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21 pages, 5173 KiB

Open AccessArticle

A Long-Range Signal-Based Target Localization Algorithm

by Jinfa Ge, Dongsheng Zhu, Lijuan Sun, Chong Han and Jian Guo

Electronics 2024, 13(6), 1069; https://doi.org/10.3390/electronics13061069 - 14 Mar 2024

Viewed by 484

Indoor target localization is pivotal across various applications, encompassing security monitoring, behavioral analysis, and elderly care. This work proposes an advanced target localization algorithm that harnesses antennas endowed with sensing capabilities to capture the phase change in the signal ratio, derived from the [...] Read more.

Indoor target localization is pivotal across various applications, encompassing security monitoring, behavioral analysis, and elderly care. This work proposes an advanced target localization algorithm that harnesses antennas endowed with sensing capabilities to capture the phase change in the signal ratio, derived from the signal amplitude. This phase change, indicative of the target’s movement direction, is analyzed alongside the front and rear arrival angle information and signal amplitude characteristics obtained from LoRa signals. The algorithm, through a comprehensive examination of the phase change patterns, amalgamated with arrival angle data and signal amplitude characteristics, effectively estimates the precise location of the target. Experimental validations underscore the algorithm’s efficacy in determining the target’s location during continuous walking activity. Conducted within a 6 m × 12 m open platform, the algorithm achieves an average localization error of 48.5 cm, underscoring its superior performance compared to existing methodologies. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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16 pages, 3094 KiB

Open AccessArticle

A Novel Adaptive Indoor Positioning Using Mobile Devices with Wireless Local Area Networks

by Yung-Fa Huang, Yi-Hsiang Hsu, Jen-Yung Lin and Ching-Mu Chen

Electronics 2024, 13(5), 895; https://doi.org/10.3390/electronics13050895 - 26 Feb 2024

Viewed by 524

Abstract

In this paper, mobile devices were used to estimate the received signal strength indicator (RSSI) of wireless channels with three wireless access points (APs). Using the RSSI, the path loss exponent (PLE) was adapted to calculate the estimated distance among the test points [...] Read more.

In this paper, mobile devices were used to estimate the received signal strength indicator (RSSI) of wireless channels with three wireless access points (APs). Using the RSSI, the path loss exponent (PLE) was adapted to calculate the estimated distance among the test points (TPs) and the APs, through the root mean square error (RMSE). Moreover, in this paper, the proposed adaptive PLE (APLE) of the TPs was obtained by minimizing the positioning errors of the PLEs. The training samples of RSSI were measured by TPs for 6 days, and different surge processing methods were used to obtain APLE and to improve the positioning accuracy. The surge signals of RSSI were reduced by the cumulated distribution function (CDF), hybrid Kalman filter (KF), and threshold filtering methods, integrating training samples and APLE. The experimental results show that with the proposed APLE, the position accuracy can be improved by 50% compared to the free space model for six TPs. Finally, dynamic real-time indoor positioning was performed and measured for the performance evaluation of the proposed APLE models. The experimental results show that, the minimum dynamic real-time positioning error can be improved to 0.88 m in a straight-line case with the hybrid method. Moreover, the average positioning error of dynamic real-time indoor positioning can be reduced to 1.15 m using the four methods with the proposed APLE. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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21 pages, 2538 KiB

Open AccessArticle

Performance of Differential Evolution Algorithms for Indoor Area Positioning in Wireless Sensor Networks

by Shu-Hung Lee, Chia-Hsin Cheng, Kuan-Hsien Lu, Yeong-Long Shiue and Yung-Fa Huang

Electronics 2024, 13(4), 705; https://doi.org/10.3390/electronics13040705 - 9 Feb 2024

Viewed by 568

Abstract

In positioning systems in wireless sensor networks, the accuracy of localization is often affected by signal distortion or attenuation caused by environmental factors, especially in indoor environments. Although using a combination of K-Nearest Neighbor (KNN) algorithm and fingerprinting matching can reduce positioning errors [...] Read more.

In positioning systems in wireless sensor networks, the accuracy of localization is often affected by signal distortion or attenuation caused by environmental factors, especially in indoor environments. Although using a combination of K-Nearest Neighbor (KNN) algorithm and fingerprinting matching can reduce positioning errors due to poor signal quality, the improvement in accuracy by increasing the number of reference points and K values is not significant. This paper proposes a Differential Evolution-based KNN (DE-KNN) method to overcome the performance limitations of the KNN algorithm and enhance indoor area positioning accuracy in WSNs. The DE-KNN method aims to improve the accuracy and stability of indoor positioning in wireless sensor networks. According to the simulation results, in a simple indoor environment with four reference points, when the sensors are deployed in both fixed and random arrangements, the positioning accuracy was improved by 29.09% and 30.20%, respectively, compared to using the KNN algorithm alone. In a complex indoor environment with four reference points, the positioning accuracy was increased by 32.24% and 33.72%, respectively. When the number of reference points increased to five, in a simple environment, the accuracy improvement for both fixed and random deployment was 20.70% and 26.01%, respectively. In a complex environment, the accuracy improvement was 23.88% and 27.99% for fixed and random deployment, respectively. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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24 pages, 1252 KiB

