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2013 09-01 enviroinfo presentation - final

2013 09-01 enviroinfo presentation - final



"Future Internet enablers for VGI applications" presentation from ENVIROINFO 2013, Sept. 02-04 2013

"Future Internet enablers for VGI applications" presentation from ENVIROINFO 2013, Sept. 02-04 2013

Shows the ENVIROFI results relevant to crowdsourcing and crowdtasking.



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  • FI-PPP programme is large and innovative, aims at establishing the European Future Internet ecosystem and infrastructure. The Phase 1 projects concentrated at producing the requirenments for the core FI-Ware project and built some early prototypes. Phase 2 projects are expected to deliver more advanced prototypes and the 3-rd call targets the innovative SMEs which will monetarise the FI-PPP results.
  • The ENVIROFI (www.envirofi.eu) project aims at representing the know-how and interests of this Usage Area, by following two main goals: (1) to ‘Envirofy’ the Future Internet, that is, to assure that the FI applications can easily use the environmental data and services; and (2) to make the Core Platform functionality available in environmental applications. Compared to other P1 projects, ENVIROFI has put more emphasis on use of existing software from the environmental and geospatial domains, as well as on the own software development than other P1 projects.
  • Two out of three ENVIROFI scenarios are strongly biased towards citizen scientists, mobile crowdsourcing and crowdtasking and local situation awareness.
  • Both the ICSU Grand Challenges and the Digital Agenda for Europe explicitly acknowledge the societal importance of ICT for environment as one of the key enablers for sustainable development and improved quality of life. Most Europeans value a healthy environment, and over 60% agree that policies aimed at protecting the environment are a motivation to innovate. Yet, 42% feel badly informed with the greatest lack of information on the impacts of environmental change [1]. The Digital Agenda therefore identifies ICT for the environment as a critical area to deliver environmental, social and innovation-led growth objectives. In this vision, the opportunities of new technologies such as Sensor Web, and smart grids play a particularly important role. The European commitment to sustainable growth and innovation through investment in ICT for the environment is demonstrated by the development of the Infrastructure for Spatial Information in Europe (INSPIRE), the transition from research to operations of the Global Monitoring for Environment and Security (GMES) initiative, the development of the a Shared Environmental Information System (SEIS), and the combination of all three as a European contribution to the Global Earth Observation System of Systems (GEOSS) initiative, which recognizes the global nature of environmental problems. “ Sensor based” technology just achieved a major breakthrough as physical sensors became Web enabled; “citizen based” technology, also known as Volunteered Geographic Information (VGI), faces a new area of mass deployment; and “model based” technologies provide major interoperability challenges. Not surprisingly, the Sensor Web, or better the Observation Web is considered as the “next big thing” in the development of smart systems. [1] EC. European Comission Public Opinion, 2008. Eurobarometer Surveys (http://ec.europa.eu/public_opinion/archives/eb/eb68/eb68_en.htm)
  • In some senses, humans are „bad sensors“. They are non-standardized, difficult to calibrate, don‘t like the idea of working 24/7, easily bored and their accuracy and sensitivity erratically varies over time. However, they also excell at pattern recognition and interpretation of the results. This makes them complementary to hardware sensors and very valuable for some types of applications.
