumps in the road Power management Accuracy of collected data Data interpretation 16

17 Security Network Sniffing network traffic Masquerade (spoofing) Denial of Service (DoS) Message tampering (session hijacking) Privacy Access Control Auditing 17

18 Privacy and Accountability Group Signature Valid signatures by group members always verify correctly, and invalid signatures always fail verification Given a message and its signature, the identity of the individual signer cannot be determined without the group manager's secret key Given two messages and their signatures, we cannot tell if the signatures were from the same signer or not. 18

19 Access Control Expressive and flexible policies Context- aware model Distributed and suitable for big data Need-to-share paradigm 19

20 Policy-Based Access Control Dynamic nature Draws policies and attributes from many Community of Interests (COIs) Utilizes extensible Access Control Markup Language (XACML) Technica s open source PBAC reference implementation 20

21 Conclusion Smartphone as road sensors Technical and non-technical challenges Conceptual approaches for attacking data collection and security issues 21

22 Acknowledgements Prof. Marin Litoiu Graduate Students Vasileios Theodorou Mitch Constantine 22