1. Developing Vehicular Data Cloud Services in the IoT Environment
Wu He, Gongjun Yan, and Li Da Xu, Senior Member, IEEE
Presented by Jonathan Lobo

2. Motivation
Modern vehicles already equipped with lots of sensors and communication devices
IoT and Cloud computing provide an opportunity to address transportation issues
Intelligent Transportation Systems (ITSs)

3. Intelligent Transportation System
A vehicular data platform using IoT and the cloud “where transportation-related information, such as traffic control and management, car location tracking and monitoring, road condition, car warranty, and maintenance information, can be intelligently connected and made available to drivers, automakers, part-manufacturers, vehicle quality controllers, safety authorities, and regional transportation division”

4. Related Work - IoT Vehicular ad-hoc networks (VANET) iDrive (BMW)
Support V2V and V2I communication
Integrate different communication technologies and sensor networks
Driver safety, traffic monitoring, roadside assistance
iDrive (BMW)
Informatics system using sensors to track vehicle location, road condition, and provide directions
Intelligent Internet of Vehicles Management System (IIOVMS)
Collect traffic information in real-time

5. Related Work - Cloud Vehicular cloud service platforms
Integrate existing vehicular networks, sensors, on-board vehicular devices
Service Oriented Architecture (SOA)
Vehicular devices exchange services and information to collaborate in real-time
ITS-Cloud architecture
3 layers: cloud, communication, end-user
Integrates in-vehicle CPS, V2V, V2I

6. Proposed Vehicular Data Cloud Platform
Goal: provide secure, on-demand vehicular services to customers
Conventional cloud
Data processing, high-level traffic administration applications
Temporary cloud
Formed on demand
Vehicles provide under-utilized computing power, networking, storage
Support for dynamic applications such as traffic monitoring, smart parking

7. Proposed Vehicular Data Cloud Platform

8. Proposed Vehicular Data Cloud Platform

9. Intelligent Parking Cloud Service
Goal : Collect and analyze geographic location, parking availability, parking space reservations, and traffic information to make finding parking spots easier
$345 in wasted time, fuel, and emissions

10. Intelligent Parking Cloud Service
Vehicle has transceiver
Before arriving, reserve an open spot
When a car enters the parking lot, the entrance booth will validate the reservation and direct driver to the reserved parking slot
Parking lot has wi-fi network, infrared devices, and parking belts
Validate whether a car has parked

11. Intelligent Parking Cloud Service
Wireless transceiver tower in parking lot broadcasts parking lot information
Roadside transceivers display the information

12. Parking Service Models
Predict revenue / spot availability using birth-death stochastic process
Birth = vehicle entering parking lot
Death = vehicle leaving parking lot
Birth rate
Death rate
Number of spots occupied at time t

13. Parking Service Models
Occupied spots at time 0
Probability of a car parking event at time t when there are j cars trying to park
Expected number of parked cars at time t

14. Vehicular Maintenance Data Mining
Motivation
Maintenance is frustrating for customers
Car manufacturers, parts designers can also learn from data
Goal
Data mine all vehicular maintenance data documents and classify by issue
Use data to detect dangerous road situations, issue warning messages, prevent accidents, assess vehicles’ performance

15. Naïve Bayes Classifier
Documents
Classes
Training Data
Classifier
Joint probability

16. Naïve Bayes Classifier
Maximum a Posteriori (MAP) Estimation

17. Logistic Regression Model
Class Probability
Model Parameters

18. Warranty Issue Clustering

19. Challenges Scalability Performance, reliability, quality of service
Must be energy efficient, handle dynamically changing number of vehicles, spikes in traffic at different times, emergency situations
Performance, reliability, quality of service
Vehicles are moving so communication may be unreliable
Different cloud data centers to optimize response time
Lack of standardization
Coordination between stakeholders
Lack of clear business model
Security and privacy
Lack of established infrastructure for authentication and authorization

20. Conclusion
Architecture is great, but in order to be useful, services need to be developed and deployed
Integrating data from vehicular devices and the road infrastructure will allow innovation in the automobile industry