[HTML][HTML] IoT-based traffic prediction and traffic signal control system for smart city
Because of the population increasing so high, and traffic density remaining the same, traffic
prediction has become a great challenge today. Creating a higher degree of communication …
prediction has become a great challenge today. Creating a higher degree of communication …
A novel framework to avoid traffic congestion and air pollution for sustainable development of smart cities
Traffic management is crucial for the sustainable development of smart cities. There has
been a continuous emphasis from the research community to predict air quality and manage …
been a continuous emphasis from the research community to predict air quality and manage …
Semi-supervised federated learning for travel mode identification from GPS trajectories
GPS trajectories serve as a significant data source for travel mode identification along with
the development of various GPS-enabled smart devices. However, such data directly …
the development of various GPS-enabled smart devices. However, such data directly …
[HTML][HTML] Data congestion control framework in Wireless Sensor Network in IoT enabled intelligent transportation system
T Kavitha, N Pandeeswari, R Shobana… - Measurement …, 2022 - Elsevier
Abstract Intelligent Transportation System (ITS) holds an inevitable concern in road safety
and efficient transportation. Data communication is enforced by wireless sensor nodes and …
and efficient transportation. Data communication is enforced by wireless sensor nodes and …
Stacked LSTM for short-term traffic flow prediction using multivariate time series dataset
Short-term traffic flow prediction has paramount importance in intelligent transportation
systems for proactive traffic management. In this paper, a short-term traffic flow prediction …
systems for proactive traffic management. In this paper, a short-term traffic flow prediction …
[HTML][HTML] Traffic congestion classification using GAN-Based synthetic data augmentation and a novel 5-layer convolutional neural network model
Private automobiles are still a widely prevalent mode of transportation. Subsequently, traffic
congestion on the roads has been more frequent and severe with the continuous rise in the …
congestion on the roads has been more frequent and severe with the continuous rise in the …
Improving transportation mode identification with limited GPS trajectories
The deployment of Global Positioning System (GPS) sensors in modern smartphones and
wearable devices has enabled the acquisition of high-coverage urban trajectories …
wearable devices has enabled the acquisition of high-coverage urban trajectories …
[PDF][PDF] An overview of traffic congestion detection and classification techniques in VANET
Vehicular traffic congestion has been and still is a major problem for many countries and
knowledge about the traffic condition is important in order to schedule, plan and avoid traffic …
knowledge about the traffic condition is important in order to schedule, plan and avoid traffic …
[HTML][HTML] Exploring bus tracking data to characterize urban traffic congestion
Quantification of traffic dynamics is a valuable tool for city planning and management.
Metrics such as the vehicle average speed, travel time, delays, and count of stops, can be …
Metrics such as the vehicle average speed, travel time, delays, and count of stops, can be …
A hybrid deep convolutional neural network approach for predicting the traffic congestion index
D Tran Quang, S Hoon Bae - Promet-Traffic&Transportation, 2021 - hrcak.srce.hr
Sažetak Traffic congestion is one of the most important issues in large cities, and the overall
travel speed is an important factor that reflects the traffic status on road networks. This study …
travel speed is an important factor that reflects the traffic status on road networks. This study …