Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) several limiting problems, such as variation signals drift PDR. An auxiliary tool for landmarks, which easily identified specific sensor patterns environment, this will exploited...

Intelligent occupancy sensing is becoming a vital underpinning for various emerging applications in smart homes, such as security surveillance and human behavior analysis. However, prevailing approaches mainly rely on video camera, ambient sensors, or wearable devices, which either requires arduous deployment arouses privacy concerns. In this paper, we present novel real-time, device-free, privacy-preserving WiFi-enabled Internet of Things platform sensing, can promote myriad applications....

WiFi fingerprinting-based indoor positioning system (IPS) has become the most promising solution for localization. However, there are two major drawbacks that hamper its large-scale implementation. First, an offline site survey process is required which extremely time-consuming and labor-intensive. Second, RSS fingerprint database built vulnerable to environmental dynamics. To address these issues comprehensively, in this paper, we propose WinIPS, a WiFi-based non-intrusive IPS enables...

Indoor localization has attracted more and attention because of its importance in many applications. One the most popular techniques for indoor is received signal strength indicator (RSSI) based fingerprinting approach. Since RSSI values are very complicated noisy, conventional machine learning algorithms often suffer from limited performance. Recently developed deep have been shown to be powerful analysis complex data. In this paper, we propose a local feature-based long short-term memory...

Over the recent years, WiFi sensing has been rapidly developed for privacy-preserving, ubiquitous human-sensing applications, enabled by signal processing and deep-learning methods. However, a comprehensive public benchmark deep learning in sensing, similar to that available visual recognition, does not yet exist. In this article, we review progress topics ranging from hardware platforms algorithms propose new library with benchmark, SenseFi. On basis, evaluate various models terms of...

In the metaverse, digital avatar plays an important role in representing human beings for various interaction with virtual objects and environments, which puts a high demand on effective pose estimation. Though camera-based solutions yield remarkable performance, they encounter privacy issues degraded performance caused by varying illumination, especially smart home. this article, we propose WiFi-based Internet of Things-enabled estimation scheme metaverse simulation, namely, MetaFi++....

Indoor positioning system (IPS) has become one of the most attractive research fields due to increasing demands on location-based services (LBSs) in indoor environments. Various IPSs have been developed under different circumstances, and them adopt fingerprinting technique mitigate pervasive multipath effects. However, performance severely suffers from device heterogeneity existing across commercial off-the-shelf mobile devices (e.g., smart phones, tablet computers, etc.) environmental...

In this paper, we propose a robust and accurate indoor localization tracking system using smartphone built-in inertial measurement unit (IMU) sensors, WiFi received signal strength measurements opportunistic iBeacon corrections based on particle filter. We utilize Pedestrian Dead Reckoning (PDR) approach which leverages equipped accelerometers, gyroscope magnetometer to estimate the walking distance direction of user. The position estimated by fingerprinting is fused with PDR reduce its...

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in environments. WiFi technology been studied and explored provide for years view of wide deployment availability existing infrastructures A large body WiFi-based IPSs adopt fingerprinting approaches localization. However, these suffer from two major problems: intensive costs manpower time offline site survey inflexibility environmental...

The location and contextual status (indoor or outdoor) is fundamental critical information for upper-layer applications, such as activity recognition location-based services (LBS) individuals. In addition, optimizations of building management systems (BMS), the pre-cooling heating process air-conditioning system according to human traffic entering exiting a building, can utilize information, well. emerging mobile devices, which are equipped with various sensors, become feasible flexible...

The increasing demands of location-based services have spurred the rapid development indoor positioning system and localization interchangeably (IPSs). However, performance IPSs suffers from noisy measurements. In this paper, two kinds robust extreme learning machines (RELMs), corresponding to close-to-mean constraint, small-residual been proposed address issue measurements in IPSs. Based on whether feature mapping machine is explicit, we respectively provide random-hidden-nodes kernelized...

