FedHIL: Heterogeneity resilient federated learning for robust indoor localization with mobile devices

D Gufran, S Pasricha - ACM Transactions on Embedded Computing …, 2023 - dl.acm.org
Indoor localization plays a vital role in applications such as emergency response,
warehouse management, and augmented reality experiences. By deploying machine …

SENTINEL: Securing Indoor Localization against Adversarial Attacks with Capsule Neural Networks

D Gufran, P Anandathirtha… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the increasing demand for edge device-powered location-based services in indoor
environments, Wi-Fi received signal strength (RSS) fingerprinting has become popular …

Indoor localization by projecting magnetic field signals onto images with vision transformer

H Rafique, D Patti, M Palesi, GC La Delfa - Computers and Electrical …, 2025 - Elsevier
Indoor localization, powered by the Internet of Things (IoT)-based sensor fusion, represents
an evolving application that uses mobile sensors and embedded hardware within buildings …

CALLOC: Curriculum adversarial learning for secure and robust indoor localization

D Gufran, S Pasricha - 2024 Design, Automation & Test in …, 2024 - ieeexplore.ieee.org
Indoor localization has become increasingly vital for many applications from tracking assets
to delivering personalized services. Yet, achieving pinpoint accuracy remains a challenge …

SAFELOC: Overcoming Data Poisoning Attacks in Heterogeneous Federated Machine Learning for Indoor Localization

A Singampalli, D Gufran, S Pasricha - arXiv preprint arXiv:2411.09055, 2024 - arxiv.org
Machine learning (ML) based indoor localization solutions are critical for many emerging
applications, yet their efficacy is often compromised by hardware/software variations across …