Socially Responsible Technologies in Autonomous Mobility Systems: Self-Driving Car Control Algorithms, Virtual Data Modeling Tools, and Cognitive Wireless Sensor Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F22%3A00002507" target="_blank" >RIV/75081431:_____/22:00002507 - isvavai.cz</a>
Result on the web
<a href="https://www.ceeol.com/search/article-detail?id=1085227" target="_blank" >https://www.ceeol.com/search/article-detail?id=1085227</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Socially Responsible Technologies in Autonomous Mobility Systems: Self-Driving Car Control Algorithms, Virtual Data Modeling Tools, and Cognitive Wireless Sensor Networks
Original language description
The authors draw on extensive theoretical and empirical research in the areas of intelligent infrastructure sensors, autonomous control based on deep learning and data. and data processing technologies and spatio-temporal fusion algorithms. In this research, previous findings have been accumulated to suggest that monitoring and sensing technologies, predictive maintenance and data mining tools, and computer vision and object and detection algorithms optimize automotive traffic flows and road safety.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50200 - Economics and Business
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Contemporary Readings in Law and Social Justice
ISSN
1948-9137
e-ISSN
2162-2752
Volume of the periodical
14
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
172-188
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85145909649