High-precision Sensor Research Articles

Personalized low-cost thermal comfort monitoring using IoT technologies

Thermal comfort plays an essential role in the well-being and productivity of occupants. Typically, thermal comfort is assessed either through surveys completed by building occupants or through sensor data that is analyzed using thermal comfort models. Automating comfort surveys and data collection processes reduce the risk of information loss, providing more accurate and personalized thermal comfort assessments over longer periods of time. To this end, this paper presents the design and implementation of a thermal comfort monitoring system consisting of low-cost hardware components and using IoT technologies. The system consists of intelligent wireless sensor nodes that collect and process environmental data, a portable main station that integrates and stores data, and a digital survey that provides feedback from building occupants. To ensure accuracy, the low-cost hardware components of the intelligent sensor nodes are calibrated in a climate chamber, using high-precision sensors for reference. After calibration, the system is deployed in a field test where several intelligent sensor nodes collect environmental data in an office, while occupants complete the digital thermal comfort survey. In addition, thermal comfort indexes are computed by the intelligent sensor nodes and compared with the feedback of each building occupant. The results indicate that the low-cost thermal comfort monitoring system successfully collects and integrates thermal comfort data from the intelligent sensor nodes and the digital survey, being able to create personalized thermal comfort profiles. In future work, the system can be used in large-scale thermal comfort surveys, to develop personalized thermal comfort models and to control personalized comfort systems.

In-Situ Calibration of Six-Axis Force/Torque Transducers on A Six-Legged Robot

Abstract Ground contact modeling for multi-legged locomotion is challenging due to the possibility of multiple slipping legs. To understand the interplay of contact forces among multiple legs, we integrated a robot with six high-precision 6-DoF force-torque sensors, and measured the wrenches (forces and torques) produced in practice. Here we present an in-situ calibration procedure for simultaneously measuring all foot contact wrenches of a hexapod using 6-DoF load cells installed at the hips. We characterized transducer offset, leg gravity offset and the wrench transformation error in our calibration model. Our calibration reduced the RSME by 63% for forces and 90% for torques in the residuals of the robot standing in different poses, compared with naive constant offset removal.

A Rapid and High-Precision Electronic Non-Metallic Substrate Thickness Detection Sensor Based on Coaxial Resonator

A Rapid and High-Precision Electronic Non-Metallic Substrate Thickness Detection Sensor Based on Coaxial Resonator

Pressure Characteristics and Secondary Ignition Effects of Gas Produced in RDE Using Lignite and Anthracite/CH4 Fuel.

This study aims to address the energy efficiency release and environmental impact of coal dust in rotating detonation engines (RDEs) by monitoring the detonation characteristics of lignite and anthracite in methane gas-solid mixtures using high-precision sensor technology. Experimental results indicate that the peak detonation pressure of anthracite is 1.4% higher than that of lignite, and its detonation wave propagation speed is at least 5.5% faster, suggesting that anthracite exhibits more stable and efficient fuel energy release characteristics during detonation. Additionally, the sensor technology enabled detailed recording of pressure fluctuations and gas composition changes during the detonation process, providing accurate data for assessing and controlling emissions of harmful gases such as carbon monoxide and carbon dioxide. These data are crucial for designing more efficient and environmentally friendly coal dust detonation systems, enhancing mine safety and environmental protection. The outcomes of this research not only advance technological progress in the field of energy science but also address efficiency and environmental issues in industrial applications, offering significant support for achieving safer and more sustainable energy production methods.

Surpassing the Quantum Limit in Bosonic Loss Estimation without Quantum Probes.

Bosonic loss estimation has an important role in quantum metrology. It was once believed that the ultimate precision of this task is restricted to the standard quantum limit if no quantum probe is involved. Nevertheless, a recent proposal showed that this limit can be surpassed by utilizing ring resonators with coherent state probe. Here, we experimentally realize the resonator-based bosonic loss estimation and verify the resonant enhancement effect. This Letter explores the advantages of resonator-based metrology and sheds light on the development of high-precision miniature sensors.

Micro-Opto-Electro-Mechanical Systems for High-Precision Displacement Sensing: A Review.

