ADEROS: Artificial Intelligence-Based Detection System of Critical Events for Road Security
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU148549" target="_blank" >RIV/00216305:26220/23:PU148549 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10147025" target="_blank" >https://ieeexplore.ieee.org/document/10147025</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/JSYST.2023.3276644" target="_blank" >10.1109/JSYST.2023.3276644</a>
Alternative languages
Result language
angličtina
Original language name
ADEROS: Artificial Intelligence-Based Detection System of Critical Events for Road Security
Original language description
The deployment of artificial intelligence (AI) in Intelligent Transportation Systems (ITS), especially in the field of Intelligent Transportation Cyber-Physical Systems (ITCPS) has a strong potential to achieve higher efficiency, reliability, and increased safety in both transportation and traffic. This work focuses on the real-world implementation of ITCPS, in which structure and elements in combination with advanced image processing methods increase safety and fluidity of road traffic at crossroads and railway crossings. In this work, we present a novel system called Artificial Intelligence-based Detection System for Road Security (ADEROS), which combines elements of CPS systems, object detection, and classification, computer vision (CV) which analyzes vehicle trajectory tracking, vehicle and pedestrian presence, light signaling systems, railway barriers at railway crossings, and railway warnings. The presented system is based on a camera module that is suitably positioned to capture the entire scene. The module uses graphics processing units (GPU) for accelerated image processing techniques and the YOLOv4 deep neural network model to detect traffic participants and then dangerous situations in various crossroads and railway crossings. Our improved unique detector can distinguish between individual types of road users and the status of several safety devices at crossroads and railway crossings (for example, the state of traffic lights (TL) or rail barriers). Furthermore, we present experimental implementation details of the ADEROS system, which includes a central server web interface for live traffic situation monitoring, various communication channels for the camera module, and a central server based on.NET core, Cassandra DB, and different security protocols. All data from risky situations are evaluated and transferred to the central server securely without human intervention. The central server aggregates and archives all risky situational data from connected c
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
<a href="/en/project/CK04000027" target="_blank" >CK04000027: Traffic controll system of new generation (SENDER)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Systems Journal
ISSN
1932-8184
e-ISSN
1937-9234
Volume of the periodical
neuveden
Issue of the periodical within the volume
2023
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
1-12
UT code for WoS article
001012428400001
EID of the result in the Scopus database
2-s2.0-85162702252