Micro-safe: Microservices-and deep learning-based safety-as-a-service architecture for 6G-enabled intelligent transportation system

C Roy, R Saha, S Misra, K Dev - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this paper, we propose a microservices and deep learning-based scheme, termed as
Micro-Safe, for provisioning Safety-as-a-Service (Safe-aaS) in a 6G environment. A Safe …

Cloud-based collaborative road-damage monitoring with deep learning and smartphones

A Ramesh, D Nikam, VN Balachandran, L Guo… - Sustainability, 2022 - mdpi.com
Road damage such as potholes and cracks may reduce ride comfort and traffic safety. This
influence can be prevented by regular, proper monitoring and maintenance of roads …

RCNN-GAN: an enhanced deep learning approach towards detection of road cracks

SF Mahenge, S Wambura, L Jiao - Proceedings of the 2022 6th …, 2022 - dl.acm.org
Automatic detection of road cracks is one of the significant aspects of road maintenance
systems. However, it involves a lot of complexities to accurately identify the cracks because …

Analyzing embedded AIOT devices for deep learning purposes

R Budjac, M Barton, P Schreiber… - Computer Science On-line …, 2022 - Springer
In this article, we focused on the artificial intelligence of things (AIoT) embedded devices that
are characterized by higher computing power. These devices are designed directly to work …

Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data

X Tan, Y Shen, M Wang, B Wang - Proceedings of the 32nd ACM …, 2023 - dl.acm.org
Graph knowledge discovery from graph-structured data is a fascinating data mining topic in
various domains, especially in the Internet of Things, where inferring the graph structure …

Improving Driving Style in Connected Vehicles via Predicting Road Surface, Traffic, and Driving Style

YK Jawad, M Nitulescu - Applied Sciences, 2024 - mdpi.com
This paper investigates the application of ensemble learning in improving the accuracy and
reliability of predictions in connected vehicle systems, focusing on driving style, road surface …

Speed Bump Detection Through Inertial Sensors and Deep Learning in a Multi-contextual Analysis

J Menegazzo, A von Wangenheim - SN Computer Science, 2022 - Springer
Speed bumps are vertical raisings of the road pavement used to force drivers to slow down
to ensure greater safety in traffic. However, these obstacles have disadvantages in terms of …

Theoretical Experiments on Road Profile Data Analysis using Filter Combinations

DW Karmiadji, M Rosyidi, T Widodo… - Automotive …, 2023 - journal.unimma.ac.id
Identification of road profiles is needed to provide the input of automotive simulation and
endurance testing. The analysis with estimation methods is mostly done to identify road …

Cloud-Based Collaborative Road Condition Monitoring Using In-Vehicle Smartphone Data

Y Jia, G Comert, A Ramesh, D Nikam… - 2023 - rosap.ntl.bts.gov
Ensuring the safety of transportation systems requires monitoring the conditions of roads.
Traditional monitoring and inspection of road conditions require surveyors to walk or drive …

Pavement Surface Type Classification Based on Deep Learning to the Automatic Pavement Evaluation System

AC Espíndola, EF Nobre Júnior, ET Silva Júnior - 2021 - repositorio.ufc.br
. Computer vision techniques, image processing, and machine learning became
incorporated into an automatic pavement evaluation system with technological advances …