Distributed intelligence model for Internet of things applications
| dc.contributor.author | Rababah, Baha | |
| dc.contributor.examiningcommittee | Thulasiram, Ruppa K (Computer Science) | en_US |
| dc.contributor.examiningcommittee | Ashraf, Ahmed (Electrical and computer engineers) | en_US |
| dc.contributor.supervisor | Eskicioglu, Rasit (Computer Science) | en_US |
| dc.date.accessioned | 2021-05-13T14:02:43Z | |
| dc.date.available | 2021-05-13T14:02:43Z | |
| dc.date.copyright | 2021-05-01 | |
| dc.date.issued | 2021-05 | en_US |
| dc.date.submitted | 2021-05-01T10:13:58Z | en_US |
| dc.degree.discipline | Computer Science | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | Increasing the implication of Internet of Things (IoT) data puts a focus on extracting the knowledge from sensors' raw data. The management of sensors' data is ine cient with current solutions, as studies have generally focused on either providing cloudbased IoT solutions or ine cient prede ned rules. Providing IoT gateways with relevant intelligence is essential for gaining knowledge from raw data to make the decision of whether to actuate or o oad tasks to the cloud. This work proposes a model that provides an IoT gateway with the intelligence needed to extract the knowledge from sensors' data in order to make the decision locally without needing to send all raw data to the cloud over the Internet. When the gateway is unable to process a task locally, the data and task are o oaded to the cloud. | en_US |
| dc.description.note | October 2021 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/35511 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | Internet of Things, Distributed Intelligence, IoT Gateway, Machine Learning, and Neural Networks | en_US |
| dc.title | Distributed intelligence model for Internet of things applications | en_US |
| dc.type | master thesis | en_US |