Objectives
The industrial PhD project aims to develop new chemoresistive sensors with enhanced stability, selectivity, and ultralow power consumption. To this end, new gas sensitive materials will be synthesized and fully characterised (morphology, composition and gas sensing properties). The aerosol-assisted chemical vapour deposition and the atmospheric pressure chemical vapour deposition methods will be considered for achieving three-dimensional assemblies (sponge-like) of two-dimensional transition metal dichalcogenides (2D TMDs) doped with clusters of noble metals. These newly designed sensors will be used to create an IoT gas sensing network capable of monitoring volatile organic compounds and gas released during human indoor activities. The project will also explore novel AI-based approaches to enhance sensor selectivity and manage the inevitable missing sensor data in any continuous monitoring system.
Our Role
NVISION leads the artificial intelligence part of the Industrial PhD project and investigates imputation methods backed with advanced Machine and Deep Learning techniques to implement data prediction strategies to handle, in an efficient way, the issues of missing data in long continuous data acquisition exercises, in which unexpected communication breaks or temporary sensor malfunction may occur such as in elderly living facilities.
Funding
Generalitat de Catalunya, Agència per a la Competitivitat de l’Empresa (ACCIÓ)
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Funded by ACCIÓ (GenCat) – Catalan Agency for Business Competitiveness