Active Perception over Machine and Citizen Sensing

Education Technology Business

Cory Henson and Amit Sheth, Active Perception Over Machine and Citizen Sensing, SemTech 2011, June 2011. http://semtech2011.semanticweb.com/sessionPop.cfm?confid=62&proposalid=3825 http://semantic-sensor-web.com

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

Active Perception
over Machine and Citizen Sensing
Cory Henson and Amit Sheth
Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled Computing
Wright State University, Dayton, Ohio, USA

1

Ohio Center of Excellence on
Knowledge-Enabled Computing
(Kno.e.sis)
A cross-country flight from New York

to Los Angeles on a
Boeing 737 plane generates a massive 240 terabytes of data
- GigaOmni Media

2

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

In the next few years, sensors networks will produce
10-20 times the amount of generated by social media
- GigaOmni Media

3

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

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

Observer

observes

Quality

* Formally described in a sensor/observation ontology

5

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

Sensor and Sensor Network (SSN) Ontology

http://www.w3.org/2005/Incubator/ssn/wiki/
6

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

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

Quality

inheres in

Entity

7

* Formally described in
domain ontologies
(and knowledge bases)

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

http://linkedsensordata.com
8

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

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

Perceiver

perceives

Entity

• 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)
9

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

minimize
explanations

tractable

degrade gracefully

Web reasoning

Web Ontology
Language (OWL)

Parsimonious Covering
Theory (PCT)

10

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

Conversion of PCT to OWL 2 (EL)

Parsimonious
Covering Theory
(Abductive Logic)

*

OWL-DL

* 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.

11

11

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

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

sends
observation

sends
focus

Perceiver

12

Traditionally called the
Perception Cycle
(or Active Perception)

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

Nessier’s Perception Cycle

13

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

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

14

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

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

Observer

sends
observation

observes

sends
focus

Perceiver

Quality

inheres in

perceives

15

Entity

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

i
16

ntelleg
“to perceive”

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

Application of
Weather

Traffic

17

17

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

Traffic Application

18

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

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

Weather Application

50% savings in resource requirements needed for detection
19

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

thank you, and please visit us at

http://semantic-sensor-web.com
Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled Computing
Wright State University, Dayton, Ohio, USA

20

A presentation about Civet, a service delivered by Knowledge Hives, we (Arek and Sebastian) gave on June 8th at SemTech 2011. The presentation also mentioned results of the "Semantic tools for digital libraries" project a.k.a. SemLib, which is a 24th month R&D project supported by EU FP7 Theme: Research for SMEs (no. FP7-SME-2010-01-262301-SEMLIB) commenced in January 2011. More info at http://www.semlibproject.eu

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