Deepsense: A unified deep learning framework for time-series mobile sensing data processing
Mobile sensing and computing applications usually require time-series inputs from sensors,
such as accelerometers, gyroscopes, and magnetometers. Some applications, such as …
such as accelerometers, gyroscopes, and magnetometers. Some applications, such as …
Gamified mobile applications for improving driving behavior: A systematic mapping study
Many research works and official reports approve that irresponsible driving behavior on the
road is the main cause of accidents. Consequently, responsible driving behavior can …
road is the main cause of accidents. Consequently, responsible driving behavior can …
Can Smartphones Serve as an Instrument for Driver Behavior of Intelligent Transportation Systems Research? A Systematic Review: Challenges, Motivations, and …
The increasing number of road accidents is a major issue in many countries. Studying
drivers' behaviour is essential to identify the key factors of these accidents. As improving …
drivers' behaviour is essential to identify the key factors of these accidents. As improving …
Rdeepsense: Reliable deep mobile computing models with uncertainty estimations
Recent advances in deep learning have led various applications to unprecedented
achievements, which could potentially bring higher intelligence to a broad spectrum of …
achievements, which could potentially bring higher intelligence to a broad spectrum of …
From centralized management to edge collaboration: A privacy-preserving task assignment framework for mobile crowdsensing
The flexible combination of pervasive portable smart devices and omnipresent high-speed
access infrastructures has revolutionized the data sensing and knowledge acquisition in …
access infrastructures has revolutionized the data sensing and knowledge acquisition in …
Vemo: Enabling transparent vehicular mobility modeling at individual levels with full penetration
Understanding and predicting real-time vehicle mobility patterns on highways are essential
to address traffic congestion and respond to the emergency. However, almost all existing …
to address traffic congestion and respond to the emergency. However, almost all existing …
EXIMIUS: A measurement framework for explicit and implicit urban traffic sensing
Urban traffic sensing has been investigated extensively by different real-time sensing
approaches due to important applications such as navigation and emergency services …
approaches due to important applications such as navigation and emergency services …
coSense: Collaborative urban-scale vehicle sensing based on heterogeneous fleets
The real-time vehicle sensing at urban scale is essential to various urban services. To date,
most existing approaches rely on static infrastructures (eg, traffic cameras) or mobile …
most existing approaches rely on static infrastructures (eg, traffic cameras) or mobile …
Speedadv: Enabling green light optimized speed advisory for diverse traffic lights
L Ding, D Zhao, B Zhu, Z Wang, C Tan… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Green Light Optimized Speed Advisory (GLOSA) systems have emerged to allow drivers to
pass traffic lights during a green interval. However, various adaptive and intelligent traffic …
pass traffic lights during a green interval. However, various adaptive and intelligent traffic …
Pragmatic cyber physical systems design based on parametric models
M García-Valls, D Perez-Palacin… - Journal of Systems and …, 2018 - Elsevier
The adaptive nature of cyber physical systems (CPS) comes from the fact that they are
deeply immersed in the physical environments that are inherently dynamic. CPS also have …
deeply immersed in the physical environments that are inherently dynamic. CPS also have …