Titlebook: Machine Learning for Indoor Localization and Navigation; Saideep Tiku,Sudeep Pasricha Book 2023 The Editor(s) (if applicable) and The Auth

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Overview of Approaches for Device Heterogeneity Management During Indoor Localizationd positioning technology, has attracted extensive attention. In the process of localization, the difference in RSS caused by heterogeneity between different devices cannot be ignored. It leads to the degradation of positioning accuracy. A comprehensive overview of device heterogeneity management met

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Deep Learning for Resilience to Device Heterogeneity in Cellular-Based Localizationre suitable for providing such ubiquitous services due to their widespread availability. One of the main barriers to accuracy is a large number of models of cell phones, which have variations of the measured received signal strength (RSSI), even at the same location and time. This chapter discusses

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Smartphone Invariant Indoor Localization Using Multi-head Attention Neural Network However, a few critical challenges have prevented the widespread proliferation of this technology in the public domain. One such critical challenge is device heterogeneity, i.e., the variation in the RSSI signal characteristics captured across different smartphone devices. In the real world, the sm

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Heterogeneous Device Resilient Indoor Localization Using Vision Transformer Neural Networksgs to localize users with smartphones. Unfortunately, it has been demonstrated that the heterogeneity of wireless transceivers among various cellphones used by consumers reduces the accuracy and dependability of localization algorithms. In this chapter, we propose a novel framework based on vision t

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Heterogeneous Device Resilient Indoor Localization Using Vision Transformer Neural Networks smartphone heterogeneity while improving localization accuracy from 41% to 68% over the best-known prior works. We also demonstrate the generalizability of our approach and propose a data augmentation technique that can be integrated into most deep learning-based localization frameworks to improve accuracy.

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