| dc.contributor.author |
Bhanot, Surekha |
|
| dc.date.accessioned |
2023-02-09T06:55:54Z |
|
| dc.date.available |
2023-02-09T06:55:54Z |
|
| dc.date.issued |
2011 |
|
| dc.identifier.uri |
http://www.iaeng.org/publication/WCECS2011/WCECS2011_pp106-111.pdf |
|
| dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9101 |
|
| dc.description.abstract |
Management and security of electric power plays
a key role in economy and sustainable development. The major
concerns in optimal usage of Power are reduction in wastage
and creating intelligent switching systems to make optimal use
of the power available. This paper proposes an adaptive smart
home system for optimal utilization of power, through
Artificial Neural Network (ANN). The system proposed
comprises of a Recurrent Neural Network to capture Human
behavior patterns and a Feed Forward Architecture in ANN
for security applications in the smart homes. The technique is
used to minimize the power wastage by studying and adapting
to the consumption behavior patterns of the consumers. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
WCECS |
en_US |
| dc.subject |
EEE |
en_US |
| dc.subject |
Temporal response |
en_US |
| dc.subject |
Human behavior mapping |
en_US |
| dc.subject |
Recurrent neural network (RNN) |
en_US |
| dc.subject |
Single layer perceptron model |
en_US |
| dc.title |
Smart Home System Design based on Artificial Neural Networks |
en_US |
| dc.type |
Article |
en_US |