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Crowdsourced traffic event detection and source reputation assessment using smart contracts
ID
Mihelj, Jernej
(
Avtor
),
ID
Zhang, Yuan
(
Avtor
),
ID
Kos, Andrej
(
Avtor
),
ID
Sedlar, Urban
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(2,38 MB)
MD5: 68DAD177EF95B9AA602CF4D1D8973C58
URL - Izvorni URL, za dostop obiščite
https://www.mdpi.com/1424-8220/19/15/3267
Galerija slik
Izvleček
Real-time data about various traffic events and conditions—offences, accidents, dangerous driving, or dangerous road conditions—is crucial for safe and efficient transportation. Unlike roadside infrastructure data which are often limited in scope and quantity, crowdsensing approaches promise much broader and comprehensive coverage of traffic events. However, to ensure safe and efficient traffic operation, assessing trustworthiness of crowdsourced data is of crucial importance; this also includes detection of intentional or unintentional manipulation, deception, and spamming. In this paper, we design and demonstrate a road traffic event detection and source reputation assessment system for unreliable data sources. Special care is taken to adapt the system for operation in decentralized mode, using smart contracts on a Turing-complete blockchain platform, eliminating single authority over such systems and increasing resilience to institutional data manipulation. The proposed solution was evaluated using both a synthetic traffic event dataset and a dataset gathered from real users, using a traffic event reporting mobile application in a professional driving simulator used for driver training. The results show the proposed system can accurately detect a range of manipulative and misreporting behaviors, and quickly converges to the final trust score even in a resource-constrained environment of a blockchain platform virtual machine.
Jezik:
Angleški jezik
Ključne besede:
truth discovery
,
road traffic
,
event detection
,
reputation assessment
,
blockchain
,
smart contract
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FE - Fakulteta za elektrotehniko
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2019
Št. strani:
17 str.
Številčenje:
Vol. 19, iss. 15, art. 3267
PID:
20.500.12556/RUL-132831
UDK:
004:351.811
ISSN pri članku:
1424-8220
DOI:
10.3390/s19153267
COBISS.SI-ID:
12587860
Datum objave v RUL:
04.11.2021
Število ogledov:
956
Število prenosov:
163
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
Sensors
Skrajšan naslov:
Sensors
Založnik:
MDPI
ISSN:
1424-8220
COBISS.SI-ID:
10176278
Licence
Licenca:
CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:
http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:
To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:
01.08.2019
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
odkrivanje resnice v podatkih
,
cestni promet
,
detekcija dogodkov
,
ocenjevanje ugleda
,
veriženje podatkovnih blokov
,
pametne pogodbe
Projekti
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P2-0246
Naslov:
ICT4QoL - Informacijsko komunikacijske tehnologije za kakovostno življenje
Financer:
Drugi - Drug financer ali več financerjev
Program financ.:
National Natural Science Foundation of China
Številka projekta:
61572231
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