scholarly journals A Lightweight Passive Human Tracking Method Using Wi-Fi

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 541
Author(s):  
Jian Fang ◽  
Lei Wang ◽  
Zhenquan Qin ◽  
Bingxian Lu ◽  
Wenbo Zhao ◽  
...  
Keyword(s):  
Target Tracking ◽  
Human Motion ◽  
Wireless Devices ◽  
Target Movement ◽  
Channel State ◽  
Time Model ◽  
Tracking Method ◽  
Extensive Evaluation ◽  
Device Free ◽  
The Impact

Target tracking is a critical technique for localization in an indoor environment. Current target-tracking methods suffer from high overhead, high latency, and blind spots issues due to a large amount of data needing to be collected or trained. On the other hand, a lightweight tracking method is preferred in many cases instead of just pursuing accuracy. For this reason, in this paper, we propose a Wi-Fi-enabled Infrared-like Device-free (WIDE) method for target tracking to realize a lightweight target-tracking method. We first analyze the impact of target movement on the physical layer of the wireless link and establish a near real-time model between the Channel State Information (CSI) and human motion. Secondly, we make full use of the network structure formed by a large number of wireless devices already deployed in reality to achieve the goal. We validate the WIDE method in different environments. Extensive evaluation results show that the WIDE method is lightweight and can track targets rapidly as well as achieve satisfactory tracking results.

scholarly journals Channel State Information from Pure Communication to Sense and Track Human Motion: A Survey

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3329 ◽  
Author(s):  
Mohammed A. A. Al-qaness ◽  
Mohamed Abd Elaziz ◽  
Sunghwan Kim ◽  
Ahmed A. Ewees ◽  
Aaqif Afzaal Abbasi ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Channel State Information ◽  
Software Radio ◽  
Human Motion ◽  
Indoor Environments ◽  
Channel State ◽  
State Information ◽  
Human Motion Detection ◽  
The Future ◽  
Device Free

Human motion detection and activity recognition are becoming vital for the applications in smart homes. Traditional Human Activity Recognition (HAR) mechanisms use special devices to track human motions, such as cameras (vision-based) and various types of sensors (sensor-based). These mechanisms are applied in different applications, such as home security, Human–Computer Interaction (HCI), gaming, and healthcare. However, traditional HAR methods require heavy installation, and can only work under strict conditions. Recently, wireless signals have been utilized to track human motion and HAR in indoor environments. The motion of an object in the test environment causes fluctuations and changes in the Wi-Fi signal reflections at the receiver, which result in variations in received signals. These fluctuations can be used to track object (i.e., a human) motion in indoor environments. This phenomenon can be improved and leveraged in the future to improve the internet of things (IoT) and smart home devices. The main Wi-Fi sensing methods can be broadly categorized as Received Signal Strength Indicator (RSSI), Wi-Fi radar (by using Software Defined Radio (SDR)) and Channel State Information (CSI). CSI and RSSI can be considered as device-free mechanisms because they do not require cumbersome installation, whereas the Wi-Fi radar mechanism requires special devices (i.e., Universal Software Radio Peripheral (USRP)). Recent studies demonstrate that CSI outperforms RSSI in sensing accuracy due to its stability and rich information. This paper presents a comprehensive survey of recent advances in the CSI-based sensing mechanism and illustrates the drawbacks, discusses challenges, and presents some suggestions for the future of device-free sensing technology.

