Presentation on theme: "John Soldatos, Associate Professor Athens Information Technology Mobile Crowdsensing, Social and Big Data as Innovation Enablers for Future."— Presentation transcript:
John Soldatos, Associate Professor Athens Information Technology email@example.com Mobile Crowdsensing, Social and Big Data as Innovation Enablers for Future Internet Cloud-based Architectures and Services Athens - March 13, 2014 Integrating Social Sensors in IoT applications for Smart Cities
Internet-of-Things IoT Physical & Virtual Objects Uniquely Identifiable Objects Blend into Business and Social Processes Interoperable Protocols
IoT Sensors (Data Sources) and Actuators (Services) IoT process data streams (Physical & Virtual Sensors) Cameras Microphones LIDAR Radar Energy Meter Image Sensors RFID / Barcode Reader A/V Processing Algorithms Manual Count / Human Sensor IoT invokes actuating services Motion Controller Relays Lights On/Off Trigger Alarms Start/Stop Device Invoke Notification Services Execute workflows Computers - Web Services
«Social» Sensors Types of «Social» Sensors Sentiment Analysis Topic-based Community Tracking Event Detection Opinion Mining More... «Social» Sensors Applications Political Science Market Research Financial Services Branding Crisis Management Law Enforcement More...
Citizens as «Social» Sensors Citizens can act as sensors to connect with governments and help the latter understand their wishes and needs Technologies GIS Applications Web and Mobile Apps Typical Use Cases Incident Reporting Suggestions & Comments Use of Social Media Tweet to government accounts @gov Access/post in Facebook pages etc.
IoT and Social Media Social Media provide millions of insights on human activity and behaviour during emergencies and security incidents Examples: London Riots (Twitter), Egypt (Twitter/Facebook), but also «Sandy» Storm (20M Tweets, 10 Instagram photos / sec) Relevant Technologies: Sentiment Analysis, Community Tracking, Rumour Spreading Detection,...) - Used in several industries (marketing, branding, finance...) IoT architectures and technologies support «Social» Sensors (as Virtual Sensor) Twitter Sentiment Analysis On-line: http://www.sentiment140.com/ Twitter Map During «Sandy» IoT architectures deal with the proliferating «Social» Sensors
FP7 SMART Project Factsheet Consortium: Atos Athens Information Technology IBM Haifa Research Lab Imperial College London Consorzio S3LOG TELESTO Technologies Ltd. (SME) University of Glasgow (Research) Prisa Digital City-of-Santander Timeframe: 01/11/2011-31/10/2014 Project Budget: 4.425.000 Euro EC Contribution: 2.686.292 Euro Web Site: http://www.smartfp7.eu/
FP7 SMART = Search Engine over Integrated Social and Sensor Networks A/V Sensor Streams Processing Perceptive Components MultiMedia Intercepting Content from Social Networks Support for multiple social networks/media Social Fusion of Multiple Data Sour ces Reasoning over various Data Streams Intelligent Novel Indexing & Retrieval Techniques Global Deployment (incl. BigData) Scalable & Dynamic Based on Open Source Components (terrier.org) Publicly available based on an open source license Open Source M.-D. Albakour, C. Macdonald, I. Ounis, A. Pnevmatikakis, J. Soldatos, «SMART: An Open Source Framework for Searching the Physical World», Proceedings of the ACM SIGIR 2012 Workshop on Open Source Information.
SMART Edge Nodes Edge Node: SMART Point of Presense Provides real-time information from the city: Perceived from the environment (sensors) Filtered from social networks Retrieved from the linked data cloud Inferred by fusing the above into higher-level events
SMART Applications: Live News Live News : “What is happening now?” “Which places are crowded?”, “What are the specific trends in the city?” “Where are riots and fights happening?” Answers = Multimedia streams mixing sounds/images with textual data stemming from sensors and metadata steams (including social networks) Deployed at City of Santander
SMART Applications: Security & Surveillance Detect people and/or scenes that could be considered as suspicious across certain times and urban locations Data Streams from Cameras, Mics and Social Networks Deployed at City of Santander
SMART Applications: Build Your Own SC Scenario JSR 168 (Java Portlets) compliant editor Sensor and Social Sensor Driven Portlets and mashups Customized Portal Developments for Smart City Authorities Authoring tool for SMART Cities Development Deployed at Santander, Athens, Glasgow
SMART Open Source http://opensoftware.smartfp7.eu/ SMART is open source software released Fully documented! Users, Developers, Contributors can access it at: http://opensoftware.smartfp7. eu/ Follow us: @smartfp7 Visit us at FIA Athens (2014) Exhibition
Alternative Approach: Standardized Semantic Modelling of «Social» Sensors Semantic Interoperability Distributed and Heterogeneous Data Sources Diverse Data Streams Common Semantics Needed Solution: Semantic Annoitation (W3C Ontology) Reasoning Algorithms Intelligent Selection & Filtering of Sensors Intelligent Selection & Filtering of Sensor Data Use of Reasoners RDF/OWL Ontology (W3C SSN + Linked Data) Semantic Standards for sensors provide a uniform way for representing and reasoning over heterogeneous data streams
«Social» Sensors in the Cloud (OpenIoT project) PerformanceCapacity ElasticityUtility-Driven IoT in the Cloud Open Source Project (https://github.com/ OpenIotOrg/openiot) Martin Serrano, Manfred Hauswirth, John Soldatos, Nikos Kefalakis, "Design Principles for Utility-Driven Services and Cloud-Based Computing Modelling for the Internet of Things", International Journal of Web and Grid Services (to appear), 2014.
Conclusions Social Media Processing can provide millions of insights on people and things attitude and behaviour «Social» Sensors is a prominent Virtual Sensor in the scope of IoT applications IoT architectures make provisions for the integration of Socia Media data Semantic Interoperability of Social Media Streams is a key for their dynamic discovery and use