Health crisis situation awareness using mobile multiple modalities

Grewe, Lynne L.; Asati, Subhangi; Choudhary, Shivali; Gallegos, Emmanuel; Gupta, Divya; House, Maithri E.; Kes, Cemil; Ngyuen, Jamie; Patel, Bhumit A.; Patel, Kunjkumar; Jain, Dikshant Pravin; Shahshahani, Jake; Aguilera, Phillip; Shahshahani, Allen; Weginwar, Manasi Rajiv; Hu, Chengzhi

doi:10.1117/12.2587544

Cited by 1 publication

(1 citation statement)

References 10 publications

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“…Among the developments include methods of human occupancy [120]. Situations can arise when edge devices [121] are mobile platforms [122] which require measures of interpretability to ensure patients being tracked are provided adequate knowledge relative to their needs [123].…”

Section: Digital Twin For Healthcarementioning

confidence: 99%

Digital twin meets information fusion: panel summary

Blasch,

Chen,

Chen

et al. 2024

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII

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Within the recent years, the concept of Digital Twins (DT) emerged to support digital engineering physical-systems design in the processing and analysis of device components, data flows, and networked systems. As an element of systems engineering, the DT serves as a method for life cycle management for operations and maintenance through monitoring, diagnostics, and prognostics. Key to DT methods is the use of distributed sensors to monitor the system and determine the functioning with the use of physical design information, such as a series of distributed edge sensors and the layout of a physical electrical grid. While industries like industrial manufacturing, electrical power, space systems, and healthcare maintenance have embraced DT; other groups are utilizing the concept for analysis. Given that a large number of sensors are used to gather data on the health of system, it is natural that data fusion, estimation theory, and signals processing support digital twin fusion (DTwF); but there are a variety of challenges such as big data, distribution fusion, and edge analytics. The panel will discuss areas in which data and information fusion techniques enhance DT applications.

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