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Full-Text Articles in Physical Sciences and Mathematics

Identifying Elderlies At Risk Of Becoming More Depressed With Internet-Of-Things, Jiajue Ou, Huiguang Liang, Hwee Xian Tan Jul 2018

Identifying Elderlies At Risk Of Becoming More Depressed With Internet-Of-Things, Jiajue Ou, Huiguang Liang, Hwee Xian Tan

Research Collection School Of Computing and Information Systems

Depression in the elderly is common and dangerous. Current methods to monitor elderly depression, however, are costly, time-consuming and inefficient. In this paper, we present a novel depression-monitoring system that infers an elderly’s changes in depression level based on his/her activity patterns, extracted from wireless sensor data. To do so, we build predictive models to learn the relationship between depression level changes and behaviors using historical data. We also deploy the system for a group of elderly, in their homes, and run the experiments for more than one year. Our experimental study gives encouraging results, suggesting that our IoT system …


Technology-Enabled Medication Adherence For Seniors Living In The Community: Experiences, Lessons, And The Road Ahead, Hwee Xian Tan, Hwee-Pink Tan, Huiguang Liang Jul 2018

Technology-Enabled Medication Adherence For Seniors Living In The Community: Experiences, Lessons, And The Road Ahead, Hwee Xian Tan, Hwee-Pink Tan, Huiguang Liang

Research Collection School Of Computing and Information Systems

Medication non-adherence in seniors can lead to severe health complications, including morbidity, mortality and decreased quality of life. In view of ageing populations worldwide, there is significant interest among the healthcare sector and researchers to improve medication adherence rates for seniors. However, existing studies in the literature focus primarily on identifying the predictors of medication non-adherence. In this paper, we present our work on technology-enabled medication adherence for 24 community-dwelling seniors over a period of more than 2 years. We leverage Internet of Things (IoT) devices to track inferred medication consumption in the seniors’ homes, and provide quasi real-time alerts …


A Simplified Secure Programming Platform For Internet Of Things Devices, Halim Burak Yesilyurt Jun 2018

A Simplified Secure Programming Platform For Internet Of Things Devices, Halim Burak Yesilyurt

FIU Electronic Theses and Dissertations

The emerging Internet of Things (IoT) revolution has introduced many useful applications that are utilized in our daily lives. Users can program these devices in order to develop their own IoT applications; however, the platforms and languages that are used during development are abounding, complicated, and time-consuming. The software solution provided in this thesis, PROVIZ+, is a secure sensor application development software suite that helps users create sophisticated and secure IoT applications with little software and hardware experience. Moreover, a simple and efficient domain-specific programming language, namely Panther language, was designed for IoT application development to unify existing programming languages. …


Performance Characterization Of Deep Learning Models For Breathing-Based Authentication On Resource-Constrained Devices, Jagmohan Chauhan, Jathusan Rajasegaran, Surang Seneviratne, Archan Misra, Aruan Seneviratne, Youngki Lee Apr 2018

Performance Characterization Of Deep Learning Models For Breathing-Based Authentication On Resource-Constrained Devices, Jagmohan Chauhan, Jathusan Rajasegaran, Surang Seneviratne, Archan Misra, Aruan Seneviratne, Youngki Lee

Research Collection School Of Computing and Information Systems

Providing secure access to smart devices such as mobiles, wearables and various other IoT devices is becoming increasinglyimportant, especially as these devices store a range of sensitive personal information. Breathing acoustics-based authentication offers a highly usable and possibly a secondary authentication mechanism for such authorized access, especially as it canbe readily applied to small form-factor devices. Executing sophisticated machine learning pipelines for such authenticationon such devices remains an open problem, given their resource limitations in terms of storage, memory and computational power. To investigate this possibility, we compare the performance of an end-to-end system for both user identification anduser verification …