Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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Active Perception over Machine and Citizen Sensing

Cory Henson and Amit Sheth

Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled ComputingWright State University, Dayton, Ohio, USA

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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A cross-country flight from New York to Los Angeles on a Boeing 737 plane generates a massive 240 terabytes of data

- GigaOmni Media

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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In the next few years, sensors networks will produce10-20 times the amount of generated by social media - GigaOmni Media

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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For example, both people and machines are capable of observing qualities, such as redness.

* Formally described in a sensor/observation ontology

observesObserver Quality

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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Sensor and Sensor Network (SSN) Ontology

http://www.w3.org/2005/Incubator/ssn/wiki/

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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The ability to perceive is afforded through the use of background knowledge, relating observable qualities to entities in the world.

* Formally described in domain ontologies

(and knowledge bases)

inheres in

Quality

Entity

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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http://linkedsensordata.com

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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With the help of sophisticated inference, both people and machines are also capable of perceiving entities, such as apples.

• the ability to degrade gracefully with incomplete information

• the ability to minimize explanations based on new information

• the ability to reason over data on the Web

• fast (tractable)

perceivesEntityPerceiver

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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minimizeexplanations

degrade gracefully

tractable

Parsimonious Covering Theory (PCT)

Web OntologyLanguage (OWL)

Web reasoning

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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OWL-DL

Conversion of PCT to OWL 2 (EL)

ParsimoniousCovering Theory(Abductive Logic)

* Cory Henson, Krishnaprasad Thirunarayan, Amit Sheth, Pascal Hitzler. Representation of Parsimonious Covering Theory in OWL-DL. In: Proceedings of the 8th International Workshop on OWL: Experiences and Directions (OWLED 2011), San Francisco, CA, United States, June 5-6, 2011.

*

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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The ability to perceive efficiently is afforded through the cyclical exchange of information between observers and perceivers.

Traditionally called the Perception Cycle

(or Active Perception)

sendsfocus

sends observation

Observer

Perceiver

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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Nessier’s Perception Cycle

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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Cognitive Theory of Perception (timeline)

• 1970’s - Perception is an active, cyclical process of exploration and interpretation

- Nessier’s Perception Cycle

• 1980’s - The perception cycle is driven by background knowledge in order to generate and test hypotheses.

- Richard Gregory (optical illusions)

• 1990’s - In order to effectively test hypotheses, some observations are more informative than others.

- Norwich’s Entropy Theory of Perception

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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observes

inheres in

Integrated together, we have an general model – capable of abstraction – relating observers, perceivers, and background knowledge.

perceives

sendsfocus

sends observation

Observer Quality

EntityPerceiver

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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ntellegi “to perceive”

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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Application of

Traffic Weather

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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Traffic Application

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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50% savings in resource requirements needed for detection

Weather ApplicationDetection of events, such as blizzards, from weather station observations on LinkedSensorData

Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)

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thank you, and please visit us at

http://semantic-sensor-web.com

Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled ComputingWright State University, Dayton, Ohio, USA