# Joint Activity Recognition and Indoor Localization with WiFi Fingerprints

arXiv: https://arxiv.org/abs/1904.04964 · HTML: https://mlsanity.com/paper/1904.04964/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Apr 2019.

## Built on by (most cited first, 19 of 19)

- [WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing](https://mlsanity.com/paper/2402.09430/) (2024)
- [WiOpen: A Robust Wi-Fi-based Open-set Gesture Recognition Framework](https://mlsanity.com/paper/2402.00822/) (2024)
- [XRF V2: A Dataset for Action Summarization with Wi-Fi Signals, and IMUs in Phones, Watches, Earbuds, and Glasses](https://mlsanity.com/paper/2501.19034/) (2025)
- [A Survey on Wi-Fi Sensing Generalizability: Taxonomy, Techniques, Datasets, and Future Research Prospects](https://mlsanity.com/paper/2503.08008/) (2025)
- [CSI-Bench: A Large-Scale In-the-Wild Dataset for Multi-task WiFi Sensing](https://mlsanity.com/paper/2505.21866/) (2025)
- [AutoQML: Automated Quantum Machine Learning for Wi-Fi Integrated Sensing and Communications](https://mlsanity.com/paper/2205.09115/) (2022)
- [Quantum Transfer Learning for Wi-Fi Sensing](https://mlsanity.com/paper/2205.08590/) (2022)
- [Gesture Recognition with mmWave Wi-Fi Access Points: Lessons Learned](https://mlsanity.com/paper/2306.17062/) (2023)
- [MaskFi: Unsupervised Learning of WiFi and Vision Representations for Multimodal Human Activity Recognition](https://mlsanity.com/paper/2402.19258/) (2024)
- [Multi-Band Wi-Fi Sensing with Matched Feature Granularity](https://mlsanity.com/paper/2112.14006/) (2021)
- [Deakin RF-Sensing: Experiments on Correlated Knowledge Distillation for Monitoring Human Postures with Radios](https://mlsanity.com/paper/2305.14829/) (2023)
- [CSI-Based Efficient Self-Quarantine Monitoring System Using Branchy Convolution Neural Network](https://mlsanity.com/paper/2306.01756/) (2023)
- [Static vs. Dynamic Databases for Indoor Localization based on Wi-Fi Fingerprinting: A Discussion from a Data Perspective](https://mlsanity.com/paper/2402.12756/) (2024)
- [CSI4Free: GAN-Augmented mmWave CSI for Improved Pose Classification](https://mlsanity.com/paper/2406.18684/) (2024)
- [Beyond Physical Labels: Redefining Domains for Robust WiFi-based Gesture Recognition](https://mlsanity.com/paper/2601.03825/) (2026)
- [WiFi-based Multi-task Sensing](https://mlsanity.com/paper/2111.14619/) (2021)
- [Beyond Sub-6 GHz: Leveraging mmWave Wi-Fi for Gait-Based Person Identification](https://mlsanity.com/paper/2510.08160/) (2025)
- [Purify-then-Align: Towards Robust Human Sensing under Modality Missing with Knowledge Distillation from Noisy Multimodal Teacher](https://mlsanity.com/paper/2604.05584/) (2026)
- [ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization](https://mlsanity.com/paper/2605.01866/) (2026)

## Abstract (arXiv)

Recent years have witnessed the rapid development in the research topic of WiFi sensing that automatically senses human with commercial WiFi devices. This work falls into two major categories, i.e., the activity recognition and the indoor localization. The former work utilizes WiFi devices to recognize human daily activities such as smoking, walking, and dancing. The latter one, indoor localization, can be used for indoor navigation, location-based services, and through-wall surveillance. The key rationale behind this type of work is that people behaviors can influence the WiFi signal propagation and introduce specific patterns into WiFi signals, called WiFi fingerprints, which can be further explored to identify human activities and locations. In this paper, we propose a novel deep learning framework for joint activity recognition and indoor localization task using WiFi Channel State Information~(CSI) fingerprints. More precisely, we develop a system running standard IEEE 802.11n WiFi protocol, and collect more than 1400 CSI fingerprints on 6 activities at 16 indoor locations. Then we propose a dual-task convolutional neural network with 1-dimensional convolutional layers for the joint task of activity recognition and indoor localization. Experimental results and ablation study show that our approach achieves good performances in this joint WiFi sensing task. Data and code have been made publicly available at https://github.com/geekfeiw/apl.