Active Perception over Machine and Citizen Sensing

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

In the next few years, sensors networks will produce
10-20 times the amount of generated by social media
- GigaOmni Media
3

Active Perception
over Machine and Citizen Sensing
Cory Henson and AmitSheth
Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled Computing
Wright State University, Dayton, Ohio, USA
4

To enable situation awareness on the Web, we must utilize abstractions capable of representing observations and perceptions generated by either people or machines.
Web
observe
perceive
“real-world”
5

For example, both people and machines are capable of observing qualities, such as redness.
observes
Observer
Quality
* Formally described in a sensor/observation ontology
6

Sensor and Sensor Network (SSN) Ontology
http://www.w3.org/2005/Incubator/ssn/wiki/
7

The ability to perceive is afforded through the use of background knowledge, relating observable qualities to entities in the world.
Quality
* Formally described in domain ontologies
(and knowledge bases)
inheres in
Entity
8

http://linkedsensordata.com
9

With the help of sophisticated inference, both people and machines are also capable of perceiving entities, such as apples.
perceives
Entity
Perceiver
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)
10

minimize
explanations
tractable
degrade gracefully
Web reasoning
Web Ontology
Language (OWL)
Parsimonious Covering Theory (PCT)
11

Conversion of PCT to OWL 2 (EL)
Parsimonious
Covering Theory
(Abductive Logic)
*
OWL-DL
Cory Henson, KrishnaprasadThirunarayan, AmitSheth, 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.
12
12

The ability to perceive efficiently is afforded through the cyclical exchange of information between observers and perceivers.
Observer
sends
observation
sends
focus
Traditionally called the Perception Cycle
(or Active Perception)
Perceiver
13

Nessier’s Perception Cycle
14

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
15

Integrated together, we have an general model – capable of abstraction – relating observers, perceivers, and background knowledge.
observes
Observer
Quality
sends
observation
sends
focus
inheres in
perceives
Entity
Perceiver
16

i
ntelleg
“to perceive”
17

Application of
Weather
Traffic
18
18

Traffic Application
19

Detection of events, such as blizzards, from weather station observations on LinkedSensorData
Weather Application
50% savings in resource requirements needed for detection
20

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
21

http://wiki.knoesis.org	655
http://mnemosyne.de-blog.jp	479
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Active Perception over Machine and Citizen Sensing

by Kno.e.sis Center, Wright State University on Jun 08, 2011

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Active Perception over Machine and Citizen Sensing — Presentation Transcript