P2 3-manfred hauswirth
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- © Copyright 2012 OpenIoT Consortium EU OpenIoT Project FP7 ICT-2011 1.3: Internet-connected Objects Open Source blueprint for large scale self-organizing cloud environments for IoT applications Manfred Hauswirth, DERI John Soldatos, AIT Sensing an Enterprise Semantic Cloud Based IoT Middleware FinES Cluster Meeting, Aalborg, May, 9th, 2012 Panel #2 , «The Sensing Enteprise»
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Manfred Hauswirth from DERI presented the "EU OpenIoT Project" (FInES Workshop at Aalborg)
Transcript of P2 3-manfred hauswirth
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© Copyright 2012
OpenIoT Consortium
EU OpenIoT Project
FP7 ICT-2011 1.3: Internet-connected Objects
Open Source blueprint for large
scale self-organizing cloud
environments for IoT applications
Manfred Hauswirth, DERI
John Soldatos, AIT
Sensing an Enterprise Semantic Cloud Based IoT
Middleware
FinES Cluster Meeting, Aalborg, May, 9th, 2012
Panel #2 , «The Sensing Enteprise»
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
© Copyright 2012
OpenIoT Consortium 2
Sensing Enterprise Definition
• Sensing Enterprise:
– Enterprise anticipating future decisions by using multi-dimensional information captured through physical and virtual objects and providing added value information to enhance its global context awareness
• Concept created by the FInES community in the context of the Augmented Internet (see: “FinES Position Paper on Orientations for FP8 A European Innovation Partnership for Catalysing the Competitiveness of European Enterprises”, March 2011)
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
© Copyright 2012
OpenIoT Consortium 3
Scope of OpenIoT
• STREP Project, December 2011- November 2014
– Main Goal: Research and development of an open source middleware platform enabling the setup of utility/cloud based infrastructures for IoT services
– http://www.openiot.eu/
• Example:
– Utility-based sensor clouds (i.e., Sensing-as-a-Service)
• Main research topics:
– Semantic interoperability for ICO
– Linked Sensor Data
– Pay-as-you-go IoT services
– Utility-driven security and privacy
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
© Copyright 2012
OpenIoT Consortium 4
Relation to Sensing Enterprise
• OpenIoT is processing information streams stemming from both physical and virtual objects: – Physical objects : sensing devices (e.g., temperature sensor, WSN, ZigBee)
– Virtual objects: User-defined combinations of sensing streams such as sensor information fusion algorithms (e.g., product “greenness” sensor)
• OpenIoT enables a certain level of reasoning over the information collected from multiple physical and virtual objects: – Semantic Web technologies / reasoning capabilities
– Enabling added-value filtering & processing (context-aware) in order to identify information or drive decisions & actions
• OpenIoT aspires to measure utility associated with physical / virtual sensors: – Utility can be used to measure business value (e.g., track & trace the value of
an asset, identify the value of a brand)
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
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OpenIoT Consortium 5
OpenIoT Highlights (1)
• Enhancement of the popular open-source Global Sensor Networks Middleware (http://sourceforge.net/apps/trac/gsn/)
– Background IPR of the project
– GSN-Cloud infrastructure integration towards a «Sensor Cloud»
– Early experiments with popular cloud infrastructures (SimpleDB, Hbase, Cassandra over Amazon Cloud) in progress
• Integration with other IoT platforms and ecosystems:
– Support for standards (such as IETF COAP, W3C SSN)
– Integration with IoT platforms (EPCGlobal, Pachube.com…)
– More sensors and data feeds
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
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OpenIoT Highlights (2)
• Utility-based infrastructures:
– IoT accounting & billing
– Utility-driven security & privacy
– Utility-driven resource management
• Scalable, global infrastructure:
– Support for any type of Sensor
– Support for any type of Virtual Sensor
• Support for on-demand utility based services:
– Sensing-as-a-Service
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
© Copyright 2012
OpenIoT Consortium 7
Draft Architecture
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
© Copyright 2012
OpenIoT Consortium 8
W3C Semantic Sensor Networks
• Uniform description of all physical and virtual sensors
– Can model any kind observations relevant to the sensing enterprise
• Enables semantic interoperability between sensors and sensor services
– Uniform way of exchanging data from/to the sensors
• Provides a basis for reasoning that can ease development of advanced applications
– E.g., select sensors, filter information
• Organizes, manages, queries, understands and controls sensor information through high-level specifications
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
© Copyright 2012
OpenIoT Consortium 9
SSN-XG Ontology Structure
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
© Copyright 2012
OpenIoT Consortium 10
SSN-XG Ontology Structure
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
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OpenIoT Consortium 11
OpenIoT can Handle Social Sensors
• Social sensors: filters & components processing feeds from social networks
– Prominent example: Twitter filters such as Gender Analysis and Sentiment Analysis
• Social sensors enable a range of entreprise applications such as branding & marketing applications
• Sentiment Analysis : http://www.sentiment140.com/
• Ask Twitter from the FP7 SMART project (http://www.smartfp7.eu)
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
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Sensing Enterprise Use Cases
• Data Discovery and Linking: Find all observations that meet certain criteria, and possibly link them to other external data sources
– Measure eco-profile for a product family & link to its pricing!
• Device Discovery and Selection: Find all the devices that meet certain criteria (e.g,., type, geographic region, measured phenomenon, range of measurement, availability, owner or responsible party, manufacturer,….)
– Which are the social sensors that deal with our enterprise?
• Combinations of the above: Provenance and diagnosis
– Which is the most effective marketing strategy?
• Device Operation Tasking and Programming:
– Configure manufacturing production after sensing demand and oil prices!
Open Source blueprint for large scale self-organizing cloud environments for IoT applications
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OpenIoT Consortium 13
Indicative Application Areas
• Manufacturing:
– Sense, Track & Trace Tangible Assets (e.g., Cost of Product, Product Eco-Profile)
– Sense, Track & Trace Intangible Assets (e.g., a Quality Control Process)
• Branding/Marketing:
– Effectiveness of a market campaign
– Sensing/Assessing a corporate brand
• Reputation Management:
– Trust Assessment about an Entity (Business or Individual)
• Possibilities are limited by corporate creativity and types of virtual / physical sensors available
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OpenIoT Consortium 14
Conclusions
• The emerging digital «Sensing» Enterprise will be supported through a wider range of physical, virtual and social sensors
• The Sensing Enterprise concept can allow companies to sense and measure business value of tangible and intangible assets
• Prominent application areas can be found in manufacturing, logistics, branding/marketing, reputation management,…
• Enterpises are only limited by creativity in the ways they exploit the multitude of available sensors in order to sense & measure business value