Open AccessArticle

An Unsupervised Method to Recognise Human Activity at Home Using Non-Intrusive Sensors

by Raúl Gómez-Ramos, Jaime Duque-Domingo, Eduardo Zalama and Jaime Gómez-García-Bermejo

Electronics 2023, 12(23), 4772; https://doi.org/10.3390/electronics12234772 - 24 Nov 2023

Cited by 1 | Viewed by 875

Abstract

As people get older, living at home can expose them to potentially dangerous situations when performing everyday actions or simple tasks due to physical, sensory or cognitive limitations. This could compromise the residents’ health, a risk that in many cases could be reduced [...] Read more.

As people get older, living at home can expose them to potentially dangerous situations when performing everyday actions or simple tasks due to physical, sensory or cognitive limitations. This could compromise the residents’ health, a risk that in many cases could be reduced by early detection of the incidents. The present work focuses on the development of a system capable of detecting in real time the main activities of daily life that one or several people can perform at the same time inside their home. The proposed approach corresponds to an unsupervised learning method, which has a number of advantages, such as facilitating future replication or improving control and knowledge of the internal workings of the system. The final objective of this system is to facilitate the implementation of this method in a larger number of homes. The system is able to analyse the events provided by a network of non-intrusive sensors and the locations of the residents inside the home through a Bluetooth beacon network. The method is built upon an accurate combination of two hidden Markov models: one providing the rooms in which the residents are located and the other providing the activity the residents are carrying out. The method has been tested with the data provided by the public database SDHAR-HOME, providing accuracy results ranging from 86.78% to 91.68%. The approach presents an improvement over existing unsupervised learning methods as it is replicable for multiple users at the same time. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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27 pages, 8504 KiB

Open AccessArticle

Resilient Localization and Coverage in the Internet of Things

by Yaser Al Mtawa, Hossam S. Hassanein and Nidal Nasser

Electronics 2023, 12(14), 3172; https://doi.org/10.3390/electronics12143172 - 21 Jul 2023

Cited by 2 | Viewed by 1341

Abstract

The proliferation of the Internet of Things (IoT) has revolutionized traditional services, giving rise to emerging smart infrastructures by connecting the physical and digital worlds. Sensory data is essential in IoT-based systems for providing context-aware and location-based services. Hence, the accurate localization of [...] Read more.

The proliferation of the Internet of Things (IoT) has revolutionized traditional services, giving rise to emerging smart infrastructures by connecting the physical and digital worlds. Sensory data is essential in IoT-based systems for providing context-aware and location-based services. Hence, the accurate localization of IoT devices is paramount. Anchor misplacement can significantly affect location information and coverage services in IoT. We study the effect of anchor misplacement in typical IoT settings where sensors are randomly deployed, can be mobile, and may belong to multiple providers. We identify sensing coverage holes formed by anchor misplacement and analyze their presence and impact. To mitigate the impact of anchor misplacement on network reliability, we propose a framework to identify the affected sensor nodes and then identify and remove misplaced anchor nodes. The validity of our approach is verified, and its effectiveness is demonstrated by several experiments with different network topologies and parameters. Our results are promising and can be utilized in multiple coverage applications, such as smart agriculture systems and habitat monitoring, regardless of the sensors or deployment types. It also sheds light on best practices and methods for a reliable design of IoT-based systems. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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16 pages, 4475 KiB

Open AccessArticle

Advanced Thermal Control Using Chip Cooling Laminate Chip (CCLC) with Finite Element Method for System-in-Package (SiP) Technology

by Aziz Oukaira, Dhaou Said, Jamal Zbitou and Ahmed Lakhssassi

Electronics 2023, 12(14), 3154; https://doi.org/10.3390/electronics12143154 - 20 Jul 2023

Cited by 5 | Viewed by 1428

Abstract

This paper introduces a novel approach to address thermal management challenges in system-in-package (SiP) technology, which is a significant concern in various advanced technologies. The main objective is to assess the electrical and thermal performance of the SiP model by utilizing Chip Cooling [...] Read more.

