Developing Integrated Mobile Systems for Human Monitoring and Interactive Applications

Date

2021

Authors

Inupakutika, Devasena

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Abstract

The rapid developments in the field of mobile computing have kindled significant interest in sensor-based monitoring and interactions. The knowledge gaps in this context mainly pertain to concerns over: a) data sourcing for contextual information; b) need for integrated environments for pervasive data handling; and c) human-machine interaction. This dissertation presents a set of methods for the design, implementation, and testing of pervasive computing systems supporting human situations, activities, and motions. The purpose of this research is to enhance human monitoring and user mobility through the development of integrated mobile systems and interactive applications. Specifically, human monitoring aspects include disease medication adherence via interactive applications such as mobile apps and chatbots, activity tracking via wearable sensors or smart devices, positioning indoors via wireless local area network (WLAN) signals. In this work, we devised a four-fold framework, a comprehensive integrated system solution, where we independently developed the following facets: a) Data sourcing mechanisms for contextual information provided by the sensing capabilities of: i) existing consumer-grade sensors such as wearable devices, smart scales; ii) self-reported data through interactive mobile applications or chatbots; and iii) new sensor solutions such as multipath data for indoor positioning.
b) Integrated environments for pervasive data collection, monitoring and intervention. c) Interactive applications enabling human-machine interaction for: i) self-reported data sourcing; and ii) intervention and campaign applications. The individual facets of the framework are evaluated and validated through four projects. We contemplate that the comprehensive architecture and analysis of the integrated systems in all the facets of human monitoring presented in this work will provide the critical inputs in directing the advancement of future pervasive computing systems.

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Keywords

Applied deep learning, Human Monitoring, Integrated Systems, Interactive applications, Mobile applications

Citation

Department

Electrical and Computer Engineering