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USJ Macao Hosts BDIOT 2024 Conference: "Advancing e-Health by Big Data and IoT"

2024-09-24

24

Sep

24/09/2024

USJ Macao hosts the 8th International Conference on Big Data and Internet of Things (BDIOT 2024) highlighting innovative e-health solutions that aim to advance global health and improve healthcare delivery.



The University of Saint Joseph (USJ) hosted the 8th International Conference on Big Data and Internet of Things (BDIOT 2024) from September 14-16, 2024. This event, co-sponsored by USJ Macao and the University of Macao, took place at the USJ Green Campus, and aims to explore the critical intersection of Big Data, the Internet of Things (IoT), and their applications in global health.

BDIOT 2024 provided an important platform for worldwide researchers and industry professionals to share their insights on how innovative e-health solutions can enhance healthcare delivery and improve health outcomes worldwide. The conference supports the Macao Government’s “4+1” strategic plan, which emphasises the development of the digital economy and smart city initiatives as key drivers for sustainable growth. By focusing on e-health, the conference supports the broader goal of integrating technology into health services, ultimately benefitting the community and enhancing the quality of life in Macao.

USJ’s Vice-Rector for Research and Innovation, Prof. Alexandre Lobo, participated as the Conference Chair, along with Dean of the Institute for Data Engineering and Science, Prof. George Du, as Programme Chair, and Prof. Ivan Arraut from the Faculty of Business and Law as Programme Co-Chair. Together with the participants, the conference reflected commitment to promoting knowledge and innovation in health technologies, recognising the importance of developments in addressing global health challenges.


 
[Welcoming Address by USJ Vice-Rector Prof. Alexandre Lobo]

[Arumugam Nallanathan on “The Role Artificial Intelligence (Al) in Massive Internet of Things (mloT)”]

[Hai-Ning Liang on “Re-conceptualizing Text Entry for Extended Reality Systems via Spatial Interfaces”]


[Cheng Qiang on “Analysis of deep learning algorithms for emotion classification based on facial expression recognition”]

[Visit of the USJ Laboratory of Applied Neurosciences]