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Vikramaditya Jakkula. Temporal Pattern Discovery in Smart Homes. Smart Homes. Experimentation Environment. MavPad Argus Sensor Network around 100 Sensors. include Motion, Devices, Light, Pressure, Humidity and more. . Temporal Relations In Smart Homes. A “before” B “finishes-by” C.

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Vikramaditya jakkula

Vikramaditya Jakkula

Temporal Pattern Discovery in Smart Homes



Experimentation environment
Experimentation Environment

  • MavPad Argus Sensor Network

  • around 100 Sensors.

  • include Motion, Devices, Light, Pressure,

  • Humidity and more.


Temporal relations in smart homes
Temporal Relations In Smart Homes

A “before” B “finishes-by” C




Experimentation
Experimentation

  • Step 1: Eliminate Unnecessary datasets and identify the most frequent Itemset using Apriori Algorithm.

  • Step 2: Use Weight based Relation analysis to identify best relation to remove ambiguity.


Step 1 the apriori algorithm example
Step 1:The Apriori Algorithm Example

Database D

C1

L1

Scan D

C2

C2

L2

Scan D

L3

C3

Scan D


Step 2 relation formation

Table 3: Sample of Frequent Relation Pairs.

Step 2: Relation Formation

  • Use the above define temporal relations with the weight based rule given below to identify the best temporal relations.


Future directions
Future Directions

  • Prediction of activity.

  • Anomaly detection mechanism.

  • Visualization of temporal intervals for monitoring daily activities and lifestyle.


Conclusion
Conclusion


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