Road Condition Estimation with Data Mining Methods using Vehicle Based Sensors
The work provides novel methods to process inertial sensor and acoustic sensor data for road condition estimation and monitoring with application in vehicles, which serve as sensor platforms. Furthermore, methods are introduced to combine the results from various vehicles for a more reliable estimat...
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| Main Author: | |
|---|---|
| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
Karlsruhe
KIT Scientific Publishing
2021
|
| Series: | Karlsruher Schriftenreihe Fahrzeugsystemtechnik
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| Subjects: | |
| Online Access: | DOAB: download the publication DOAB: description of the publication |
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| 072 | 7 | |a TG |2 bicssc | |
| 100 | 1 | |a Masino, Johannes |4 auth | |
| 245 | 1 | 0 | |a Road Condition Estimation with Data Mining Methods using Vehicle Based Sensors |
| 260 | |a Karlsruhe |b KIT Scientific Publishing |c 2021 | ||
| 300 | |a 1 electronic resource (234 p.) | ||
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| 490 | 1 | |a Karlsruher Schriftenreihe Fahrzeugsystemtechnik | |
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a The work provides novel methods to process inertial sensor and acoustic sensor data for road condition estimation and monitoring with application in vehicles, which serve as sensor platforms. Furthermore, methods are introduced to combine the results from various vehicles for a more reliable estimation. | ||
| 540 | |a Creative Commons |f by-sa/4.0 |2 cc |4 http://creativecommons.org/licenses/by-sa/4.0 | ||
| 546 | |a English | ||
| 650 | 7 | |a Mechanical engineering & materials |2 bicssc | |
| 653 | |a Maschinelles Lernen | ||
| 653 | |a Fahrzeugtechnik | ||
| 653 | |a Straßenschäden | ||
| 653 | |a Fahrzeugsensorik | ||
| 653 | |a Maschine Learning | ||
| 653 | |a Vehicle Technology | ||
| 653 | |a Road Condition | ||
| 653 | |a Vehicle Sensors | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/bitstream/20.500.12657/48822/1/road-condition-estimation-with-data-mining-methods-using-vehicle-based-sensors.pdf |7 0 |z DOAB: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/70074 |7 0 |z DOAB: description of the publication |