Home automation: Real-time electricity consumption monitoring and remote home appliance control

dc.contributor.authorAmoaning-Yankson, Kingsley
dc.date.accessioned2019-07-01T10:48:39Z
dc.date.available2019-07-01T10:48:39Z
dc.date.issued2018-04
dc.descriptionApplied project submitted to the Department of Computer Science, Ashesi University, in partial fulfillment of Bachelor of Science degree in Computer Science, April 2018en_US
dc.description.abstractInternet of things (IoT) has provided an opportunity for technology to be used to solve more complex problems and understand a lot more processes and activities by collecting and analyzing data. The growing demand for electricity in Ghana has been coupled with the increase in cost of providing this basic amenity. The homeowner has been burdened with high electricity billing, which has led to the adoption of life changing recommendations. Home automation technology has provided a means of effectively monitoring electricity consumption and remote control of homes. Unfortunately, this technology has not been leveraged in solving the problem of high electricity billing in Ghana. This project has built a system that leverages IoT technology in creating a cost-effective real-time electricity monitoring and remote-control system. The System helps its users to reduce their electricity consumption by helping him/her ensure appliances that are not in use can be turned off remotely, provides a visual representation of consumption data and a threshold setting feature for monitoring total daily/monthly consumption.en_US
dc.description.sponsorshipAshesi Universityen_US
dc.identifier.urihttp://hdl.handle.net/20.500.11988/419
dc.language.isoen_USen_US
dc.subjectInternet of Thingsen_US
dc.subjectelectricity monitoringen_US
dc.subjecthome automationen_US
dc.titleHome automation: Real-time electricity consumption monitoring and remote home appliance controlen_US
dc.typeApplied projecten_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Amoaning-Yankson_Kingsley_2018_CS_AppliedProject .pdf
Size:
6.39 MB
Format:
Adobe Portable Document Format
Description: