Recently, emerging SDN-based VANET (ie, vehicular ad hoc network based on software-
defined networking) enables VANET management to be programmable and flexible. It …

Intelligent connected vehicle trajectory data are of great value for data mining applications
such as traffic management and commercial institutions. However, the leakage of sensitive …

With the advancements in wireless networks, the number of user devices has increased
dramatically, resulting in high device densities. Despite the resulting data traffic deluge …

Anomaly detection is an important issue in trajectory data mining. Various approaches have
been proposed to address this issue. However, most previous studies focus only on outlier …

In this paper we focus on knowledge extraction from large-scale wireless networks through
stream processing. We present the primary methods for sampling, data collection, and …

This paper attempts to identify the requirement and the development of machine learning-
based mobile big data (MBD) analysis through discussing the insights of challenges in the …

This work presents an effective tool to predict the future trajectories of vehicles when its
current and previous locations are known. We propose a Long Short-Term Memory (LSTM) …

Smart societies require next generation mobility platforms and applications to enable the
needed quality and pace of life. This paper proposes a mobile computing system that …

Driver identification faces various challenges in real-time applications. These challenges
include high dimensional input data, moderate accuracy, scalability issues and need for …

Vehicle-to-pedestrian (V2P) communication can significantly improve pedestrian safety in a
connected vehicle environment. However, pedestrian safety is hindered as pedestrians …