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.

Popis anglicky
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.

Klíčová slova
elektronický nos, umělá inteligence, senzory, 5G

Klíčová slova anglicky
sensors, electronic nose, artificial intelligence

FW07010015

čeština

Burget Radim, doc. Ing., Ph.D. - hlavní řešitel
Jonák Martin, Ing., Ph.D. - spoluřešitel

Ústav telekomunikací
- odpovědné pracoviště (16.5.2022 - nezadáno)
Ústav telekomunikací
- příjemce (16.5.2022 - nezadáno)

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

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

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