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

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)

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”

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

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

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

Proposed Vehicular Data Cloud Platform

Proposed Vehicular Data Cloud Platform

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

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

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

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

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

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

Naïve Bayes Classifier Documents Classes Training Data Classifier Joint probability

Naïve Bayes Classifier Maximum a Posteriori (MAP) Estimation

Logistic Regression Model Class Probability Model Parameters

Warranty Issue Clustering

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

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