This study presents the development and characterization of a novel electronic nose system based on customized surface acoustic wave (SAW) sensors. The system includes four sensors, customized with different custom po...
详细信息
This study presents the development and characterization of a novel electronic nose system based on customized surface acoustic wave (SAW) sensors. The system includes four sensors, customized with different custom polymer coatings, in order to detect volatile organic compounds (VOCs). The main innovation lies in the design of a robust and versatile switching electronics system that allows for the integration of the SAW sensors into portable systems, as well as interoperability with other gas sensor technologies. The system includes a modular architecture that allows multiple sensor arrays to be combined to improve the selectivity and discrimination of complex gas mixtures. To verify the proper performance of the system and the detection capability of the manufactured sensors, experimental laboratory tests have been carried out. Specifically, ethanol and acetone measurements up to a 2000 ppm concentration have been performed. These preliminary experimental results demonstrate the capability of the SAW sensors with different response patterns across the sensor array. In particular, the sensor made with the polyvinyl acetate polymer exhibits high sensitivity to both VOCs.
In the era of rapidly advancing technologies, the integration of artificial intelligence (AI) and deep learning (DL) with sensor technologies is providing novel solutions across diverse fields, from healthcare [1,2,3,...
In the era of rapidly advancing technologies, the integration of artificial intelligence (AI) and deep learning (DL) with sensor technologies is providing novel solutions across diverse fields, from healthcare [1,2,3,4,5] to industrial applications [6,7,8,9,10]. These innovations enable more efficient data analysis, accurate predictions, and improved performance in real-world scenarios. This Special Issue brings together a collection of research articles that showcase the impact of AI and DL on sensor applications, highlighting their ability to address complex challenges such as sensor fault detection, environmental adaptations, and predictive *** were rigorously evaluated for their technical quality, leading to the selection of ten research articles and two review papers for inclusion in this Special Issue. These works focus on advancements in weed detection through deep learning and the application of explainable artificial intelligence (XAI) in medical contexts. The selected contributions are listed below, along with concise summaries of *** Special Issue showcases the transformative potential of artificial intelligence (AI) and deep learning in conjunction with sensor technologies, offering innovative solutions across a wide array of fields, from medical diagnostics to industrial applications. The diverse approaches presented in these papers emphasize the importance of personalized and efficient solutions in domains such as healthcare, resource-constrained embedded systems, traffic flow prediction, and additive manufacturing. The integration of machine learning models, particularly deep learning, has proven to be a powerful tool in enhancing sensor data analysis, improving accuracy, and optimizing performance.
Flexible pressure sensors have shown significant application prospects in fields such as artificial intelligence and precision manufacturing. However, most flexible pressure sensors are often prepared using polymer ma...
详细信息
Flexible pressure sensors have shown significant application prospects in fields such as artificial intelligence and precision manufacturing. However, most flexible pressure sensors are often prepared using polymer materials and precise micronano processing techniques, which greatly limits the widespread application of sensors. Here, this work chooses textile material as the construction material for the sensor, and its latitude and longitude structure endows the sensor with a natural structure. The flexible pressure sensor was designed using a multilayer stacking strategy by combining multilayer textile materials with two-dimensional MXene materials. The experiment shows that its sensitivity is 52.08 kPa-1 at 30 and 7.29 kPa-1 within 30-120 kPa. As a demonstration, these sensors are applied to wireless human motion monitoring, as well as related applications involving auxiliary communication and robotic arm integration. Furthermore, relevant demonstrations of sensor array applications are presented. This work provides inspiration for the design and application of flexible pressure sensors.
The active matrix resistive sensor arrays are widely used in a variety of fields because they can eliminate the crosstalk current problem found in passive matrix resistive sensor arrays. However, the ON-resistance of ...
