MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03506nam a2200289 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| Qualifying information |
hardback |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
Universiti Teknologi Brunei |
| Language of cataloging |
eng |
| Transcribing agency |
UTB |
| 084 ## - BOOK Call Number |
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| Classification number |
UTB 120 REPORT, THESIS & DISSERTATION |
| -- |
RTDS 263 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Ak Mohammad Salihin Pg Hj Abd Rahim |
| Relator term |
Author |
| 245 10 - TITLE STATEMENT |
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| Title |
Threshold Based Algorithm For Bicycling Crash Detection Empirical Evaluation and Optimization / |
| Statement of responsibility, etc. |
Ak Mohammad Salihin Pg Hj Abd Rahim |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc. |
Brunei Darussalam : |
| Name of publisher, distributor, etc. |
Universiti Teknologi Brunei , |
| Date of publication, distribution, etc. |
© 2019. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
73 Pages : |
| Other physical details |
illustrations , charts ; |
| Dimensions |
30 cm. |
| 500 ## - GENERAL NOTE |
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| General note |
A Dissertation Submitted in Partial Fulfillment for the Degree of Msc By Coursework i Computing and Information systems Universiti Teknologi Brunei. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Abstract<br/>Despite the growing popularity of bicycles as an alternative to motor vehicles, the world has categorized bicycles as one of the vulnerable road users on the road. The widespread use and increase in the capability of smartphones serve as a motivation for developing more cost-effective solutions to boost bicycling safety. The purpose of this research is to support further the needs for enhancing the safety of the bicyclists by proposing a solution that combines the ability of a smartphone and a threshold-based algorithm (TBA) for bicycling crash detection. Multiple studies have concluded that TBA is effective in detecting fall incidents. However, the majority of the studies on TBA focused more on detecting fall amongst the elderly, and there is inadequate research on the use of this algorithm for a bicycling crash. In addition to this, the findings from the studies on TBA also reported that the algorithm has a limitation of a high false positive rate, and it requires some amendments in its structure to optimize its performance. Therefore, this research aimed to contribute new findings by applying the TBA to the bicycling domain and suggest ways to optimize the algorithm, so it fits the researched domain best. The optimization process involved developing a mobile application prototype entitled Cyclists Fall to generate the dataset for finding a reliable threshold value to evaluate the algorithm. The findings presented underlined that the application of the basic TBA in the bicycling domain has similar behavior as the elderly fall, where it performs very well in detecting bicycling crashes, but the false positive rate remains high. Due to this reason, this research considers two optimization methods to improve the algorithm, the Acceleration-Drop method and the Multiple-Exceeds method. The first method was rejected due to its high implementation complexity. On the contrary, the second method shows that it has effectively reduced the false positive rate in the result, and the precision has increased significantly from 62.5 per cent to 84 per cent. |
| 502 ## - Dissertation Note |
|---|
| Dissertation Note |
Dissertation (Degree of Msc in Computing and Information Systems) |
| 504 ## - Bibliography, Etc. Note |
|---|
| Bibliography, Etc. Note |
Includes bibliography references. |
| 610 #4 - SUBJECT ADDED ENTRY--CORPORATE NAME |
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| Form subdivision |
Final Year Project |
| Corporate name or jurisdiction name as entry element |
Universiti Teknologi Brunei |
| 650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Bicycles |
| General subdivision |
Accidents |
| -- |
Detection. |
| 650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Crash detection systems. |
| 650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Algorithms. |
| 710 ## - ADDED ENTRY--CORPORATE NAME |
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| Corporate name or jurisdiction name as entry element |
Universiti Teknologi Brunei |
| Subordinate unit |
School of Computing and Informatics |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Local Classification |
| Suppress in OPAC |
No |
| Koha item type |
Reports, Thesis & Dissertation Students |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) |
|---|
| Internal field |
Reports, Thesis & Dissertation |
| CC (RLIN) |
850425 : 002041 c. 1_UTB |
| Internal field |
Universiti Teknologi Brunei |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) |
|---|
| Internal field |
CD-ROM |
| CC (RLIN) |
850426 : CD No. RTDS CD 34 UTB |
