Geofencing Implement For Self-Monitoring Wandering Behavior And Sharing Location In Realtime With Firebase

Geofencing is an advanced technique that collects geolocation data in order to test whether a path of travel has crossed into or out of a geographical area represented by a geometric shape. The Firebase Backend-as-a-Service (Baas) supports Android applications with data store and realtime share capa...

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Bibliographic Details
Published in2023 IEEE Cloud Summit pp. 84 - 89
Main Authors Flynn, Dennis, Kimm, Haklin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2023
Subjects
Alzheimer's
Behavioral sciences
Geofence
Geriatrics
Location Based Service
Medical services
Operating systems
Photography
Realtime Firebase
Satellite images
Shape
Smart phone
Web services
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Summary:Geofencing is an advanced technique that collects geolocation data in order to test whether a path of travel has crossed into or out of a geographical area represented by a geometric shape. The Firebase Backend-as-a-Service (Baas) supports Android applications with data store and realtime share capabilities. These techniques are applied in location based services and areas of human activity recognition research, especially for problems in medicine like dementia/Alzheimer patients, HIV transmission prevention, and monitoring COVID-19 patients' movements. In this paper, we present an Android application with a two-stage geofencing trigger used to initiate communication with the Firebase BaaS and trigger features that address wandering behavior in geriatric healthcare patients. The proposed tool uses the Android Location API, the Google Maps SDK and the Firebase BaaS. In order to integrate geofencing into our existing Firebase feature platform, this paper investigates use of the Android Location Library's Geofence. Our toolchain and methods for analyzing geofence location data to address wandering behavior were preferred after review of related research and comparison with existing commercial solutions. Lastly, our geofence integration tool is developed, implemented and field-tested in order to calibrate user options for the primary geofence parameters. We also provide analysis and discussion of our geofencing optimizations in the context of geriatric healthcare.
DOI:10.1109/CloudSummit57601.2023.00020