We propose a gesture recognition system that leverages existing WiFi infrastructures and learns gestures from channel state information (CSI) measurements. Having developed an innovative OpenWrt-based platform for commercial devices to extract CSI data, we novel deep Siamese representation learning architecture one-shot recognition. Technically, our model extends the capacity of spatio-temporal patterns standard structure by incorporating convolutional bidirectional recurrent neural...

In the era of Internet Things (IoT), human activity recognition is becoming vital underpinning for a myriad emerging applications in smart home and buildings. Existing approaches require either deployment extra infrastructure or cooperation occupants to carry dedicated devices, which are expensive, intrusive inconvenient pervasive implementation. this paper, we propose DeepSense, device-free scheme that can automatically identify common activities via deep learning using only commodity...

Location-based service (LBS) has become an indispensable part of our daily lives. Realizing accurate LBS in indoor environments is still a challenging task. WiFi fingerprinting-based positioning system (IPS) achieved encouraging results recently, but the time and labor overhead constructing dense radio map remains key bottleneck that hinders it for real-world large-scale implementation. In this article, we propose WiGAN automatic fine-grained ratio construction adaptation scheme empowered by...

We propose a novel domain adaptation framework, namely Consensus Adversarial Domain Adaptation (CADA), that gives freedom to both target encoder and source embed data from domains into common domaininvariant feature space until they achieve consensus during adversarial learning. In this manner, the discrepancy can be further minimized in embedded space, yielding more generalizable representations. The framework is also extended establish new few-shot scheme (F-CADA), remarkably enhances ADA...

WiFi technology has been applied to various places due the increasing requirement of high-speed Internet access. Recently, besides network services, sensing is appealing in smart homes since it device-free, cost-effective and privacy-preserving. Though numerous methods have developed, most them only consider single home scenario. Without connection powerful cloud server massive users, large-scale still difficult. In this paper, we firstly analyze summarize these obstacles, propose an...

In the era of Internet Things, crowd counting, which estimates number people within a region, becomes underpinning for many emerging applications, such as occupancy estimation in smart building and queuing management product placement shopping center. Existing vision based counting schemes require favorable lighting conditions also raise privacy concerns. RF approaches rely on specialized sensors users to carry devices. Thus, an accurate, reliable non-intrusive scheme is still desired. this...

Smart buildings today are aimed at providing safe, healthy, comfortable, affordable, and beautiful spaces in a carbon energy-efficient way. They emerging as complex cyber-physical systems with humans the loop. Cost, need to cope increasing functional complexity, flexibility, fragmentation of supply chain, time-to-market pressure rendering traditional heuristic ad hoc design paradigms inefficient insufficient for future. In this paper, we present platform-based methodology smart building...

We propose AutoID, a human identification system that leverages the measurements from existing WiFi-enabled Internet of Things (IoT) devices and produces identity estimation via novel sparse representation learning technique. The key idea is to use unique fine-grained gait patterns each person revealed WiFi Channel State Information (CSI) measurements, technically referred as shapelet signatures, "fingerprint" for identification. For this purpose, OpenWrt-based IoT platform designed collect...

Accurate Location Based Service (LBS) is one of the fundamental but crucial services in era Internet Things (IoT). WiFi fingerprinting-based Indoor Positioning System (IPS) has become most promising solution for indoor LBS. However, offline calibrated received signal strength (RSS) radio map unable to provide consistent LBS with high localization accuracy under various environmental dynamics. To address this issue, we propose TKL-WinSMS as a systematic strategy, which able realize robust and...

Pedestrian dead reckoning (PDR) is a promising complementary technique to balance the requirements on both accuracy and costs in outdoor indoor positioning systems. In this paper, we propose unified framework comprehensively tackle three sub problems involved PDR, including step detection counting, heading estimation length estimation, based sequentially rotating device (reference) frame Earth through sensor fusion. To be specific, robust counting algorithm devised according vertical angular...