High-precision displacement sensing has been widely used across both scientific research and industrial applications. The recent interests in developing micro-opto-electro-mechanical systems (MOEMS) have given rise to an excellent platform for miniaturized displacement sensors. Advancement in this field during past years is now yielding integrated high-precision sensors which show great potential in applications ranging from photoacoustic spectroscopy to high-precision positioning and automation. In this review, we briefly summarize different techniques for high-precision displacement sensing based on MOEMS and discuss the challenges for future improvement.

Compact inertial sensors for measuring external disturbances of physics experiments

Compact, high-precision inertial sensors are needed in the control schemes of many modern physics experiments to isolate them from disturbances caused by seismic motion. We present an inertial sensor whose mechanical oscillator fits on a one-inch diameter optic. The oscillators achieve a mechanical Quality factor of a fundamental oscillation mode of 600,000 and a resonance frequency of 50 Hz, giving them a suspension thermal noise floor lower than all commercially available inertial sensors. The motion of this fundamental mode is suitable to encode inertial motion into the sensor readout. The oscillator is combined with an optical resonator readout scheme that achieves a displacement noise of 100 fm/Hz\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sqrt{\ ext{Hz}}$$\\end{document} above 0.2 Hz. We validate the sensors’ noise floor using a huddle test. Below 20 Hz, the sensor offers comparable performance to the best inertial sensors available today while being a fraction of the size. Above 20 Hz, the sensor is, to the author’s knowledge, the best demonstrated in the literature to date for such a sensor, with a self-noise floor of 0.1 ng/Hz\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sqrt{\ ext{Hz}}$$\\end{document}. The excellent performance of the sensors across seismically relevant frequencies, vacuum compatibility, and compact size make it a prime candidate for integration into sophisticated seismic isolation schemes, such as those used by gravitational wave detectors.

Automated line scan profilometer based on the surface recognition method

Existing high-precision measurement devices face numerous challenges when dealing with complex surfaces, including high manual involvement, low measurement efficiency, and high costs. It is even more difficult to obtain complete surface data, particularly when confronted with unknown surfaces. This paper combines a fringe projection sensor with a high-precision line-structured light sensor to construct a line scan profiler. It proposes a surface recognition measurement method to overcome these challenges. This method fully leverages the fringe projection sensor's wide-field advantage to identify the object's surface shape and pose quickly. Subsequently, through the point cloud extraction and path planning algorithms proposed in this paper, efficient and complete line scan measurement paths are automatically generated, thus achieving the automation of the measurement process. Experimental measurements of aspherical lenses, freeform reflective mirrors, and artificial knee joint models validate the advantages of this method over existing methods in terms of measurement efficiency, automation capability, and applicability.

DFT study of gas responses to CH4, H2S, and CO on TM Atom (Sc, V, Cr, Mn)-modified HfSe2 monolayers

In this study, the adsorption of waste gases (CH4, H2S, CO) generated during the extraction, processing, and utilization of natural gas on TM atom (Sc, V, Cr, Mn)-modified HfSe2​ surfaces were analyzed using Density Functional Theory (DFT) calculations. Initially, the doping effects of the four TM atoms were examined, followed by a detailed investigation of the adsorption of these three gases in terms of adsorption energy, band structure, density of states (DOS), charge transfer, and recovery time. Among the TM atoms, Sc doping was found to be the most favorable due to its highest adsorption energy. However, in subsequent gas adsorption processes, it was observed that V and Mn-modified HfSe2 surfaces exhibited better adsorption performance for H2S and CO. Furthermore, it was discovered that at high temperatures, V-HfSe2 can function as a gas sensor for CO, while at room temperature, V-HfSe2 and Mn-HfSe2 can serve as high-precision real-time monitoring sensors for H2S and CO, respectively.

Overview of Radar Alignment Methods and Analysis of Radar Misalignment's Impact on Active Safety and Autonomous Systems.

