Internet of Things Approach to CloudBased Smart Car
Internet of Things Approach to Cloud-Based Smart Car Parking Yacine Atif, Jianguo Ding, Manfred A. Jeusfeld University of Skövde, Sweden September 20, 2016
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
Parking Activities (Key Activities)
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
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
Research Methodology Big Data Analytics Real-Time Processing Business Modeling Computational Search Wo. T Platform Sensing as a Service Middleware Io. T Infrastructure Parking Devices Car Devices Security, Privacy and Trust Cloud Server
Internet of Things Infrastructure • Parking applications need a common abstraction of, and a standard approach to interact with parking spaces • Io. T infrastructure harnesses physical heterogeneity of parking sensors, and render them as a shared representation via standard RESTfull Web services • Io. T layer provides Internet connectivity to sensing devices through embedded or augmented communications technologies (infrastructure)
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 (Sensor. ML) Cloud computing enables sensors to offload their payload to the backend
Sensing as A service Middleware • Architecture based on eventdriven SOA [to address capabilities needed to respond to real-time Io. T infrastructure • Sensor adapter layer provides an interface with underlying Io. T infrastructure to address the technical diversity of sensor types and communication • The semantic mediator layer imports sensor description in Sensor. ML and translates it to OWL description using ontology and mediation rules.
Web of Things Platform Internet of Things (Io. T) and the requirement for a standard application platform birthed the Web of Things (Wo. T) • Wo. T focuses on using Web platform to interoperate sensor-services with Web applications • Wo. T 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 Wo. T through Restfull Web services
Cloud Applications Big Data Analytics Real-Time Processing Business Modeling Computational Search
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
• 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, Privacy and Security
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
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
Thank You Yacine. Atif@his. se
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