A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution

AH Ganesh, B Xu - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The impact of internal combustion engine-powered automobiles on climate change due to
emissions and the depletion of fossil fuels has contributed to the progress of electrified …

Integration of blockchain technology and federated learning in vehicular (iot) networks: A comprehensive survey

AR Javed, MA Hassan, F Shahzad, W Ahmed, S Singh… - Sensors, 2022 - mdpi.com
The Internet of Things (IoT) revitalizes the world with tremendous capabilities and potential
to be utilized in vehicular networks. The Smart Transport Infrastructure (STI) era depends …

Milestones in autonomous driving and intelligent vehicles: Survey of surveys

L Chen, Y Li, C Huang, B Li, Y Xing… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

[HTML][HTML] Artificial intelligence in healthcare: review and prediction case studies

G Rong, A Mendez, EB Assi, B Zhao, M Sawan - Engineering, 2020 - Elsevier
Artificial intelligence (AI) has been developing rapidly in recent years in terms of software
algorithms, hardware implementation, and applications in a vast number of areas. In this …

Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges …

P Dong, J Zhao, X Liu, J Wu, X Xu, Y Liu… - … and Sustainable Energy …, 2022 - Elsevier
The rapid development of intelligent and connected technologies is conducive to the
efficient energy utilization of hybrid electric vehicles (HEVs). However, most energy …

Federated learning in vehicular edge computing: A selective model aggregation approach

D Ye, R Yu, M Pan, Z Han - IEEE Access, 2020 - ieeexplore.ieee.org
Federated learning is a newly emerged distributed machine learning paradigm, where the
clients are allowed to individually train local deep neural network (DNN) models with local …

Applications of artificial intelligence and big data analytics in m‐health: A healthcare system perspective

ZF Khan, SR Alotaibi - Journal of healthcare engineering, 2020 - Wiley Online Library
Mobile health (m‐health) is the term of monitoring the health using mobile phones and
patient monitoring devices etc. It has been often deemed as the substantial breakthrough in …

Triboelectric nanogenerator as next-generation self-powered sensor for cooperative vehicle-infrastructure system

Y Pang, X Zhu, C Lee, S Liu - Nano Energy, 2022 - Elsevier
Triboelectric nanogenerators (TENG) have progressed over the years, bringing significant
benefits to self-powered sensing owing to the compelling features of high sensitivity, low …

Explainable artificial intelligence (xai) for intrusion detection and mitigation in intelligent connected vehicles: A review

CI Nwakanma, LAC Ahakonye, JN Njoku… - Applied Sciences, 2023 - mdpi.com
The potential for an intelligent transportation system (ITS) has been made possible by the
growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration …

Investigating the prospect of leveraging blockchain and machine learning to secure vehicular networks: A survey

M Dibaei, X Zheng, Y Xia, X Xu, A Jolfaei… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
With recent developments in communication technologies, vehicular networks have become
a reality with various applications. However, the cybersecurity aspect of vehicular networks …