This paper introduces a novel approach to address thermal management challenges in system-in-package (SiP) technology, which is a significant concern in various advanced technologies. The main objective is to assess the electrical and thermal performance of the SiP model by utilizing Chip Cooling Laminate Chip (CCLC) technology. To achieve this, we employed finite element method (FEM) analysis using COMSOL Multiphysics^® and MATLAB^® to compare the results of electrical and thermal SiP models with and without CCLC technology. The numerical simulations revealed that, as opposed to the traditional model, the temperature variation decreased significantly with a uniform temperature distribution when employing the CCLC technology. Additionally, the thermal conduction performance of the packaging system using CCLC demonstrated remarkable reliability and resolution with cost-effective micro-devices, particularly in micro-medicine applications. The analysis of the electrical and thermal models reported a maximum error between them of 1.15

^{\circ}

C. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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17 pages, 2196 KiB

Open AccessArticle

MUS3E: A Mobility Ubiquitous Sensor Edge Environment for the Elderly

by Tomihiro Utsumi, Masatoshi Arikawa and Masashi Hashimoto

Electronics 2023, 12(14), 3003; https://doi.org/10.3390/electronics12143003 - 8 Jul 2023

Viewed by 971

Abstract

With the ageing of society, the number of households with older individuals or couples living alone is increasing. An “ageing-in-place” approach allows older adults to continue to live at home and receive help only when needed. However, this approach is insufficient for emergencies, [...] Read more.

With the ageing of society, the number of households with older individuals or couples living alone is increasing. An “ageing-in-place” approach allows older adults to continue to live at home and receive help only when needed. However, this approach is insufficient for emergencies, such as falls, as well as for individuals with gradually deteriorating health conditions, such as frailty. Unexpected accidents significantly reduce the quality of life (QoL) of older adults. This paper proposes a new framework, the mobility ubiquitous sensor edge environment (MUS3E), to digitally transform ordinary houses to detect the movement of older individuals throughout their home environment and to notify family members and care providers of residents’ health status and safety information. The framework can be easily and inexpensively installed in any home, transforming an ordinary house into a smart home with an automated function for monitoring older residents. It uses ambient sensors such as passive infrared ray sensors to automatically measure health conditions by measuring factors such as walking speed. Residents need not interact with or control the system and can go about their daily lives. Since the sensors used in this system are mass-produced consumer products, they are inexpensive and easily replaceable, as there are many alternatives. In this study, we were able to demonstrate the practically and feasibility of this framework using a prototype that uses open architecture Internet of Things (IoT) software (Debian GNU/Linux 11, Arduino 1.8.19, ESP8266 2.7.4, ESP32 1.0.6, PubSubClient 2.8.0, ESPPerfectTime 0.3.0, mosquitto 2.0.11) components to digitally transform the living environment of older individuals. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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17 pages, 3354 KiB

Open AccessArticle

Performance Enhancement of CAN/Ethernet Automotive Gateway with a CAN Data Reduction Algorithm

by Sung Bhin Oh, Young Soo Do, Min Jeong Lee, Jin Ho Kim and Jae Wook Jeon

Electronics 2023, 12(13), 2777; https://doi.org/10.3390/electronics12132777 - 22 Jun 2023

Cited by 2 | Viewed by 1494

Abstract

Data reduction (DR) techniques for the controller area network (CAN) are being developed to reduce the increased bus load caused by the growing number of electronic control units (ECUs) and automotive software complexity in modern automobiles. DR techniques enable the transmission of the [...] Read more.

Data reduction (DR) techniques for the controller area network (CAN) are being developed to reduce the increased bus load caused by the growing number of electronic control units (ECUs) and automotive software complexity in modern automobiles. DR techniques enable the transmission of the same information with less bandwidth, effectively reducing the busload in CAN-based networks. Modern vehicles are composed of various in-vehicle network (IVN) protocols, such as CAN, local interconnect network (LIN), and Ethernet. However, existing DR techniques only consider the communication between CAN nodes. The application of DR techniques to a CAN bus may lead to compatibility issues when communicating with heterogeneous IVN protocols. This paper proposed a CAN/Ethernet gateway system for seamless communication with CAN DR. The proposed gateway system was implemented on a TC275-based embedded system, and its performance was evaluated and analyzed. The experimental results revealed that CAN DR compression effectively improves both the CAN bus load and end-to-end processing time of the gateway system. The CAN bus load was reduced by up to 33.68%, and the average end-to-end processing time was reduced to 336 μs. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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16 pages, 3106 KiB

Open AccessArticle

A Network Scheduling Method Based on Segmented Constraints for Convergence of Time-Sensitive Networking and Industrial Wireless Networks

by Min Wei, Chang Liu, Jin Wang and Shujie Yang

Electronics 2023, 12(11), 2418; https://doi.org/10.3390/electronics12112418 - 26 May 2023

Viewed by 982

Abstract

In industrial applications, it is necessary to select different types of networks according to different communication requirements. To meet this requirement, a converged network of wired and wireless networks is frequently employed. Notably, fulfilling the end-to-end transmission requirements of converged networks is challenging. [...] Read more.

In industrial applications, it is necessary to select different types of networks according to different communication requirements. To meet this requirement, a converged network of wired and wireless networks is frequently employed. Notably, fulfilling the end-to-end transmission requirements of converged networks is challenging. As a solution, converged-network scheduling methods have proved valuable. In this paper, a network scheduling method for the convergence of industrial wireless networks and time-sensitive networks is proposed. Additionally, the proposed method is tested and verified. The results show that the end-to-end average transmission delay is reduced and the jitter is acceptable. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks II)

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