  • Out of six envirofi enablers groups, two are covered by FI-ware and two more feature well developed and standardized software.
  • Data fusion is a never-ending story and unlikely to be fully exploited in foreseeable future. Mobile crowd sourcing, crowdtasking and local situation awareness require software optimized for these uses at the level of workflows, technology, presentation, quality assurance and user interaction.
  • Tasking of volunteers and experts is a key to data collection and quality assurance. It is crucial to task the users which are both able and willing to perform this task, while avoiding the information overflow. In ENVIROFI, AIT was able to develop a concept and basic technology which will allow us to implement the context- and profile- specific tasking in the future projects.
  • In order to handle the types of applications shown in previous slide, AIT developed the “MDAF” framework. The framework consists of a server part, a mobile client part and a caching/syncronization layer between the two On the backend, the MDAF can to various other services, including the OGC WFS and SOS (to integrate additional observations) and the FI-Ware Pub/Sub Generic enabler (to interact with other FI-Ware services, especially with the Wirecloud mashup platform). The MDAF-internal event handling is needed in order to handle geospatial aspects of the event handling (sending to events to users which indicated interest in certain Area of Interest).
  • In order to improve the interaction with users, we define the event-driven informing/alerting/tasking as one of the three basic user interraction patterns. Status at the end if the ENVIROFI project: Viewing and reportign is fully functional and can be adaptet to new applications as needed. Event handling is developed at PoC level. we can send the events, and they are also shown to the user in several ways. It would be easy to go a step further and alert the user when he/she is near some currently active event. What is currently missing is the server-side mechanism to generate some sensible requests for action – automatically or by application owner. All users get to see today is a note saying „new observation in your vicinity“.
  • Unlike standard monitoring systems, the human sensors (and to a lesser extent also information from user-owned sensors) inevitably deliver conflicting and incomplete information. The Quality assurance of such data often relies on combination of peer review, expert opinions and various indicators. In MDAF, all these results can happily co-exist even if they are contradicting each other. The decision „what is the reality?“ is only made at the level of „application specific view“, taking into account the owners interests and trust in various data sources. As a result, it is perfectly possible to generate several conflicting „realities“ from the same data set. E.g. a Greanpeace applicaiton will show different reality than a fisherman association applicaiton simply because they make different assumprions concerning the relative importance and trustworthiness of the data. The „applicaiton specific view“ has not been fully implemented, but the technology is the same as the one used for the quality assurance part.
  • The architecture shown here goes beyond the ENVIROFI pilots and indicates our ideas what woudl be possible to do with FI-Ware GEs in the future.
  • This demo has been developed within the project scope and brought to working PoC status. We are confident that the concept will work well when we start making „real“ applicaitons. In fact, we (AIT) are using this in CRISMA project now, so the number of available widgets and our know-how steadily rises…
  • I‘m not sure which is the license for the slides which I „inherited“ here, sorry. I‘m sure that *I* can use them, and I presume the right to re-use them will be granted to anyone who asks. Please contact the respective consortium leaders.