The rapid development of active safety systems in the automotive industry and research in autonomous driving requires reliable, high-precision sensors that provide rich information about the surrounding environment and the behaviour of other road users. In practice, there is always some non-zero mounting misalignment, i.e., angular inaccuracy in a sensor's mounting on a vehicle. It is essential to accurately estimate and compensate for this misalignment further programmatically (in software). In the case of radars, imprecise mounting may result in incorrect/inaccurate target information, problems with the tracking algorithm, or a decrease in the power reflected from the target. Sensor misalignment should be mitigated in two ways: through the correction of an inaccurate alignment angle via the estimated value of the misalignment angle or alerting other components of the system of potential sensor degradation if the misalignment is beyond the operational range. This work analyses misalignment's influences on radar sensors and other system components. In the mathematically proven example of a vertically misaligned radar, pedestrian detectability dropped to one-third of the maximum range. In addition, mathematically derived heading estimation errors demonstrate the impact on data association in data fusion. The simulation results presented show that the angle of misalignment exponentially increases the risk of false track splitting. Additionally, the paper presents a comprehensive review of radar alignment techniques, mostly found in the patent literature, and implements a baseline algorithm, along with suggested key performance indicators (KPIs) to facilitate comparisons for other researchers.

High-precision flexible sweat self-collection sensor for mental stress evaluation

As a stress hormone existing in the human body, cortisol can reflect the psychological stress and health status in daily life, and is a potential biomarker of the body’s stress response. To effectively collect sweat and accurately identify the target, this paper reports a flexible wearable cortisol detection device with outstanding reliability and sensitivity. Molecular imprinted polymer (MIP) ensures cortisol specificity. And carbon nanotubes (CNT) on electrodes increase sensitivity, expanding the detection range to 10−3 to 104 nM, with sensitivity at 189.2 nA/lg(nM). In addition, porous chitosan hydrogel (PCSH) collects sweat effectively, its adhesive properties and 80% swelling rate offer a low-cost alternative to microfluidics. Flexible printed circuit board (FPCB) and serpentine electrode (SE) ensure device durability. This non-invasive, highly sensitive device offers a novel method for mental stress monitoring and clinical diagnosis, advancing human physiological state monitoring.

Sensor based interactive digital entertainment and gamified training to alleviate basketball player fatigue

In recent years, due to the increasing number of basketball games and training activities, basketball players often face the problem of fatigue and injury. This study aims to develop an interactive digital entertainment and gamification training method to provide basketball players with more efficient training methods and enhance their training fun. Sensors can be installed in various key parts of the athlete’s body, through the use of high-precision sensor equipment, real-time acquisition of athlete action data, the use of machine learning and data mining technology, real-time analysis and modeling of sensor data to extract key information and movement patterns. Using gamified training theory to design interactive digital entertainment system, develop a series of training scenarios and gamified tasks for different technical elements, combine sensor data and motion analysis results, and provide athletes with personalized training plans and feedback mechanisms to help them improve their technical level. Through an interactive digital entertainment system, basketball players can train and compete in a virtual environment. They can complete various training tasks by interacting with the system, which will give real-time evaluation and guidance based on the athlete’s performance to help them correct mistakes, improve technique and improve training results.

Designing gram-scale resonators for precision inertial sensors

Recent advances in glass fabrication technology have allowed for the development of high-precision inertial sensors in devices weighing of the order of grams. Gram-scale inertial sensors can be used in many applications with tight space or weight requirements. A key element of these devices’ performance is the behavior of a mechanical resonator. We present a detailed study on the design of resonators for such sensors. First, we consider how the mechanical parameters of a resonator couple with an inertial sensor’s performance. Then, we look at how to geometrically design resonators to achieve specific mechanical behavior without undergoing brittle failure. Both analytic tools and finite element analysis are used to this end. We then derive expressions that can be used to optimize the performance of an inertial sensor for a specific sensitive bandwidth. A simple geometry used throughout the field is studied as an example. However, the results are presented in a general form so that they can be easily adapted to any required geometry and use case. Ultimately, the results presented here guide the design of gram-scale inertial sensors and will improve the performance of devices that follow them. Published by the American Physical Society 2024

