Driving activity assessment using accelerometer data
| Main Authors: | Šolaja, Nikola, Miljković, Nadica, Sodnik, Jaka |
|---|---|
| Format: | Proceeding Journal |
| Bahasa: | eng |
| Terbitan: |
, 2022
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/6036290 |
| ctrlnum |
6036290 |
|---|---|
| fullrecord |
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<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Šolaja, Nikola</creator><creator>Miljković, Nadica</creator><creator>Sodnik, Jaka</creator><date>2022-02-10</date><description>Abstract
In this paper, we evaluated a variety of features acquired from data recorded from single tri-axial accelerometer placed on the subjects’ wrist in order to differentiate among driving events. Results obtained from 12 experienced drivers assessed in driving simulators with wristband revealed features that might be relevant for future driver’s activity recognition. Our preliminary exploratory data analysis showed that the most informative features for discriminative analysis among driving tasks are entropy and average spectral energy of the resultant acceleration.
Presentation
The presentation for this paper was held by MSc Nikola Šolaja in Portorož in 2019 and the presentation is available at https://zenodo.org/record/3510839.</description><description>Acknowledgement: Authors would like to thank Nervtech Ltd. from Trzin, Slovenia for providing data recorded in the driving simulator. Research was partly supported by the Ministry of education, science, and technological development, Republic of Serbia by Grant TR-33020 and also partly by the Slovenian Research Agency (L2-8178 and P2-0246).</description><identifier>https://zenodo.org/record/6036290</identifier><identifier>10.5281/zenodo.6036290</identifier><identifier>oai:zenodo.org:6036290</identifier><language>eng</language><relation>info:eu-repo/grantAgreement/MESTD/Technological+Development+%28TD+or+TR%29/33020/</relation><relation>doi:10.5281/zenodo.6036289</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by/4.0/legalcode</rights><subject>accelerometer</subject><subject>activity recognition</subject><subject>driving simulator</subject><subject>exploratory data analysis</subject><subject>hand movements</subject><title>Driving activity assessment using accelerometer data</title><type>Journal:Proceeding</type><type>Journal:Proceeding</type><recordID>6036290</recordID></dc>
|
| language |
eng |
| format |
Journal:Proceeding Journal Journal:Journal |
| author |
Šolaja, Nikola Miljković, Nadica Sodnik, Jaka |
| title |
Driving activity assessment using accelerometer data |
| publishDate |
2022 |
| topic |
accelerometer activity recognition driving simulator exploratory data analysis hand movements |
| url |
https://zenodo.org/record/6036290 |
| contents |
Abstract
In this paper, we evaluated a variety of features acquired from data recorded from single tri-axial accelerometer placed on the subjects’ wrist in order to differentiate among driving events. Results obtained from 12 experienced drivers assessed in driving simulators with wristband revealed features that might be relevant for future driver’s activity recognition. Our preliminary exploratory data analysis showed that the most informative features for discriminative analysis among driving tasks are entropy and average spectral energy of the resultant acceleration.
Presentation
The presentation for this paper was held by MSc Nikola Šolaja in Portorož in 2019 and the presentation is available at https://zenodo.org/record/3510839. Acknowledgement: Authors would like to thank Nervtech Ltd. from Trzin, Slovenia for providing data recorded in the driving simulator. Research was partly supported by the Ministry of education, science, and technological development, Republic of Serbia by Grant TR-33020 and also partly by the Slovenian Research Agency (L2-8178 and P2-0246). |
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IOS16997.6036290 |
| institution |
ZAIN Publications |
| institution_id |
7213 |
| institution_type |
library:special library |
| library |
Cognizance Journal of Multidisciplinary Studies |
| library_id |
5267 |
| collection |
Cognizance Journal of Multidisciplinary Studies |
| repository_id |
16997 |
| subject_area |
Multidisciplinary |
| city |
Stockholm |
| province |
INTERNASIONAL |
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1 |
| repoId |
IOS16997 |
| first_indexed |
2022-06-06T06:53:38Z |
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2022-06-06T06:53:38Z |
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dc |
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17.610285 |