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Incorporating ubiquitous data in air pollution forecast model for performance improvement

Project Member(s): Ha, Q.

Funding or Partner Organisation: NSW Department of Planning, Industry and Environment
NSW Department of Planning, Industry and Environment

Start year: 2022

Summary: This proposal presents the next step in the collaboration between UTS and DPIE -Atmospheric Research to focus on the following deliverables: (i) Model configuration analysis, involving an optimisation process for improving versatility, (ii) Uncertainty management and reliability enhancement with the developed LSTM-BNN technique, taking LWSN and CMAQ data into account, and (iii) Implementation of the developed algorithms into the prototype WebApp demonstrator.

Publications:

Nguyen, HAD, Le, TH, Ha, QP & Azzi, M 1970, 'Deep learning for construction emission monitoring with low-cost sensor network', Proceedings of the 40th International Symposium on Automation and Robotics in Construction, 40th International Symposium on Automation and Robotics in Construction, International Association for Automation and Robotics in Construction (IAARC).
View/Download from: Publisher's site

FOR Codes: Air quality, atmosphere and weather, Automation engineering, Network engineering