Physical security and safety of IoT equipment: A survey of recent advances and opportunities
The connectivity and intelligence of Internet of Things (IoT) equipment offer improved
services, but several technical challenges have emerged in recent years that hinder the …
services, but several technical challenges have emerged in recent years that hinder the …
Driver behavior modeling toward autonomous vehicles: Comprehensive review
Driver behavior models have been used as input to self-coaching, accident prevention
studies, and develo** driver-assisting systems. In recent years, driver behavior …
studies, and develo** driver-assisting systems. In recent years, driver behavior …
Human-factors-in-driving-loop: Driver identification and verification via a deep learning approach using psychological behavioral data
Driver identification has been popular in the field of driving behavior analysis, which has a
broad range of applications in anti-thief, driving style recognition, insurance strategy, and …
broad range of applications in anti-thief, driving style recognition, insurance strategy, and …
Driving behavior analysis guidelines for intelligent transportation systems
The advent of in-vehicle networking systems as well as state-of-the-art sensors and
communication technologies have facilitated the collection of large volume and almost real …
communication technologies have facilitated the collection of large volume and almost real …
Explainable artificial intelligence (xai) in insurance
Explainable Artificial Intelligence (XAI) models allow for a more transparent and
understandable relationship between humans and machines. The insurance industry …
understandable relationship between humans and machines. The insurance industry …
Feature selection for driving style and skill clustering using naturalistic driving data and driving behavior questionnaire
Y Chen, K Wang, JJ Lu - Accident Analysis & Prevention, 2023 - Elsevier
Driver's driving style and driving skill have an essential influence on traffic safety, capacity,
and efficiency. Through clustering algorithms, extensive studies explore the risk assessment …
and efficiency. Through clustering algorithms, extensive studies explore the risk assessment …
A wavelet-based real-time fire detection algorithm with multi-modeling framework
This paper presents a wavelet-based real-time automated fire detection algorithm that takes
into consideration the multi-resolution property of the wavelet transforms. Unlike …
into consideration the multi-resolution property of the wavelet transforms. Unlike …
Siamese temporal convolutional networks for driver identification using driver steering behavior analysis
Driver identification has shown sustainable development in recent years in a wide variety of
applications including but not limited to security, personalization, fleet management …
applications including but not limited to security, personalization, fleet management …
Hybrid deep learning models for road surface condition monitoring
The goal of road surface condition (RSC) monitoring is to ensure transport safety and driving
comfort. Motion sensors from a smartphone are usually used for RSC monitoring. These …
comfort. Motion sensors from a smartphone are usually used for RSC monitoring. These …
A driving behavior risk classification framework via the unbalanced time series samples
H Zhu, R **ao, J Zhang, J Liu, C Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Driving risk classification is usually used for evaluating and reducing traffic accidents. It is of
great significance to improve urban traffic problems, such as traffic jams and road accidents …
great significance to improve urban traffic problems, such as traffic jams and road accidents …