The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations
In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to
combat global climate change. We identify two crucial opportunities that AI offers in this …
combat global climate change. We identify two crucial opportunities that AI offers in this …
Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
Deep learning for spatio-temporal data mining: A survey
With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
A big-data driven approach to analyzing and modeling human mobility trend under non-pharmaceutical interventions during COVID-19 pandemic
During the unprecedented coronavirus disease 2019 (COVID-19) challenge, non-
pharmaceutical interventions became a widely adopted strategy to limit physical movements …
pharmaceutical interventions became a widely adopted strategy to limit physical movements …
The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets
The station-free sharing bike is a new sharing traffic mode that has been deployed in a large
scale in China in the early 2017. Without docking stations, this system allows the sharing …
scale in China in the early 2017. Without docking stations, this system allows the sharing …
A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data
The primary objective of this study is to investigate how the deep learning approach
contributes to citywide short-term crash risk prediction by leveraging multi-source datasets …
contributes to citywide short-term crash risk prediction by leveraging multi-source datasets …
Advances in self-powered sports monitoring sensors based on triboelectric nanogenerators
F Sun, Y Zhu, C Jia, T Zhao, L Chu, Y Mao - Journal of Energy Chemistry, 2023 - Elsevier
The new era of the internet of things brings great opportunities to the field of intelligent
sports. The collection and analysis of sports data are becoming more intelligent driven by …
sports. The collection and analysis of sports data are becoming more intelligent driven by …
An unsupervised learning method with convolutional auto-encoder for vessel trajectory similarity computation
To achieve reliable mining results for massive vessel trajectories, one of the most important
challenges is how to efficiently compute the similarities between different vessel trajectories …
challenges is how to efficiently compute the similarities between different vessel trajectories …
Real-time accident detection: Coping with imbalanced data
Detecting accidents is of great importance since they often impose significant delay and
inconvenience to road users. This study compares the performance of two popular machine …
inconvenience to road users. This study compares the performance of two popular machine …
Transport mode detection based on mobile phone network data: A systematic review
The rapid development in telecommunication networks is producing a huge amount of
information regarding how people (with their mobile devices) move and behave over space …
information regarding how people (with their mobile devices) move and behave over space …