dc.contributor.author |
Muhammad Farooq Arshad, Hussnain Shafique Cheema, Muhammad Asad Ullah |
|
dc.date.accessioned |
2020-11-03T10:37:47Z |
|
dc.date.available |
2020-11-03T10:37:47Z |
|
dc.date.issued |
2016 |
|
dc.identifier.uri |
http://10.250.8.41:8080/xmlui/handle/123456789/8995 |
|
dc.description |
Advisor: Dr. Asad Waqar Malik |
en_US |
dc.description.abstract |
With rising electricity prices, granular control over power consumption is needed more than ever. Consumers are unaware of how much electricity they utilize on a given day and thereby lack valuable insights needed to save electricity. Consumers frequently get inaccurate bills due to manual meter reading methodology. On electricity provider's side of things, electricity theft is a common occurring.
Smart Power Assistant gives a transparent picture of electric usage to electricity providers and consumers. It predicts consumers’ electricity usage and bill based on their history of energy usage by employing statistical models; thus, providing them with an opportunity to control their energy consumption. Consumers can access full records of their usage over the last year, split into half hour intervals. This data coupled with effective visualization and business intelligence could provide consumers with deeper insights into their electricity usage pattern and thereby assist them in deciding how to save on electricity by identifying potential energy hogs. For producers, our system could be very helpful in calculating the consumers’ monthly bills and sending them online as well. This could reduce the man-power which is needed to read meters and send bills to consumers by visiting them. |
en_US |
dc.publisher |
National University of Sciences and Technology, Islamabad. |
en_US |
dc.subject |
Computer Science, Smart Power Assistant |
en_US |
dc.title |
Smart Power Assistant |
en_US |
dc.type |
Thesis |
en_US |