MyAQI
Author:
Affiliation:
1. Deakin University, Melbourne, Australia
2. Swinburne University, Melbourne, Australia
3. Université de Lorraine, CRAN, UMR, (CNRS), Campus Sciences, BP, Vandoeuvre-lès-Nancy, France
4. Luleå University of Technology, Skellefteå, Sweden
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3365871.3365884
Reference15 articles.
1. Tamara Belyakhina B Arkady Zaslavsky Karan Mitra and Saguna Saguna. 2013. DisCPAQ: Distributed Context Acquisition and Reasoning for Personalized Indoor Air Quality Monitoring in IoT-Based Systems Vol. 8121. Springer Berlin Heidelberg 75--86. https://doi.org/10.1007/978-3-642-40316-3 Tamara Belyakhina B Arkady Zaslavsky Karan Mitra and Saguna Saguna. 2013. DisCPAQ: Distributed Context Acquisition and Reasoning for Personalized Indoor Air Quality Monitoring in IoT-Based Systems Vol. 8121. Springer Berlin Heidelberg 75--86. https://doi.org/10.1007/978-3-642-40316-3
2. AirCloud
3. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015
4. Urban air pollution alert service for smart cities
5. Robert B Haber and David A Mcnabb. 1990. Visualization ldioms: A Conceptual Model for Scientific Visualization Systems. Visualization in scientific computing 74 (1990) 93. Robert B Haber and David A Mcnabb. 1990. Visualization ldioms: A Conceptual Model for Scientific Visualization Systems. Visualization in scientific computing 74 (1990) 93.
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1. Optimizing Forecasted Activity Notifications with Reinforcement Learning;Sensors;2023-07-19
2. A novel hybrid algorithm with static and dynamic models for air quality index forecasting;Nonlinear Dynamics;2023-05-20
3. Machine learning algorithms to forecast air quality: a survey;Artificial Intelligence Review;2023-02-16
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