Thesis Committee Member(s)
Shari Plantz-Masters, Ph.D; Robert Sjodin
College for Professional Studies
MS Information Technology Management
School of Computer & Information Science
Thesis - Open Access
Number of Pages
Bluetooth Low Energy beacon devices, typically operating on coin cell batteries, have emerged as key components of micro-location wireless sensor networks. To design efficient and reliable networks, designers require tools for predicting battery and beacon lifetime, based on design parameters that are specific to micro-location applications. This design science research contributes to the implementation of an artifact functioning as a predictive tool for coin cell battery lifetime when powering Bluetooth Low Energy beacon devices. Building upon effective and corroborated components from other researchers, the Beacon Lifetime Model 1.0 was developed as a spreadsheet workbook, providing a user interface for designers to specify parameters, and providing a predictive engine to predict coin cell battery lifetime. Results showed that the measured and calculated predictions were consistent with those derived through other methodologies, while providing a uniquely extensible user interface which may accommodate future work on emerging components. Future work may include research on real world scenarios, as beacon devices are deployed for robust micro-location applications. Future work may also include improved battery models that capture increasingly accurate performance under micro-location workloads. Beacon Lifetime Model 1.x is designed to incorporate those emerging components, with Beacon Lifetime Model1.0 serving as the initial instantiation of this design science artifact.
Date of Award
© Donna Auguste
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Auguste, Donna, "Model for Predicting Bluetooth Low Energy Micro-Location Beacon Coin Cell Battery Lifetime" (2015). All Regis University Theses. 11.