详细信息
The active matrix resistive sensor arrays are widely used in a variety of fields because they can eliminate the crosstalk current problem found in passive matrix resistive sensor arrays. However, the ON-resistance of the pixel transistor used in the active matrix resistive sensor array causes voltage drop and reduces the sensing accuracy. Increasing the width of the pixel transistor can reduce the ON-resistance and improve accuracy, but it increases the required circuit area, resulting in a decrease in the integration density and spatial resolution of the array. To solve the problem of inaccuracy and large circuit area found in conventional active matrix resistive sensor arrays, we propose two types of readout circuits based on an additional feedback path. With the additional feedback path between the sensor and the column amplifier, the effect of the voltage drop on the pixel transistor can be eliminated. The measurement results show that the proposed Type I and Type II readout circuits achieve less than 0.1% of the maximum error, remarkably reduced from 997.4% of the conventional counterpart.
Fluorescence array sensors provide an effective strategy to mitigate the cross-reactivity of single fluorescence materials by exploiting their high dimensionality and exceptional sensitivity. However, conventional flu...
详细信息
Fluorescence array sensors provide an effective strategy to mitigate the cross-reactivity of single fluorescence materials by exploiting their high dimensionality and exceptional sensitivity. However, conventional fluorescent sensing arrays are often hindered by complex and bulky designs, resulting in low cost-effectiveness and severely restricting their potential for integration into compact sensing devices. Benefiting from its high integration advantage, photonic integration technology offers a promising solution for developing low-cost and miniaturized fluorescent gas sensor arrays. In this article, we present a novel fluorescence array sensor based on a silicon nitride photonic integration platform. This innovative device enables lab-on-chip functionality by integrating a microfluidic channel for efficient gas detection in a few square centimeters. The sensor demonstrates exceptional performance, accurately identifying six types of volatile organic compounds and achieving a remarkably low detection limit of 2.8 ppb for N-methylphenethylamine (MPEA). Notably, it exhibits high precision in detecting MPEA even within complex, high-concentration perfume mixtures. Moreover, this technology enables the expansion of the fluorescence array without increasing the sensor's volume, offering a practical solution for integrated fluorescence sensor array detection.
Navigation systems are developing rapidly;nevertheless, tasks are becoming more complex, significantly increasing the number of challenges for robotic systems. Navigation can be separated into global and local navigat...
详细信息
Navigation systems are developing rapidly;nevertheless, tasks are becoming more complex, significantly increasing the number of challenges for robotic systems. Navigation can be separated into global and local navigation. While global navigation works according to predefined data about the environment, local navigation uses sensory data to dynamically react and adjust the trajectory. Tasks are becoming more complex with the addition of dynamic obstacles, multiple robots, or, in some cases, inspection of places that are not physically reachable by humans. Cognitive tasks require not only detecting an object but also evaluating it without direct recognition. For this purpose, sensor fusion methods are employed. However, sensors of different physical nature sometimes cannot directly extract required information. As a result, AI methods are becoming increasingly popular for evaluating acquired information and for controlling and generating robot trajectories. In this work, a review of sensors for mobile robot localization is presented by comparing them and listing advantages and disadvantages of their combinations. Also, integration with path-planning methods is looked into. Moreover, sensor fusion methods are analyzed and evaluated. Furthermore, a concept for channel robot navigation, designed based on the research literature, is presented. Lastly, discussion and conclusions are drawn.
Air pollution, originating from both natural and human-made sources, presents significant threats to human health and the environment. This review explores the latest technological advancements in air quality sensors ...
详细信息
Air pollution, originating from both natural and human-made sources, presents significant threats to human health and the environment. This review explores the latest technological advancements in air quality sensors focusing on their applications in monitoring a wide range of pollution sources from volcanic eruptions and wildfires to industrial emissions, transportation, agricultural activities and indoor air quality. The review categorizes these sources and examines the operational principles, system architectures, and effectiveness of various air quality monitoring instruments including low-cost sensors, gas analyzers, weather stations, passive sampling devices and remote sensing technologies such as satellite and LiDAR. Key insights include the rapid evolution of sensor technology driven by the need for more accurate, real-time monitoring solutions that are both cost-effective and widely accessible. Despite significant advancements, challenges such as sensor calibration, standardization, and data integration remain critical for ensuring reliable air quality assessments. The manuscript concludes by emphasizing the need for continued innovation and the integration of advanced sensor technologies with regulatory frameworks to enhance environmental management and public health protection.
