Sensors, Vol. 24, Pages 2659: Reengineering Indoor Air Quality Monitoring Systems to Improve End-User Experience
dochiei
This paper presents an indoor air quality (IAQ) monitoring system designed for a better end-user experience. The monitoring system consists of elements, from the monitoring sensor to the monitoring interface, designed and implemented by the research team, especially for the proposed monitoring system. The monitoring solution is intended for users who live in houses without automatic ventilation systems. The air quality sensor is designed at a minimum cost and complexity to allow multi-zone implementation without significant effort. The user interface uses a spatial graphic representation that facilitates unders...
Source: Sensors - April 22, 2024 Category: Biotechnology Authors: Radu Nicolae Pietraru Adriana Olteanu Ioana-Raluca Adochiei Felix-Constantin Adochiei Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2653: FPGA-Microprocessor Based Sensor for Faults Detection in Induction Motors Using Time-Frequency and Machine Learning Methods
onino-Daviu
Induction motors (IM) play a fundamental role in the industrial sector because they are robust, efficient, and low-cost machines. Changes in the environment, installation errors, or modifications to working conditions can generate faults in induction motors. The trend on IM fault detection is focused on the design techniques and sensors capable of evaluating multiple faults with various signals using non-invasive analysis. The methodology is based on processing electric current signals by applying the short-time Fourier transform (STFT). Additionally, the computation of the mean and standard deviation of in...
Source: Sensors - April 22, 2024 Category: Biotechnology Authors: Roque Alfredo Osornio-Rios Isaias Cueva-Perez Alvaro Ivan Alvarado-Hernandez Larisa Dunai Israel Zamudio-Ramirez Jose Alfonso Antonino-Daviu Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2654: Gain and Bandwidth Enhancement of 3D-Printed Short Backfire Antennas Using Rim Flaring and Iris Matching
son
In this article, we present new design techniques to improve the gain and impedance bandwidth of short backfire antennas. For the gain enhancement procedure, our approach was to flare the rim of the antenna, which simultaneously led to an increase in the impedance bandwidth of the antenna. Parametric studies were carried out to obtain the optimal flaring angle. The peak realized gain was obtained as 17.2 dBi with an impedance bandwidth of 55% (2.4 dB and 28.6% increase in gain and bandwidth, respectively, compared to the unflared antenna). To further enhance the impedance bandwidth, an inductive iris was added to i...
Source: Sensors - April 22, 2024 Category: Biotechnology Authors: Yewande Mariam Aragbaiye Dustin Isleifson Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2656: Recent Advances in Intelligent Algorithms for Fault Detection and Diagnosis
i
Fault-finding diagnostics is a model-driven approach that identifies a system’s malfunctioning portion. It uses residual generators to identify faults, and various methods like isolation techniques and structural analysis are used. However, diagnostic equipment doesn’t measure the remaining signal-to-noise ratio. Residual selection identifies fault-detecting generators. Fault detective diagnostic (FDD) approaches have been investigated and implemented for various industrial processes. However, industrial operations make it difficult to implement FDD techniques. To bridge the gap between th...
Source: Sensors - April 22, 2024 Category: Biotechnology Authors: Paolo Mercorelli Tags: Review Source Type: research
Sensors, Vol. 24, Pages 2655: Prototype Learning for Medical Time Series Classification via Human & ndash;Machine Collaboration
Sensors, Vol. 24, Pages 2655: Prototype Learning for Medical Time Series Classification via Human–Machine Collaboration
Sensors doi: 10.3390/s24082655
Authors:
Jia Xie
Zhu Wang
Zhiwen Yu
Yasan Ding
Bin Guo
Deep neural networks must address the dual challenge of delivering high-accuracy predictions and providing user-friendly explanations. While deep models are widely used in the field of time series modeling, deciphering the core principles that govern the models’ outputs remains a significant challenge. This is crucial for fostering the development of trusted models and facilitating...
Source: Sensors - April 22, 2024 Category: Biotechnology Authors: Jia Xie Zhu Wang Zhiwen Yu Yasan Ding Bin Guo Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2657: Adaptive Cruise Control Based on Safe Deep Reinforcement Learning
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Fei Gao
Adaptive cruise control (ACC) enables efficient, safe, and intelligent vehicle control by autonomously adjusting speed and ensuring a safe following distance from the vehicle in front. This paper proposes a novel adaptive cruise system, namely the Safety-First Reinforcement Learning Adaptive Cruise Control (SFRL-ACC). This system aims to leverage the model-free nature and high real-time inference efficiency of Deep Reinforcement Learning (DRL) to overcome the challenges of modeling difficulties and lower computational efficiency faced by current optimization control-based ACC methods while simultaneously ma...
