[HTML][HTML] Towards federated learning and multi-access edge computing for air quality monitoring: literature review and assessment

S Abimannan, ESM El-Alfy, S Hussain, YS Chang… - Sustainability, 2023 - mdpi.com
Systems for monitoring air quality are essential for reducing the negative consequences of
air pollution, but creating real-time systems encounters several challenges. The accuracy …

[HTML][HTML] A brief review on flexible electronics for IoT: Solutions for sustainability and new perspectives for designers

G Scandurra, A Arena, C Ciofi - Sensors, 2023 - mdpi.com
The Internet of Things (IoT) is gaining more and more popularity and it is establishing itself in
all areas, from industry to everyday life. Given its pervasiveness and considering the …

Data reliability and fault diagnostic for air quality monitoring station based on low cost sensors and active redundancy

S Poupry, K Medjaher, C Béler - Measurement, 2023 - Elsevier
Air pollution is both an environmental and societal issue. Conventional air quality monitoring
involves costly measuring stations that demand specialized personnel. A more affordable …

[HTML][HTML] AirMLP: A Multilayer Perceptron Neural Network for Temporal Correction of PM2. 5 Values in Turin

M Casari, L Po, L Zini - Sensors, 2023 - mdpi.com
In recent times, pollution has emerged as a significant global concern, with European
regulations stipulating limits on PM 2.5 particle levels. Addressing this challenge …

Deep learning approach to forecast air pollution based on novel hourly index

G Narkhede, A Hiwale - Physica Scripta, 2023 - iopscience.iop.org
Air pollution is a pressing concern that the entire world is striving to combat. Among air
pollutants, particulate matter poses a significant threat to human health. The Sustainable …

A Data-Driven Supervised Machine Learning Approach to Estimating Global Ambient Air Pollution Concentrations With Associated Prediction Intervals

LJ Berrisford, H Barbosa, R Menezes - arXiv preprint arXiv:2402.10248, 2024 - arxiv.org
Global ambient air pollution, a transboundary challenge, is typically addressed through
interventions relying on data from spatially sparse and heterogeneously placed monitoring …

[HTML][HTML] Predicting the Posture of High-Rise Building Machines Based on Multivariate Time Series Neural Network Models

X Pan, J Huang, Y Zhang, Z Zuo, L Zhang - Sensors, 2024 - mdpi.com
High-rise building machines (HBMs) play a critical role in the successful construction of
super-high skyscrapers, providing essential support and ensuring safety. The HBM's …

[HTML][HTML] A Comparative Study of Deep-Learning Autoencoders (DLAEs) for Vibration Anomaly Detection in Manufacturing Equipment

S Lee, AB Kareem, JW Hur - Electronics, 2024 - mdpi.com
Speed reducers (SR) and electric motors are crucial in modern manufacturing, especially
within adhesive coating equipment. The electric motor mainly transforms electrical power …

[HTML][HTML] Anomaly Detection in Weather Phenomena: News and Numerical Data-Driven Insights into the Climate Change in Romania's Historical Regions

A Bâra, AG Văduva, SV Oprea - International Journal of Computational …, 2024 - Springer
The extreme phenomena have been increased recently in frequency and intensity causing
numerous damage that cannot be neglected by residents, local authorities and social media …

Contribution à la conception et à la mise en oeuvre d'un système de surveillance de la qualité de l'air: application à la surveillance de la qualité de l'air dans les …

S Poupry - 2023 - theses.hal.science
Cette thèse vise à mettre en place une démarche scientifique de surveillance et d'action de
prévention de la qualité de l'air dans des zones dépourvues de stations de mesure …