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1 W3C Semantic Sensor Networks Ontologies, Applications, and Future Directions Cory Henson Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis.

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Presentation on theme: "1 W3C Semantic Sensor Networks Ontologies, Applications, and Future Directions Cory Henson Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis."— Presentation transcript:

1 1 W3C Semantic Sensor Networks Ontologies, Applications, and Future Directions Cory Henson Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis )Kno.e.sis Wright State University, Dayton, Ohio, USA IERC AC4 Semantic Interoperability Workshop June 2012, Venice, Italy co-located with IoTWeek 2012

2 2 Once upon a time, there was the Web

3 3 … and then it grew (ca. 2012)

4 4 Who or what is the culprit? User generated content, new types of media, etc.

5 5 A cross-country flight from New York to Los Angeles on a Boeing 737 plane generates a massive 240 terabytes of data - GigaOmni Media What happens when all THINGS go online? (sensors, devices, and appliances begin to publish data) What happens when all THINGS go online? (sensors, devices, and appliances begin to publish data)

6 How are machines supposed to make sense of this noisy, ambiguous, heterogeneous, deluge of data? How are machines supposed to make sense of this noisy, ambiguous, heterogeneous, deluge of data? RDF OWL

7 7 lives in has pet is a has pet Person Animal Concrete Facts Resource Description Framework Concrete Facts Resource Description Framework Semantic Web (according to Farside) General Knowledge Web Ontology Language General Knowledge Web Ontology Language “Now! – That should clear up a few things around here!” is a

8 8

9 9 ~ 50 Billion Statements

10 10 SW is now moving from academia into industry

11 11 In the last few years, we have seen many successes … Knowledge Graph Watson Apple Siri

12 12

13 13 Now, what about the Sensor Web?

14 14 Sensor systems are too often stovepiped

15 15 We want to set this data free With freedom comes responsibility 1.discovery, access, and search 2.integration and interpretation

16 16 Introducing the Sensor Web Enablement (SWE)

17 17 Introducing the Sensor Web Enablement (SWE)

18 18 We want to set this data free With freedom comes responsibility 1.discovery, access, and search 2.integration and interpretation

19 19 RDFOWL Semantic Sensor Networks (SSN) How are machines supposed to make sense of this noisy, ambiguous, heterogeneous, deluge of data? How are machines supposed to make sense of this noisy, ambiguous, heterogeneous, deluge of data? So, again …

20 20 SSN Ontology (i.e., General Sensor Knowledge) SSN Ontology (i.e., General Sensor Knowledge)

21 21 SSN Ontology (i.e., General Sensor Knowledge) SSN Ontology (i.e., General Sensor Knowledge)

22 22 SSN Ontology (i.e., General Sensor Knowledge) SSN Ontology (i.e., General Sensor Knowledge)

23 23 Semantic Annotation of SWE (backwards compatible) Semantic Annotation of SWE (backwards compatible)

24 24 Adoption of SSN

25 25 SSN Use Cases

26 26 Linked Sensor Data (~2 Billion Statements) Linked Sensor Data (~2 Billion Statements)

27 27 Sensor Discovery Application Query w/ location name to find nearby sensors

28 28 Interpretation (or abstraction/explanation) of sensor data Interpretation (or abstraction/explanation) of sensor data

29 29 Applications of SSN Healthcare WeatherRescue

30 order of magnitude resource savings between storing observations vs. relevant abstractions order of magnitude resource savings between storing observations vs. relevant abstractions 50% savings in sensing resource requirements during the detection of a blizzard 50% savings in sensing resource requirements during the detection of a blizzard 30

31 31 Weather Application SECURE: Semantics-empowered Rescue Environment (detect different types of fires) SECURE: Semantics-empowered Rescue Environment (detect different types of fires)

32 Mobile app to help reduce re-admission of patients with Chronic Heart Failure Mobile app to help reduce re-admission of patients with Chronic Heart Failure 32

33 33 Passive Monitoring Phase Abnormal heart rate Clammy skin Panic Disorder Hypoglycemia Hyperthyroidism Heart Attack Septic Shock Check phone for instructions Patient has history of Heart Disease Observed Symptoms Possible Explanations Electronic Medical Record Health Alert

34 34 Active Monitoring Phase Are you feeling lightheaded? Are you have trouble taking deep breaths? yes Patient has history of Hyperthyroidism Patient has prescription for Methimazole Have you taken your Methimazole medication? Do you have low blood pressure? yes Abnormal heart rate Clammy skin Lightheaded Trouble breathing Low blood pressure Panic Disorder Hypoglycemia Hyperthyroidism Heart Attack Septic Shock Observed Symptoms Possible Explanations Electronic Medical Record Health Alert no 1.Take medication: Methimazole 2.See doctor: how about 11am?

35 35 W3C Semantic Sensor Networks Ontologies, Applications, and Future Directions Cory Henson Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis )Kno.e.sis Wright State University, Dayton, Ohio, USA Thanks. In the next century, planet earth will don an electronic skin. It will use the Internet as a scaffold to support and transmit its sensations. This skin is already being stitched together. It consists of millions of embedded electronic measuring devices. Neil Gross, The Earth Will Don an Electronic Skin, BusinessWeek, Aug IERC AC4 Semantic Interoperability Workshop June 2012, Venice, Italy co-located with IoTWeek 2012


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