Review on Target Tracking Method in Multimedia Wireless Sensor Networks

2021 ◽  
Author(s):  
Afritha Amelia ◽  
Muhammad Zarlis ◽  
Suherman Suherman ◽  
Syahril Efendi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Wireless Sensor ◽  
Tracking Method

scholarly journals Multi-Target Intense Human Motion Analysis and Detection Using Channel State Information

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3379 ◽  
Author(s):  
Jialin Liu ◽  
Lei Wang ◽  
Jian Fang ◽  
Linlin Guo ◽  
Bingxian Lu ◽  
...  
Keyword(s):  
Channel State Information ◽  
Motion Detection ◽  
School Bullying ◽  
Human Motion ◽  
Line Of Sight ◽  
Human Motion Analysis ◽  
Channel State ◽  
Detection Scheme ◽  
State Information ◽  
Human Motion Detection

Intense human motion, such as hitting, kicking, and falling, in some particular scenes indicates the occurrence of abnormal events like violence and school bullying. Camera-based human motion detection is an effective way to analyze human behavior and detect intense human motion. However, even if the camera is properly deployed, it will still generate blind spots. Moreover, camera-based methods cannot be used in places such as restrooms and dressing rooms due to privacy issues. In this paper, we propose a multi-target intense human motion detection scheme using commercial Wi-Fi infrastructures. Compared with human daily activities, intense human motion usually has the characteristics of intensity, rapid change, irregularity, large amplitude, and continuity. We studied the changing pattern of Channel State Information (CSI) influenced by intense human motion, and extracted features in the pattern by conducting a large number of experiments. Considering occlusion exists in some complex scenarios, we distinguished the Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions in the case of obstacles appearing between the transmitter and the receiver, which further improves the overall performance. We implemented the intense human motion detection system using single commercial Wi-Fi devices, and evaluated it in real indoor environments. The experimental results show that our system can achieve intense human motion detection rate of 90%.

Proportional Navigation (PN) Based Tracking of Ground Targets by Quadrotor UAVs

2013 ◽  
Author(s):  
Ruoyu Tan ◽  
Manish Kumar
Keyword(s):  
Target Tracking ◽  
Proportional Navigation ◽  
Tracking Method ◽  
Maneuvering Targets ◽  
Time Optimal ◽  
Aerial Vehicle ◽  
Quadrotor Uavs ◽  
The One ◽  
Rotary Wing ◽  
Guidance Laws

This paper addresses the problem of controlling a rotary wing Unmanned Aerial Vehicle (UAV) tracking a target moving on ground. The target tracking problem by UAVs has received much attention recently and several techniques have been developed in literature most of which have been applied to fixed wing aircrafts. The use of quadrotor UAVs, the subject of this paper, for target tracking presents several challenges especially for highly maneuvering targets since the development of time-optimal controller (required if target is maneuvering fast) for quadrotor UAVs is extremely difficult due to highly non-linear dynamics. The primary contribution of this paper is the development of a proportional navigation (PN) based method and its implementation on quad-rotor UAVs to track moving ground target. The PN techniques are known to be time-optimal in nature and have been used in literature for developing guidance systems for missiles. There are several types of guidance laws that come within the broad umbrella of the PN method. The paper compares the performance of these guidance laws for their application on quadrotors and chooses the one that performs the best. Furthermore, to apply this method for target tracking instead of the traditional objective of target interception, a switching strategy has also been designed. The method has been compared with respect to the commonly used Proportional Derivative (PD) method for target tracking. The experiments and numerical simulations performed using maneuvering targets show that the proposed tracking method not only carries out effective tracking but also results into smaller oscillations and errors when compared to the widely used PD tracking method.

An Improved Trace Method for Moving Target under Occlusion

2014 ◽  
Vol 672-674 ◽  
pp. 1931-1934
Author(s):  
Yu Bing Dong ◽  
Guang Liang Cheng ◽  
Ming Jing Li
Keyword(s):  
Mathematical Model ◽  
Target Tracking ◽  
Difficult Problem ◽  
Block Matching ◽  
Experimental Results ◽  
Polar Coordinates ◽  
Moving Target ◽  
Trajectory Prediction ◽  
Tracking Method

Occlusion is a difficult problem to be solved in the process of target tracking. In order to solve the problem of occlusion, a new tracking method combined with trajectory prediction and multi-block matching is presented and studied,and a mathematical model of trajectory prediction of moving target is established in polar coordinates and verified through some experiments. The experimental results show that the new tracking method can be better to trace and forecast the moving target under occlusion.

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