A Smart Service Model for Smart City: A Context-Based IoT Enabled Deep Learning Approach for Intelligent Transportation System Article Swipe
K. Hemant Kumar Reddy
,
Rajat Subhra Goswami
,
Diptendu Sinha Roy
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-2610874/v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-2610874/v1
Transportation is considered the fundamental pillarof economic growth in any society. Still, inherent issues likeaccidents, higher fuel consumption, and pollution have pavedthe way for the rise of the intelligent transportation system(ITS), which enables safety and improvement in the existingtransportation system. ITS helps the massive collection of datafrom multiple sources, and this big data needs immediate processing for ascertaining the events. However, prediction accuracycontinues to be low because of the trade-off of accuracy with theimmediate detection of an event, and this limits the performanceof ITS. This paper addresses this issue by proposing a novel IoT-enabled distributed context-aware Fog-cloud architecture, whichimproves the prediction accuracy by utilizing a hybrid CNN(Convolutional Neural Network) deep learning (DL) approach.Each vehicle in the system only has a track of the local knowledge.The nearby fog nodes are enabled to know the global eventsthrough incremental federated learning, which gets updatedcontinuously back and forth with fog and cloud. Experimentsdemonstrated in the paper clearly show that the modified versionof VGGNet for the CNN model outperforms RGB images,delivering an accuracy of more than 95%, which is 3% moreaccurate than the LeNet while using RGB images as input
Related Topics
Concepts
Computer science
Deep learning
Cloud computing
Convolutional neural network
Context (archaeology)
Intelligent transportation system
Artificial intelligence
Distributed computing
Real-time computing
Architecture
Internet of Things
Service (business)
Smart city
Computer security
Transport engineering
Engineering
Economics
Economy
Operating system
Paleontology
Visual arts
Art
Biology
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-2610874/v1
- https://www.researchsquare.com/article/rs-2610874/latest.pdf
- OA Status
- gold
- Cited By
- 4
- References
- 29
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4323039352
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4323039352Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-2610874/v1Digital Object Identifier
- Title
-
A Smart Service Model for Smart City: A Context-Based IoT Enabled Deep Learning Approach for Intelligent Transportation SystemWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-03Full publication date if available
- Authors
-
K. Hemant Kumar Reddy, Rajat Subhra Goswami, Diptendu Sinha RoyList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-2610874/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-2610874/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-2610874/latest.pdfDirect OA link when available
- Concepts
-
Computer science, Deep learning, Cloud computing, Convolutional neural network, Context (archaeology), Intelligent transportation system, Artificial intelligence, Distributed computing, Real-time computing, Architecture, Internet of Things, Service (business), Smart city, Computer security, Transport engineering, Engineering, Economics, Economy, Operating system, Paleontology, Visual arts, Art, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
29Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3128369476, https://openalex.org/W2267525789, https://openalex.org/W2788076214, https://openalex.org/W2196477648, https://openalex.org/W4225414027, https://openalex.org/W610613272, https://openalex.org/W2108196201, https://openalex.org/W2036785686, https://openalex.org/W2753704268, https://openalex.org/W3107312433, https://openalex.org/W2165991108, https://openalex.org/W2614459600, https://openalex.org/W1927170233, https://openalex.org/W2624162241, https://openalex.org/W3102178346, https://openalex.org/W2754460569, https://openalex.org/W3129499366, https://openalex.org/W1585377561, https://openalex.org/W2796632614, https://openalex.org/W2891157624, https://openalex.org/W2085374652, https://openalex.org/W3033059790, https://openalex.org/W2150066425, https://openalex.org/W1483870316, https://openalex.org/W1996058270, https://openalex.org/W2168867823, https://openalex.org/W2963037989, https://openalex.org/W2964658936, https://openalex.org/W4297666078 |
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