[HTML][HTML] State of data platforms for connected vehicles and infrastructures

KL Lim, J Whitehead, D Jia, Z Zheng - Communications in transportation …, 2021 - Elsevier
The continuing expansion of connected and electro-mobility products and services has led
to their ability to rapidly generate very large amounts of data, leading to a demand for …

A traffic data clustering framework based on fog computing for VANETs

MLM Peixoto, AHO Maia, E Mota, E Rangel… - Vehicular …, 2021 - Elsevier
Abstract Vehicular Ad-hoc Networks (VANETs) are based on vehicle to infrastructure
communications in which the vehicles periodically broadcast information to update a Road …

Songdriver: Real-time music accompaniment generation without logical latency nor exposure bias

Z Wang, K Zhang, Y Wang, C Zhang, Q Liang… - Proceedings of the 30th …, 2022 - dl.acm.org
Real-time music accompaniment generation has a wide range of applications in the music
industry, such as music education and live performances. However, automatic real-time …

Ananke: a streaming framework for live forward provenance

D Palyvos-Giannas, B Havers… - Proceedings of the …, 2020 - dl.acm.org
Data streaming enables online monitoring of large and continuous event streams in Cyber-
Physical Systems (CPSs). In such scenarios, fine-grained backward provenance tools can …

A new pattern representation method for time-series data

R Rezvani, P Barnaghi… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The rapid growth of Internet of Things (IoT) and sensing technologies has led to an
increasing interest in time-series data analysis. In many domains, detecting patterns of IoT …

The role of event-time order in data streaming analysis

V Gulisano, D Palyvos-Giannas, B Havers… - Proceedings of the 14th …, 2020 - dl.acm.org
The data streaming paradigm was introduced around the year 2000 to overcome the
limitations of traditional store-then-process paradigms found in relational databases (DBs) …

[HTML][HTML] Survey: time-series data preprocessing: a survey and an empirical analysis

A Tawakuli, B Havers, V Gulisano, D Kaiser… - Journal of Engineering …, 2024 - Elsevier
Data are naturally collected in their raw state and must undergo a series of preprocessing
steps to obtain data in their input state for Artificial Intelligence (AI) and other applications …

Building a government-owned open data platform for connected and autonomous vehicles

H Deng, Q Hu, CH Guan, YS Chen, M Menendez - Cities, 2024 - Elsevier
The growing recognition of the societal implications stemming from technological
advancements highlights the need for innovative governance approaches, particularly in …

DRIVEN: A framework for efficient Data Retrieval and clustering in Vehicular Networks

B Havers, R Duvignau, H Najdataei, V Gulisano… - Future Generation …, 2020 - Elsevier
The growing interest in data analysis applications for Cyber–Physical Systems stems from
the large amounts of data such large distributed systems sense in a continuous fashion. A …

Mad-c: Multi-stage approximate distributed cluster-combining for obstacle detection and localization

A Keramatian, V Gulisano, M Papatriantafilou… - Journal of Parallel and …, 2021 - Elsevier
The upcoming digitalization in the context of Cyber–physical Systems (CPS), enabled
through Internet-of-Things (IoT) infrastructures, require efficient methods for distributed …