Date of Award

8-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Discipline

Electrical Engineering

Abstract

The burgeoning realm of the Internet of Things (IoT) calls for advanced communication networks that can support an ever-increasing number of connected devices. Among these, Low Power Wide Area Networks (LPWANs), specifically LoRaWAN technology, have emerged as frontrunners due to their long-range, low-power capabilities, ideally suiting IoT's expansive nature. This dissertation presents a comprehensive study on enhancing LoRaWAN technology to overcome the existing limitations in geolocation accuracy and data aggregation efficiency. The work is set against the backdrop of the technology's vulnerability to signal attenuation in obstacle-rich environments and its challenges in scaling to accommodate dense networks without performance degradation. Moreover, the security of data transmission within such networks is scrutinized, with a specific focus on enhancing encryption protocols and visualization tools for more effective network management. The dissertation's contributions are manifold, including the development of a private server framework utilizing Advanced Encryption Standard (AES) to fortify data transmission security. Furthermore, the integration of Grafana mapping solutions with LoRaWAN servers is explored to enable sophisticated data visualization and analytics. An adaptive algorithm is proposed to dynamically adjust the spreading factor based on signal strength indicators, improving network coverage and throughput. A rebroadcast location-unaware protocol specifically optimized for mesh network conditions in IoT domains is also introduced alongside a scalable geofencing system for remote monitoring. Central to this study is the innovative approach to geolocation, which eschews traditional GPS reliance. By harnessing parameters like Received Signal Strength Indicator (RSSI), Signal-to-Noise Ratio (SNR), and Time Difference of Arrival (TDOA), combined with machine learning and location triangulation methods, the research aims to conserve power while ensuring precise location tracking. This dissertation is organized into eight chapters, methodically detailing the problem statement, literature review, methodology, implementation, results, and conclusions. It culminates in suggesting future research directions that continue to push the boundaries of LoRaWAN technology, paving the way for its broader application in diverse IoT domains.

Index Terms- Geolocation Accuracy, IoT, LoRaWAN,

Committee Chair/Advisor

Annamalai Annamalai

Committee Co-Chair:

Mohamed Chouikha

Committee Member

Ahmed A. Ahmed

Committee Member

Lijun Qian

Committee Member

Pamela Obiomon

Publisher

Prairie View A&M University

Rights

© 2021 Prairie View A & M University

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Date of Digitization

9/13/2024

Contributing Institution

John B Coleman Library

City of Publication

Prairie View

MIME Type

Application/PDF

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