09-07-2012, 03:15 PM
Context Reasoning for Potential Objects Detection in Smart Sensor Rich Environment
[attachment=27284]
Introduction
Smart space, in which devices, agents, robots and
everyday objects are all expected to seamlessly integrated
and cooperate in support of human lives, will soon
become part of our daily activities [1]. However, to
achieve this goal, numerous challenges need to be
tackled, one of which is the information acquisition from
physical world. For example, in order to perform
sophisticated communication, robots need to acquire
sufficient information about the object that human pays
attention to. This paper describes a new idea to deal with
information acquisition from physical world objects.
Potential Objects Detection
Problem Description
gives a sample of potential object detection.
There are three sensor attached objects in the figure. But
as Book-A is placed on Book-B, the ultrasonic radio sent
by Book-B is blocked by Book-A, thus Book-B is
undetectable by the network, then how to detect Book-B
is one type of potential objects detection problem.
Sixth-Sense Architecture
A whole architecture of Sixth-Sense is shown in
Figure 3. The first two layers, physical layer and sensor
deployment layer appear as the input X in (1), while the
application layer represents the output Y. What’s more,
the context reasoning layer acts as the f function.
Physical Layer: This layer involves various everyday
objects and sensors. Most of the objects are easily found
in a typical home, such as books, tables, or toys.
Conclusion and Future Work
This paper proposed a potential objects detection
system named Sixth-Sense which can be used to obtain
information from objects in the smart space. We attached
MOTEs to several selected objects to form the Sixth-
Sense Skeleton, by which we can obtain context from
these objects. The context will then be analyzed by the
inference rules. However, currently we can only detect
the existence and probable location of the potential object.
Considering the rich information from the reference
object hasn’t been sufficiently used, in the future we will
devote to obtain more information from the derived
object, even to estimate what type of object it might be.
[attachment=27284]
Introduction
Smart space, in which devices, agents, robots and
everyday objects are all expected to seamlessly integrated
and cooperate in support of human lives, will soon
become part of our daily activities [1]. However, to
achieve this goal, numerous challenges need to be
tackled, one of which is the information acquisition from
physical world. For example, in order to perform
sophisticated communication, robots need to acquire
sufficient information about the object that human pays
attention to. This paper describes a new idea to deal with
information acquisition from physical world objects.
Potential Objects Detection
Problem Description
gives a sample of potential object detection.
There are three sensor attached objects in the figure. But
as Book-A is placed on Book-B, the ultrasonic radio sent
by Book-B is blocked by Book-A, thus Book-B is
undetectable by the network, then how to detect Book-B
is one type of potential objects detection problem.
Sixth-Sense Architecture
A whole architecture of Sixth-Sense is shown in
Figure 3. The first two layers, physical layer and sensor
deployment layer appear as the input X in (1), while the
application layer represents the output Y. What’s more,
the context reasoning layer acts as the f function.
Physical Layer: This layer involves various everyday
objects and sensors. Most of the objects are easily found
in a typical home, such as books, tables, or toys.
Conclusion and Future Work
This paper proposed a potential objects detection
system named Sixth-Sense which can be used to obtain
information from objects in the smart space. We attached
MOTEs to several selected objects to form the Sixth-
Sense Skeleton, by which we can obtain context from
these objects. The context will then be analyzed by the
inference rules. However, currently we can only detect
the existence and probable location of the potential object.
Considering the rich information from the reference
object hasn’t been sufficiently used, in the future we will
devote to obtain more information from the derived
object, even to estimate what type of object it might be.