Source: Sensors - April 22, 2024 Category: Biotechnology Authors: Rui Zhao Kui Wang Wenbo Che Yun Li Yuze Fan Fei Gao Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2646: A gm/ID-Based Low-Power LNA for Ka-Band Applications
This article presents the design of a low-power low noise amplifier (LNA) implemented in 45 nm silicon-on-insulator (SOI) technology using the gm/ID methodology. The Ka-band LNA achieves a very low power consumption of only 1.98 mW andis the first time the gm/ID approach is applied at such a high frequency. The circuit is suitable for Ka-band applications with a central frequency of 28 GHz, as the circuit is intended to operate in the n257 frequency band defined by the 3GPP 5G new radio (NR) specification. The proposed cascode LNA uses the gm/ID methodology in an RF/MW scenario to exploit the advantages of moderate inversi...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: David Galante-Sempere Jeffrey Torres-Clarke Javier del Pino Sunil Lalchand Khemchandani Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2650: Vehicle-Type Recognition Method for Images Based on Improved Faster R-CNN Model
anfa Wang
The rapid increase in the number of vehicles has led to increasing traffic congestion, traffic accidents, and motor vehicle crime rates. The management of various parking lots has also become increasingly challenging. Vehicle-type recognition technology can reduce the workload of humans in vehicle management operations. Therefore, the application of image technology for vehicle-type recognition is of great significance for integrated traffic management. In this paper, an improved faster region with convolutional neural network features (Faster R-CNN) model was proposed for vehicle-type recognition. Firstly, t...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Tong Bai Jiasai Luo Sen Zhou Yi Lu Yuanfa Wang Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2651: Robust Cooperative Fault-Tolerant Control for Uncertain Multi-Agent Systems Subject to Actuator Faults
This article investigates the robust cooperative fault-tolerant control problem of multi-agent systems subject to mismatched uncertainties and actuator faults. During the design process of the intermediate variable estimator, there is no need to satisfy fault estimation matching conditions, and this overcomes a crucial constraint of traditional observers and estimators. The feedback term of the designed estimator contains the centralized estimation errors and the distributed estimation errors of the agent, and this further improves the design freedom of the proposed estimator. A novel fault-tolerant control protocol is des...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Jiantao Shi Xiang Chen Shuangqing Xing Anning Liu Chuang Chen Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2652: Machine Tool Wear Prediction Technology Based on Multi-Sensor Information Fusion
jun Xie
The intelligent monitoring of cutting tools used in the manufacturing industry is steadily becoming more convenient. To accurately predict the state of tools and tool breakages, this study proposes a tool wear prediction technique based on multi-sensor information fusion. First, the vibrational, current, and cutting force signals transmitted during the machining process were collected, and the features were extracted. Next, the Kalman filtering algorithm was used for feature fusion, and a predictive model for tool wear was constructed by combining the ResNet and long short-term memory (LSTM) models (called ResN...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Kang Wang Aimin Wang Long Wu Guangjun Xie Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2644: Characterization of Running Intensity in Canadian Football Based on Tactical Position
This study aimed to use a data-driven approach to identify individualized speed thresholds to characterize running demands and athlete workload during games and practices in skill and linemen football players. Data were recorded from wearable sensors over 28 sessions from 30 male Canadian varsity football athletes, resulting in a total of 287 performances analyzed, including 137 games and 150 practices, using a global positioning system. Speed zones were identified for each performance by fitting a 5-dimensional Gaussian mixture model (GMM) corresponding to 5 running intensity zones from minimal (zone 1) to maximal (zone 5...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Abdullah Zafar Samuel Guay Sophie-Andr ée Vinet Am élie Apinis-Deshaies Rapha ëlle Creniault G éraldine Martens Fran çois Prince Louis De Beaumont Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2645: Exploring Human & ndash;Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion & ndash;Extension Performance across Varied Robot Assistance & ndash;Resistance Configurations
Sensors, Vol. 24, Pages 2645: Exploring Human–Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion–Extension Performance across Varied Robot Assistance–Resistance Configurations
Sensors doi: 10.3390/s24082645
Authors:
Denis Mosconi
Yecid Moreno
Adriano Siqueira
Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots being an important resource in this context, since they optimize therapy by applying tailored forces to assist or resist movements, contributing to improved p...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Denis Mosconi Yecid Moreno Adriano Siqueira Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2646: A g\({_m}\)/I\({_D}\)-Based Low-Power LNA for Ka-Band Applications
This article presents the design of a low-power low noise amplifier (LNA) implemented in 45 nm silicon-on-insulator (SOI) technology using the gm/ID methodology. The Ka-band LNA achieves a very low power consumption of only 1.98 mW andis the first time the gm/ID approach is applied at such a high frequency. The circuit is suitable for Ka-band applications with a central frequency of 28 GHz, as the circuit is intended to operate in the n257 frequency band defined by the 3GPP 5G new radio (NR) specification. The proposed cascode LNA uses the gm/ID methodology in an RF/MW scenario to exploit the advantages of moderate inversi...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: David Galante-Sempere Jeffrey Torres-Clarke Javier del Pino Sunil Lalchand Khemchandani Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2647: Smart Sensors and Smart Data for Precision Agriculture: A Review
rco Fossa
Precision agriculture, driven by the convergence of smart sensors and advanced technologies, has emerged as a transformative force in modern farming practices. The present review synthesizes insights from a multitude of research papers, exploring the dynamic landscape of precision agriculture. The main focus is on the integration of smart sensors, coupled with technologies such as the Internet of Things (IoT), big data analytics, and Artificial Intelligence (AI). This analysis is set in the context of optimizing crop management, using resources wisely, and promoting sustainability in the agricultural sector. ...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Abdellatif Soussi Enrico Zero Roberto Sacile Daniele Trinchero Marco Fossa Tags: Review Source Type: research
Sensors, Vol. 24, Pages 2648: Understanding the Nonlinear Response of SiPMs
do
A systematic study of the nonlinear response of Silicon Photomultipliers (SiPMs) was conducted through Monte Carlo (MC) simulations. The MC code was validated against experimental data for two different SiPMs. Nonlinearity mainly depends on the balance between the photon rate and the pixel recovery time. Additionally, nonlinearity has been found to depend on the light pulse shape, the correlated noise, the overvoltage dependence of the photon detection efficiency, and the impedance of the readout circuit. Correlated noise has been shown to have a minor impact on nonlinearity, but it can significantly affect the shap...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: V íctor Moya-Zamanillo Jaime Rosado Tags: Article Source Type: research