In situ torque measurement within the robotic harmonic reducer is highlighted for its advantages in maintaining joint stiffness and avoiding additional installation space. However, accurate measurements are challenged...
详细信息
In situ torque measurement within the robotic harmonic reducer is highlighted for its advantages in maintaining joint stiffness and avoiding additional installation space. However, accurate measurements are challenged by the ripple signal induced by the periodic squeezing of the wave generator. To address this interference, a torque sensor employing a strain rosette ring as the sensing element is developed. By strategically averaging strains at multiple positions distributed on the flexspline flange, the ripple signal can be effectively suppressed. As an important measuring component within the strain rosette ring, the sensitive unit structure is then optimized by the response surface methodology. Results highlight that the length of sensitive unit has an obvious effect on measurement. Subsequently, a prototype of the torque sensor is developed and evaluated. It is observed that relying on strain from one position makes it difficult to accurately reflect the load condition. This validates the effectiveness of the developed circumferential structure. In addition, experimental results unequivocally demonstrate the significant suppression of the ripple signal by the developed sensor. Specifically, a sinusoidal torque of 10.2 Nm is applied to the harmonic reducer while the wave generator rotates, the maximum difference between the output of the developed sensor and that from the high-precision torque sensor is 0.720 N m, and the root mean square (rms) level of the difference is 0.256 N m.
Electrochemical sensors are part of a diverse and evolving world of chemical sensors that are impacted by high demand and ongoing technological advancements. Electrochemical sensors offer benefits like cost-efficiency...
详细信息
Electrochemical sensors are part of a diverse and evolving world of chemical sensors that are impacted by high demand and ongoing technological advancements. Electrochemical sensors offer benefits like cost-efficiency, short response time, ease of use, good limit of detection (LOD) and sensitivity, and ease of miniaturization while providing consistent analytical results. These sensors are employed in various fields-such as healthcare and diagnostics, environmental monitoring, and the food industry-to detect bacteria, viruses, heavy metals, pesticides, and more. In this review, we provide a comprehensive overview of electrochemical sensing techniques, with a focus on enhancing sensor performance through the integration of vibration and hydrodynamic flow in microfluidic systems. We present a structured comparison of these methods, utilizing tables to highlight the approaches most effective for performance enhancement. Additionally, we classify various electrochemical sensing applications, offering insights into the practical utilization of these two techniques for lowering the LOD. Finally, we present a comparative analysis of relevant studies, highlighting how hydrodynamic flow and vibration impact the sensing mechanism. We also explore the potential of these techniques to facilitate the development of automated, high-throughput microfluidic platforms, thereby optimizing their functionality and efficiency.
Gas detection is crucial for detecting environmentally harmful gases. Organic field-effect transistor (OFET)-based gas sensors have attracted attention due to their promising performance and potential for integration ...
详细信息
Gas detection is crucial for detecting environmentally harmful gases. Organic field-effect transistor (OFET)-based gas sensors have attracted attention due to their promising performance and potential for integration into flexible and wearable devices. This review examines the operating mechanisms of OFET-based gas sensors and explores methods for improving sensitivity, with a focus on porous structures. Researchers have achieved significant enhancements in sensor performance by controlling the thickness and free volume of the organic semiconductor layer. Additionally, innovative fabrication techniques like self-assembly and etching have been used to create porous structures, facilitating the diffusion of target gas molecules, and improving sensor response and recovery. These advancements in porous structure fabrication suggest a promising future for OFET-based gas sensors, offering increased sensitivity and selectivity across various applications.
暂无评论