Show simple item record

Study and Implementation of Wireless Sensor Networks to Manage Energy in a Smart Home

dc.contributor.authorAdebayo, Gbenga Waliyi
dc.date.accessioned2019-06-03T15:11:54Z
dc.date.available2019-06-03T15:11:54Z
dc.date.issued2017-12-09
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/123456789/4882
dc.description.abstractMany studies have shown that smart homes can use energy more efficiently than traditional buildings. Thus, several researchers have advocated building a smart home in order to reduce energy consumption. In the literature, Wireless Sensor Network is adopted as the dominant technology for every proposed smart home . In this thesis I explain the challenges of the state of the art technology in WSN for energy management in a smart home using one of the most prominent LPWAN technologies: LoRa TM . The system is not only low-cost but is also flexible enough to accept multiple sensor nodes and collect the data, irrespective of the distance from the gateway to the various appliances in the smart home. Leveraging on LPWAN technologies, I establish a series of models that cover various aspects of a LoRa network. Then, a new Network Simulator 3 (NS3) module is introduced to simulate a LoRa-based IoT network in a typical urban scenario. Finally, the performance of the LoRa system is evaluated and analysed. I emphasize the importance of having a generic system in which its LoRaWAN network configuration function set (router and coordinator) mode of data transmission will be implemented in API mode to accommodate any sensor node for better packet reception (RX) and transmission (TX).en_US
dc.description.sponsorshipAUST,AfDBen_US
dc.language.isoenen_US
dc.subjectAdebayo Gbenga Waliyien_US
dc.subjectProf Ousmane Thiareen_US
dc.subject2017 Computer Science and Engineering Thesesen_US
dc.subjectWireless Sensor Networken_US
dc.titleStudy and Implementation of Wireless Sensor Networks to Manage Energy in a Smart Homeen_US
dc.typeThesisen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

  • Computer Science105

    This collection contains Computer Science Student's Theses from 2009-2022

Show simple item record