Improving WLAN Fingerprinting for Indoor Positioning: The Role of Signal Receiving Factors

Mrindoko Rashid Nicholaus

Mrindoko Rashid Nicholaus Department of Computer Science and Engineering, Mbeya University of Science and Technology, Tanzania

Abstract

Purpose – This study intends to analyze the critical factors affecting the accuracy of WLAN fingerprinting in Indoor Positioning Systems (IPSs) from the perspective of radio signal reception. Utilizing an Ishikawa diagram, the research aims to provide insights into the various environmental and technical factors that can degrade the performance of WLAN fingerprinting, which leverages the Received Signal Strength Indicator (RSSI) from Wi-Fi signals to estimate user location.

Method – The study employs an experimental approach, examining the effects of sample size, receiver models, and operator elevation on positioning accuracy. The approach involves controlled experiments to isolate the impact of each factor, followed by statistical analysis to identify trends and correlations.

Results – The study reveals that sample size directly correlates with accuracy, with larger samples improving precision. Receiver model variability introduces significant disparities in signal interpretation, impacting location estimation reliability. Operator elevation further complicates signal propagation, emphasizing the importance of standardizing deployment practices for consistent performance.

Conclusion – The study concludes that addressing these critical factors can substantially enhance the effectiveness of WLAN fingerprinting-based indoor positioning systems

Recommendations – To enhance WLAN fingerprinting accuracy and reliability in Indoor Positioning Systems, it is momentous to optimize sample sizes during calibration, standardize receiver equipment, and consider elevation effects in system design. These strategies can significantly improve location-based services across various applications and environments.

Research Implications – This study extends to both academic and practical domains. For researchers, it offers a structured framework to explore environmental impacts on indoor positioning system performance. Practitioners can leverage these insights to develop more robust and accurate indoor positioning systems, fostering wider adoption in applications such as navigation, asset tracking, and emergency response.

Author Biography

Mrindoko Rashid Nicholaus, Department of Computer Science and Engineering, Mbeya University of Science and Technology, Tanzania

Mrindoko R. Nicholaus is a lecturer in the Department of Computer Engineering at Mbeya University of Science and Technology (formerly MIST). He holds a Ph.D. in ICT from The Open University of Tanzania (2022), an MSc in Electronics Engineering and Information Technology from the University of Dar es Salaam (2015), and a BEng in Computer Engineering from Dar es Salaam Institute of Technology (2009). His research interests include Artificial Intelligence, Embedded Systems, Location-Based Services, Cybersecurity, and ICT for Development.