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Masters Project based on real time indoor location tracking using UWB technology and AI algorithms to predict room selection for door actuation

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ee580_meng

The contents of this repository are the source code and supporting documentation submitted in partial fulfilment of the requirements of the master’s degree in Electronic and Computer Engineering (MECE) of Dublin City University

All content contained within this repository is my own unless stated (and cited) otherwise Documentation can be found within the appendic folder, Code residing on the actuator node within the similarly named folder Code at the root level running on the simulation node/PC

Any issues or queries regarding the materials please reach me at aisling.lee32@mail.dcu.ie Project supervised by Dr Derek Molloy

All appendix materials attached can also be found here if there are issues with accessing them https://1drv.ms/u/s!ApgORorE7L4PiMo7hFZsnK7LDfCSRw?e=Wkg4vy Files contained in appendix

AislingLee_20216371_LiteratureReview OralPresentation_slides.pdf

AislingLee_20216371_LiteratureReview OralPresentation_Video_v2.mp4* Too large to uplaod here is located in onedrive link above

EE580_AislingLee_DevelopmentLog.pdf

EE580_AislingLee_E2E_FullProjectDemo.mp4

EE580_AislingLee_LiteratureReview.pdf

EE580_AislingLee_MEng Project Research Log.pdf

EE580_AislingLee_ProjectPlan.pdf

EE580_AislingLee_RiskAssesment.pdf

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Masters Project based on real time indoor location tracking using UWB technology and AI algorithms to predict room selection for door actuation

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