This project is financed with state support from the Technology Agency of the Czech Republic and the Ministry of Industry and Trade of the Czech Republic within the TREND Programme.
This project was funded under the National Recovery Plan from the European Recovery and Resilience Facility.
www.tacr.cz
Research useful for society.

Project detail

Indoor environment quality monitoring of buildings using odor sensors and artificial intelligence

Duration: 01.01.2023 — 31.12.2025

Funding resources

Technologická agentura ČR - 7. veřejná soutěž - Program průmyslového výzkumu a experimentálního vývoje TREND

- whole funder

On the project

Předmětem projektu je výzkum a vývoj prototypu pro monitorování bezpečnosti stavu ovzduší v průmyslových objektech s použitím pokročilých senzorů a software pro vizualizaci a řízení sítě senzorů s použitím webového uživatelského rozhraní.

Description in English
The aim of the project is research and development of a prototype monitoring device for continuous monitoring of indoor air quality and safety in buildings and industrial buildings using advanced sensors and development of evaluation software for data analysis from these sensors using artificial intelligence, visualization of results and sensors control using the web user interface. The designed components will be interconnected via a 5G network, through which the measured data will be sent to the cloud storage, where they will be continuously analyzed. This will make it possible to continuously monitor the condition of the building's indoor environment and draw attention to the occurrence of dangerous concentrations of undesirable substances in the air and other risk conditions.

Keywords
elektronický nos, umělá inteligence, senzory, 5G

Key words in English
sensors, electronic nose, artificial intelligence

Mark

FW07010015

Default language

Czech

People responsible

Jonák Martin, Ing., Ph.D. - fellow researcher
Burget Radim, doc. Ing., Ph.D. - principal person responsible

Units

Department of Telecommunications
- beneficiary (2022-05-16 - not assigned)

Results

RASHID, S.; KARNATI, M.; AGGARWAL, G.; DUTTA, M.; SIKORA, P.; BURGET, R. Attention-based Multiscale Deep Neural Network for Diagnosis of Polycystic Ovary Syndrome Using Ovarian Ultrasound Images. In 2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). International Congress on Ultra Modern Telecommunications and Control Systems and Workshops. Ghent: IEEE Computer Society, 2023. p. 44-49. ISBN: 979-8-3503-9328-6. ISSN: 2157-023X.
Detail

SIKORA, P.; KIAC, M.; COSTA, P.; MOLINERO-GARCÍA, A.; GORSKA, M. Automatic image analysis applied to the recognition of quartz surface microtextures using neural network. MICRON, 2024, vol. 182, no. July 2024, p. 1-10. ISSN: 1878-4291.
Detail

KŘÍŽ, P.; SIKORA, P.; ŘÍHA, K.; BURGET, R. Unveiling the Smell Inspector and Machine Learning Methods for Smell Recognition. In 2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). Ghent: IEEE Computer Society, 2023. p. 182-187. ISBN: 979-8-3503-9328-6.
Detail

Responsibility: Burget Radim, doc. Ing., Ph.D.