W3C Semantic Sensor Networks Ontologies, Applications, and Future Directions

Transcription

1 IERC AC4: Semantic Interoperability Workshop On Semantic Interoperability (June 19-20, 2012) W3C Semantic Sensor Networks Ontologies, Applications, and Future Directions Cory Henson Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis ) Wright State University, Dayton, Ohio, USA 1

2 Once upon a time, there was the Web 2

3 and then it grew (ca. 2012) 3

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

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) 5

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

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

8 ~ 50 Billion Statements 8

9 SW is now moving from academia into industry 9

10 Watson Apple Siri In the last few years, we have seen many successes Knowledge Graph 10

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12 Now, what about the Sensor Web? 12

13 Sensor systems are too often stovepiped 13

14 We want to set this data free With freedom comes responsibility 1. discovery, access, and search 2. integration and interpretation 14

15 Introducing the Sensor Web Enablement (SWE) 15

16 Introducing the Sensor Web Enablement (SWE) 16

17 We want to set this data free With freedom comes responsibility 1. discovery, access, and search 2. integration and interpretation 17

18 So, again How are machines supposed to make sense of this noisy, ambiguous, heterogeneous, deluge of data? Semantic Sensor Networks (SSN) RDF OWL 18

19 SSN Ontology (i.e., General Sensor Knowledge) 19

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

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

22 Semantic Annotation of SWE (backwards compatible) 22

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27 Interpretation (or abstraction/explanation) of sensor data 27

28 Applications of SSN Weather Rescue Healthcare 28

29 50% savings in sensing resource requirements during the detection of a blizzard order of magnitude resource savings between storing observations vs. relevant abstractions 29

30 Weather Application SECURE: Semantics-empowered Rescue Environment (detect different types of fires) 30

31 Mobile app to help reduce re-admission of patients with Chronic Heart Failure 31

32 Passive Monitoring Phase Observed Symptoms Abnormal heart rate Clammy skin Possible Explanations Panic Disorder Hypoglycemia Hyperthyroidism Heart Attack Septic Shock Electronic Medical Record Patient has history of Heart Disease Health Alert Check phone for instructions 32

33 Active Monitoring Phase Are you feeling lightheaded? yes Are you have trouble taking deep breaths? Observed Symptoms Possible Explanations 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 yes Have you taken your Methimazole medication? no Electronic Medical Record Health Alert Patient has history of Hyperthyroidism Patient has prescription for Methimazole 1. Take medication: Methimazole 2. See doctor: how about 11am? 33

34 IERC AC4: Semantic Interoperability Workshop On Semantic Interoperability (June 19-20, 2012) 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 Thanks. W3C Semantic Sensor Networks Ontologies, Applications, and Future Directions Cory Henson Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis ) Wright State University, Dayton, Ohio, USA 34