De-Noising Signals using Wavelet Transform in Internet of Underwater Things
dc.contributor.author | Khan, Asiya | |
dc.contributor.author | Pemberton, Richard | |
dc.contributor.author | momen, A | |
dc.contributor.author | bristow, D | |
dc.date.accessioned | 2019-02-08T10:10:39Z | |
dc.date.issued | 2019-08-24 | |
dc.identifier.isbn | 9783030295127 | |
dc.identifier.issn | 2194-5357 | |
dc.identifier.issn | 2194-5357 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/13283 | |
dc.description.abstract |
Internet of Underwater Things (IoUT) is an emerging field within Internet of Things (IoT) towards smart cities. IoUT has applications in monitoring underwater structures as well as marine life. This paper presents preliminary work where sensor nodes were built on Arduino Uno platform with temperature and pressure sensors with wireless capability. The sensors nodes were then tested in the Flumes of the COAST laboratory to determine the maximum depth achievable in fresh water before the signal is lost as radio frequencies are susceptible to interference under water. Further, the received signals were de-noised using Wavelet Transform, Daubechies thresholding techniques at level 5. Preliminary results suggest that at a depth of 30 cm, signal was lost, de-noising of the signal was achieved with very small errors (a mean squared error of 0.106 and 0.000446 and Peak-Sign-to-Noise Ratios of 70.18 dB and 58.83 dB for the pressure and temperature signals, respectively. Results from this study will lay the foundation to further investigations in wireless sensor networks in IoUT integrating the de-noising techniques. | |
dc.format.extent | 1192-1198 | |
dc.language.iso | en | |
dc.publisher | Springer International Publishing | |
dc.subject | IoUT | |
dc.subject | Sensors | |
dc.subject | Arduino Uno | |
dc.subject | Wavelet Transform | |
dc.title | De-Noising Signals using Wavelet Transform in Internet of Underwater Things | |
dc.type | conference | |
dc.type | inproceedings | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000628838900085&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.volume | 1038 | |
plymouth.conference-name | Intellysis 2019 | |
plymouth.publication-status | Published | |
plymouth.journal | Springer series "Advances in Intelligent Systems and Computing" | |
dc.identifier.doi | 10.1007/978-3-030-29513-4_85 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA12 Engineering | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dcterms.dateAccepted | 2019-01-07 | |
dc.rights.embargodate | 2020-8-23 | |
dc.identifier.eissn | 2194-5357 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.1007/978-3-030-29513-4_85 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2019-08-24 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |