1. Internet of Things Approach to Cloud-Based Smart Car Parking
Yacine Atif, Jianguo Ding, Manfred A. Jeusfeld
University of Skövde, Sweden
September 20, 2016

2. Parking Issues (Challenges and Opportunities)
Growing challenge of traffic and parking in urban areas
Traffic induced by entering/exiting parking (on special events or holidays)
Underutilized parking inventory
Increasing compliance and revenues
Maximizing mutual benefits for parking consumers and providers
Extending the globally interconnected continuum to parking spaces
Providing smart cities with smarter parking information and guidance

3. Parking Activities (Key Activities)

4. Parking Problems Searching and paying for a –vacant– parking space
Tracing parking status (current, past and estimated future)
Developing parking occupancy models and deriving availability probability
Reclaiming unused parking spaces and generate revenues
Alleviating the heterogeneity of connected parking spaces
Exposing parking services to smart applications
Collaborative path-planning to vacant parking spaces
Mitigating congestion induced by parking related issues
Enforcing security policies and preserving privacy

5. Parking Service Provider (Project Proposal)
OMNIA
PSP is a new business entity representing parking lot owners or intermediaries
Cloud platform (developed with our project partner) is augmented with new services that expand parking inventory and streamline parking operations

6. Research Methodology Big Data Analytics IoT Infrastructure
Sensing as a Service Middleware
Parking Devices Car Devices
Real-Time Processing
Computational Search
Security, Privacy and Trust
Business Modeling
Cloud Server
WoT Platform

7. Internet of Things Infrastructure
Parking applications need a common abstraction of, and a standard approach to interact with parking spaces
IoT infrastructure harnesses physical heterogeneity of parking sensors, and render them as a shared representation via standard RESTfull Web services
IoT layer provides Internet connectivity to sensing devices through embedded or augmented communications technologies (infrastructure)

8. Sensing as a Service Sensor-enabled devices are data collectors
Device owners offer device’s sensory data collection capabilities as services to applications
Sensors’ enabled Web services are driven by:
Cheaper sensors are promoting the development of third-party applications that respond to sensor data
Embedded sensors within Web servers are now easily programmable
Web of sensors are modelled via standard methodologies to described complex applications (SensorML)
Cloud computing enables sensors to offload their payload to the backend

9. Sensing as A service Middleware
Architecture based on event- driven SOA [to address capabilities needed to respond to real-time IoT infrastructure
Sensor adapter layer provides an interface with underlying IoT infrastructure to address the technical diversity of sensor types and communication
The semantic mediator layer imports sensor description in SensorML and translates it to OWL description using ontology and mediation rules.

10. Web of Things Platform
Internet of Things (IoT) and the requirement for a standard application platform birthed the Web of Things (WoT)
WoT focuses on using Web platform to interoperate sensor-services with Web applications
WoT substitutes the lack of capabilities in sensor services by cloud-based services
Simple HTML content populated with sensor data are channeled to backend cloud applicatons via WoT through Restfull Web services

11. Cloud Applications Big Data Analytics Real-Time Processing
Business Modeling
Computational Search

12. Collaborative Path-Planning
Computational Search
Finding a parking space is a Search problem, formulated as A* algorithm
Concurrent agents traverse the Search domain to plan paths towards vacant parking spaces, while considering each other progress
Nodes of the Search space are streets and metropolitan junctions
Agents take decisions that balance roads occupancy and reduce congestion
Agents collaborate to find the most mutually beneficial paths
Multi-agent search is computationally resource-intensive and exacerbated by dynamic and real-time traffic context

13. Security, Privacy and Trust
Trust, Privacy and Security
Role-based access control:
At sensor level (communicating parking sensors data)
At service level (publishing parking sensors data)
At application level (consuming parking sensors data)
Privacy and data protection
Protect user information protection
Protect / disable tracking information of cars
On-line payment security models and user-aware demand pricing protocols
Security, Privacy and Trust

14. Project Benefits New source of parking-related revenues
Hub for parking related services
Third-parties increase parking inventory
Intelligent parking with reduced costs and street congestion
Improved access to and exit from parking
Integrated parking functions under a common (cloud) platform
Added-value parking management services
Readiness for the connected future
Enhanced security and privacy

15. Connected Cars (Forthcoming Research)
Sustainable solutions, ready to integrate with future connected cars
Parking needs to be automated for upcoming connected cars
Seamless integration with further streamlined services such as:
Smart car insurances and diagnosis services
”Black box” like data services to resolve claims
Data-driven car to car communications (i.e. Internet of Cars)
Disruptive transformation trends of transportation

16. Thank You