2013 09-01 enviroinfo presentation - final 2013 09-01 enviroinfo presentation - final Presentation Transcript

  • “ENVIROfying” the Future Internet THE ENVIRONMENTAL OBSERVATION WEB FOR THE CROSS-DOMAIN FI-PPP APPLICATIONS Future Internet enablers for VGI applications ENVIROINFO 2013, Sept. 02-04 2013 Denis Havlik (AIT), Javier Soriano (UPM), Carlos Granell (JRC), Stuart E. Middleton (IT-INNOV); Hylke van der Schaaf (IOSB), Arne J. Berre (SINTEF), Jasmin Pielorz (UBIMET)
  • Overview 2
  • FI-PPP Programme © 2013 CONCORD Project Consortium 3 FI-WARE: Technology Foundation SME Innovation 3rd Call Use Case Expansion Phase Call 3 TF Continuation FI-CONTENT 2 FITMAN FI-STAR FIspace Call 2 FINESCE XIFI: Capacity Building INFINITY: Capacity Building & Infrastructure ENVIROFI Call 1 CONCORD: Programme Facilitation & Support 20112010 2012 2013 2014 2015 Phase 3Phase 1 Phase 2 FI-CONTENT USECASES OUTSMART SafeCity FINSENY SMARTAGRIFOOD Instant Mobility FInest 3
  • ENVIROFI Vision We envision … • an Environmental Observation Web in which all environmental data, from sensors, citizens, and models, is available through the Internet in a standardized, usable format • a system with dynamic understanding of the Earth’s atmospheric, marine and terrestrial spheres for the benefit of all European citizens © 2013 ENVIROFI Project Consortium
  • Why FI for environment? 5
  • ENVIROFI Scenarios 1. Bringing Biodiversity into the Future Internet • Enabled biodiversity surveys with advanced ontologies • Analysis, quality assurance and dissemination of biodiversity data 1. Personal Information System for Air Pollutants, allergens and meteorological conditions • Enhance human to environment interaction • Atmospheric conditions and pollution in “the palm of your hand” 1. Collaborative Usage of Marine Data Assets • Assess needs of key marine user communities • Selection of representative marine use cases for further trial: leisure and tourism, ocean energy devices, aquaculture, oil spill alert © 2013 ENVIROFI Project Consortium
  • Focus on Observations ENVIROFI focuses on observations and re-use of the standardized geospatial services Observations can originate from various sources • Web-enabled sensors and sensor networks • Citizen observations / human sensors • Models and data fusion services © 2013 ENVIROFI Project Consortium
  • Humans are sensors, but different Illustration by Scoobay (http://www.flickr.com/photos/scoobay/224565711/) 8
  • OBSERVE PUBLISH DISCOVER COMPOSE ANALYSE ACT NOTIFY MANAGE Environmental Monitoring and Decision Lifecycle Human Sensor Data Service Geospatial SEs Environmental SEs FI-WARE - Generic Enablers Apps Serv.Repositor y Marketplace Sem Comp Editor WireCloud Mediator Cloud-I2ND Alloc VMs Alloc Obj St Security ID Mgmt Data 2 Query Brok Locations Seman App Seman Ann Data 1 Comp Evt.Proc Pub/Sub Broker BigData An IoT Things Mgmt Device Mgmt GW Data Handling Prot Adapter TAGging Uncertainty semantic annotation MEDiation Discovery broker Discovery augm component Access broker Connector – SOS Connector – WCS Connector – WFS Connector – WMS Connector – toolbox Mediator – SOS Mediator – Fusion toolbox Transcode sensor Fusion Data fusion Image sample classification Asset geo- reference analysis Areas classification Prediction service Model-based fusion GEO Observ collection Observ catalogue Observ retrieval Observ identification Observ visualization Observ operatiing Image sample archive Sample Quality Asses Georef observ prox Georef Observ app NOTificatio n Alert notification Sensor Event VGI Mobile VGI enabler MDAF Cloud storage and Synchronisation (MDAF) Environmental (Biodiversity, Atmospheric and Marine) ApplicationsEnvironmental (Biodiversity, Atmospheric and Marine) Applications Geospatial Services OGC Charting OGC SensorWeb OGC Processing OGC Storage (OPeNDAP) THREDDS ERDDAP WPSSOS, SPSWMS, WCS WFS FI-W are FI-W are © 2013 ENVIROFI Project Consortium
  • 10 Main developments: (1)mobile crowd-sourcing and crowd-tasking; (2)fusion of heterogeneous data
  • Envisaged functionality 11 Mobile Users Sensors Automated Tasking External Data Manual Tasking Decision maker Experts Algorithms
  • Mobile Data Acquisition Framework (MDAF) architecture 12
  • Basic user interaction patterns View existing knowledge •Map view •Table view •Detailed View •Areas of Interest View existing knowledge •Map view •Table view •Detailed View •Areas of Interest Receive information (events!) •Requests for more observations, •Warnings, e.g. “pollen warning” •Interests, e.g. “monumental tree in vicinity” Receive information (events!) •Requests for more observations, •Warnings, e.g. “pollen warning” •Interests, e.g. “monumental tree in vicinity” Report observations •“New” things, e.g. “here and now I see a tree” •Personal, e.g. “I have a headache” •Obs. on existing thing, e.g. “this tree currently blossoms Report observations •“New” things, e.g. “here and now I see a tree” •Personal, e.g. “I have a headache” •Obs. on existing thing, e.g. “this tree currently blossoms Inform Server Backend (or proxy) Alert! Request Action!
