Estimating which Object Type a Sensor Node is Attached to in Ubiquitous Sensor Environment

2012 ◽  
pp. 404-417
Author(s):  
Takuya Maekawa ◽  
Yutaka Yanagisawa ◽  
Takeshi Okadome
Keyword(s):  
Daily Living ◽  
Sensor Node ◽  
State Transition ◽  
High Accuracy ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Object Type ◽  
Transition Diagram ◽  
State Transition Diagram ◽  
Physical Objects

By simply attaching sensor nodes to physical objects with no information about the objects, the method proposed in this paper infers the type of the physical indoor objects and the states they are in. Assuming that an object has its own states that have transitions represented by a state transition diagram, we prepare the state transition diagrams for such indoor objects as a door, a drawer, a chair, and a locker. The method determines the presumed state transition diagram from prepared diagrams that matches sensor data collected from people’s daily living for a certain period. A 2 week experiment shows that the method achieves high accuracy of inferring objects to which sensor nodes are attached. The method allows us to introduce ubiquitous sensor environments by simply attaching sensor nodes to physical objects around us.

Estimating which Object Type a Sensor Node is Attached to in Ubiquitous Sensor Environment

2010 ◽  
Vol 2 (1) ◽  
pp. 86-101 ◽  
Author(s):  
Takuya Maekawa ◽  
Yutaka Yanagisawa ◽  
Takeshi Okadome
Keyword(s):  
Daily Living ◽  
Sensor Node ◽  
State Transition ◽  
High Accuracy ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Object Type ◽  
Transition Diagram ◽  
State Transition Diagram ◽  
Physical Objects

By simply attaching sensor nodes to physical objects with no information about the objects, the method proposed in this article infers the type of the physical indoor objects and the states they are in. Assuming that an object has its own states that have transitions represented by a state transition diagram, we prepare the state transition diagrams for such indoor objects as a door, a drawer, a chair, and a locker. The method determines the presumed state transition diagram from prepared diagrams that matches sensor data collected from people’s daily living for a certain period. A 2 week experiment shows that the method achieves high accuracy of inferring objects to which sensor nodes are attached. The method allows us to introduce ubiquitous sensor environments by simply attaching sensor nodes to physical objects around us.

The State Transition Diagram

2012 ◽  
pp. 153-157
Author(s):  
Saul Greenberg ◽  
Sheelagh Carpendale ◽  
Nicolai Marquardt ◽  
Bill Buxton
Keyword(s):  
State Transition ◽  
The State ◽  
Transition Diagram ◽  
State Transition Diagram

Software Coverage Analysis

2012 ◽  
Vol 3 (3) ◽  
pp. 62-77 ◽  
Author(s):  
Praveen Ranjan Srivastava ◽  
Saurav Singh Naruka ◽  
Afaque Alam ◽  
Nikhil Agarwal ◽  
Vaibhav Mukeshkumar Shah
Keyword(s):  
State Transition ◽  
State Diagram ◽  
Software Requirements ◽  
Input State ◽  
Complete Coverage ◽  
Transition Diagram ◽  
State Transition Diagram ◽  
Coverage Analysis ◽  
Software Product ◽  
Uml Diagrams

Requirements of the desired software product can be translated into state transition diagram or other UML diagrams. To verify the complete coverage of software requirements, the proposed Ant based approach generates non-repetitive transitions from the input state diagram. This approach has less redundant transitions and also gives uncovered transition in successive paths instead of giving whole redundant path again and again. The paper also contains a comparison between already existing approaches with respect to some parameters like coverage, redundancy, total number of transitions.

scholarly journals Characterization of the Evolution of Nonlinear Uniform Cellular Automata in the Light of Deviant States

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Pabitra Pal Choudhury ◽  
Sudhakar Sahoo ◽  
Mithun Chakraborty
Keyword(s):  
Cellular Automata ◽  
Cellular Automaton ◽  
Boolean Functions ◽  
State Transition ◽  
The State ◽  
Transition Diagram ◽  
One Dimensional ◽  
State Transition Diagram ◽  
Linear Rule

Dynamics of a nonlinear cellular automaton (CA) is, in general asymmetric, irregular, and unpredictable as opposed to that of a linear CA, which is highly systematic and tractable, primarily due to the presence of a matrix handle. In this paper, we present a novel technique of studying the properties of the State Transition Diagram of a nonlinear uniform one-dimensional cellular automaton in terms of its deviation from a suggested linear model. We have considered mainly elementary cellular automata with neighborhood of size three, and, in order to facilitate our analysis, we have classified the Boolean functions of three variables on the basis of number and position(s) of bit mismatch with linear rules. The concept of deviant and nondeviant states is introduced, and hence an algorithm is proposed for deducing the State Transition Diagram of a nonlinear CA rule from that of its nearest linear rule. A parameter called the proportion of deviant states is introduced, and its dependence on the length of the CA is studied for a particular class of nonlinear rules.

Mapping and Simulation of Educational Games Using a State Transition Diagram and a Rules Base

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Sandrerley Ramos Pires ◽  
Tobias Gonçalves Pires ◽  
Dulcinéia Gonçalves F. Pires
Keyword(s):  
State Transition ◽  
Educational Games ◽  
Transition Diagram ◽  
State Transition Diagram
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