Data analytics and aggregation platform for comprehensive city-scale ai modeling
Issued Date
2023-01-23
Resource Type
ISSN
09226389
Scopus ID
2-s2.0-85149173713
Journal Title
Frontiers in Artificial Intelligence and Applications
Volume
364
Start Page
92
End Page
109
Rights Holder(s)
SCOPUS
Bibliographic Citation
Frontiers in Artificial Intelligence and Applications Vol.364 (2023) , 92-109
Suggested Citation
Sornlertlamvanich V., Iamtrakul P., Horanont T., Hnoohom N., Wongpatikaseree K., Yuenyong S., Angkapanichkit J., Piyapasuntra S., Lopkerd P., Prasertsuk S., Busayarat C., Raungratanaamporn I.S., Deepaisarn S., Charoenporn T. Data analytics and aggregation platform for comprehensive city-scale ai modeling. Frontiers in Artificial Intelligence and Applications Vol.364 (2023) , 92-109. 109. doi:10.3233/FAIA220495 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/81784
Title
Data analytics and aggregation platform for comprehensive city-scale ai modeling
Other Contributor(s)
Abstract
This research proposes an AI platform for data sharing across multiple domains. Since the data in the smart city concept are domain-specific processed, the existing smart city architecture is suffered from cross-domain data interpretation. To go beyond the digital transformation efforts in smart city development, the AI city is created on the architecture of cross-domain data connectivity and transform learning in the machine learning paradigm. In this research, the health and human behavioral data are targeted on human traceability and contactless technologies. To measure the inhabitants quality of life (QoL), the primary emotion expression study is conducted to interpret the emotional states and the mental health of people in the urbanized city. The results of information augmentation draw attention to the immersive visualization of the Thammasat model.