  • Observation DB Dealing with heterogeneity and conflicts 14 Plausibility/Confidence checks Consensus building Previous situation knowledge Habitat Informatio n Image Recognition Reporters Reputation Observ. on things (independent, conflicting, incomplete) Observations on observations (identification, plausibility, annotation) Application specific views (fusion, meaning uncertainty) Sensor Networks ENVIROFI observations ENVIROFI observations Integrate existing data Integrate existing data USE
  • Plausibility of data and QA 15 Image Classifier SE Quality Assessment SE classify & check images Image Archive SE manage images MDAF server mobile acquisition General User leaf images metadata (e.g. geotag) Expert leaf species manual assessment © 2013 ENVIROFI Project Consortium
  • Application architecture 16 „Cloud Edge“ GE: Field-deployment of observations server; (P2P?) information exchange over local WLAN „Cloud Edge“ GE: Field-deployment of observations server; (P2P?) information exchange over local WLAN 16 Observations & Situation Awareness Cloud Storage Storing of BLOBS (photos, videos) Cloud Storage Storing of BLOBS (photos, videos) Marketplace GEs: sales, revenue sharing Marketplace GEs: sales, revenue sharing Pub/sub GE: Events processing & dissemination Pub/sub GE: Events processing & dissemination Security GEs: user & right mgm.; legal compliance Security GEs: user & right mgm.; legal compliance IoT GEs: Smart sensors? IoT GEs: Smart sensors? Environmental SEs Meaning Data Fusion, Forecasting Harvestors, Connectors Observations Big data GEs: Annotation & processing Big data GEs: Annotation & processing Cloud mgm. GEs: automated deployment, scaling Cloud mgm. GEs: automated deployment, scaling I2ND GEs: Network reliability, Hardware abstraction, I2ND GEs: Network reliability, Hardware abstraction, Mashup GE: Ad-hoc applications Mashup GE: Ad-hoc applications
  • Role of web Mashups 17 ENVIROFI web-mashup PoC: http://youtu.be/yEXlLQYq7s4
  • Lessons learned (VGI) • Humans are good at occasional subjective observations and judgments; bad at repeating and quantization • Users need to be motivated, e.g. by emphasizing their contributions and profile/context-aware “tasking” • We can selectively task the users without continuously tracing their location • Narrowing down the choices by automated processing services is a GoodThing™ (tested with e.g. leaf recognition, eHabitat). Cloud hosting and citizens enablement are game- changers for environmental UA
  • Lessons Learned (FI-Ware) Most FI-Ware GEs from the Cloud Hosting, Data/Context management, and Security chapters are truly generic and should be usable in environmental applications •Event-related GEs are convenient for integration of GEs, SEs and third party services in FI application •Application mashup platform can speed up application prototyping •Marketplace & co. could be a way to bring environmental data and services to businesses that need them. •GEs from the Internet of Things (IoT) chapter may be interesting for future applications Main issues with FI-Ware: Lack of maturity (2-nd release already available!); Weak support for Geospatial data and processing, weak semantic stack; IoT partially competing with OGC SWE.
  • 20
  • Unless stated differently, the slides are © 2013 Denis Havlik and licensed under the terms of the Creative Commons ”Attribution-ShareAlike 3.0“ license. Re-use of resuls 21 MDAF development continues as FOSS. Code will be online next month; new users and partners are welcome!
  • 1. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement Number 284898 2. The ENVIROFI produced significant input to standardisation through CEN/TC287, TR 15449- 2/3, Geographic information — Spatial Data Infrastructures – Best practices, ISO 19119, OGC Topic 12, … 3. ENVIROFI is a collaborative effort of 14 partners (see next slide). Austrian part of the team includes AIT, UBIMET and the Austrian Environmental Agency 4. The Generic Enablers are developed and maintained by the „FI-Ware“ – the core project of the FI-PPP Programme. Acknowledgements 22
  • Thank you for your attention Dr. Denis Havlik denis.havlik@ait.ac.at The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement Number 284898 www.envirofi.eu