Hyposense: An Integrated Sensor Device for Hydroponics Farm Monitoring

In recent years, the monitoring of hydroponics farms has undergone a significant transformation due to the integration of sensors. However, the conventional method of manually observing measurements from multiple sensors has proven to be excessively time-consuming and costly. Additionally, the lack of automatic data recording options in most sensors has been a limiting factor. To address these challenges, we conducted an experimental study to introduce a novel integrated sensor device named “HypoSense”, designed to monitor essential parameters such as temperature, humidity, pH, light intensity, Total Dissolved Solids (TDS), and Electrical Conductivity (EC) in hydroponic systems. HypoSense consists of three microcontroller units (MCUs) incorporated with two controlling circuits based on the Arduino platform: the Arduino UNO, ESP32, and the ESP8266 (NodeMCU) microcontrollers. The device is designed using high-precision sensors, including the DHT11 for temperature and humidity monitoring, an Analog pH sensor kit for pH measurement, BH1750 for light intensity, and an Analog TDS sensor kit for TDS and electrical conductivity measurements. These sensors were chosen for their reliability, accuracy, and compatibility with the Arduino platform, ensuring that HypoSense delivers precise and consistent readings. HypoSense is a cost-effective, portable sensor device specially designed for monitoring growth parameters simultaneously in hydroponic farming, saving growers time and effort. The evaluation was carried out in two phases. Firstly, field sensors were employed to calibrate HypoSense device sensors. Next, a secondary evaluation was conducted to confirm the practicality and user-friendliness of the HypoSense device. To facilitate the evaluation of HypoSense, we set up an indoor hydroponic system for growing tomatoes and lettuce. The results of these evaluations, focusing on the performance and applicability of the HypoSense device, will provide valuable insights for hydroponic growers and future researchers in precision agriculture.

High-precision fiber-optic salinity sensor by micro-cavity and intensity demodulation

In this paper, a hollow-core fiber based micro-cavity Mach-Zehnder interferometer is realized and demonstrated by arc-discharged large lateral-offset splicing. The transmission spectra are investigated and compared with respects to loss and extinction ratio, also the cavity length and offset are theoretically and experimentally optimized. The obtained results show that the concentration of salinity can affect the wavelength response, the average salinity and temperature sensitivities are −2.275 nm/‰ and 1.71 nm/°C, respectively. Moreover, more than 5-fold improvement of the real detection limit is gained by a narrow line-width tunable laser based intensity-demodulation system. And the detection limit of 0.031 ‰ is experimentally witnessed with a time-response of ∼280 ms.

A Portable Agriculture Environmental Sensor with a Photovoltaic Power Supply and Dynamic Active Sleep Scheme

A portable environmental sensor for agricultural applications is proposed that addresses key challenges in power supply, data transmission, and monitoring efficiency. The sensor features a photovoltaic power supply and a PID-based dynamic active–sleep scheme for sustainable energy management, maintaining optimal battery levels under varying solar conditions. Its compact, waterproof, and dustproof design (90 mm × 90 mm × 150 mm, 844 g) ensures robust and reliable operation in diverse agricultural environments. High-precision digital sensors monitor temperature, humidity, light intensity, and CO2 concentration. Equipped with low-power NB-IoT technology, the sensor supports real-time remote environmental monitoring. Our experimental results show effective continuous operation, accurate environmental measurements, and performance comparable to established data loggers. The advanced power management and precise sensing capabilities make this sensor a competitive solution for improving smart agriculture practices, particularly in resource-limited or off-grid settings.

Development of High-Precision NO2 Gas Sensor Based on Non-Dispersive Infrared Technology.

Increasing concerns about air quality due to fossil fuel combustion, especially nitrogen oxides (NOx) from marine and diesel engines, necessitate advanced monitoring systems due to the significant health and environmental impacts of nitrogen dioxide (NO2). In this study, a gas detection system based on the principle of the non-dispersive infrared (NDIR) technique is proposed. Firstly, the pyroelectric detector was developed by employing an ultra-thin LiTaO3 (LT) layer as the sensitive element, integrated with nanoscale carbon material prepared by wafer-level graphics technology as the infrared absorption layer. Then, the sensor was hermetically sealed using inert gas through energy storage welding technology, exhibiting a high detectivity (D*) value of 4.19 × 108 cm·√Hz/W. Subsequently, a NO2 gas sensor was engineered based on the NDIR principle employing a Micro Electro Mechanical System (MEMS) infrared (IR) emitter, featuring a light path chamber length of 1.5 m, along with integrated signal processing and software calibration algorithms. This gas sensor was capable of detecting NO2 concentrations within the range of 0-500 ppm. Initial tests indicated that the gas sensor exhibited a full-scale relative error of less than 0.46%, a limit of 2.8 ppm, a linearity of -1.09%, a repeatability of 0.47% at a concentration of 500 ppm, and a stability of 2% at a concentration of 500 ppm. The developed gas sensor demonstrated significant potential for application in areas such as industrial monitoring and analytical instrumentation.

High-Precision Low-Cost Mid-Infrared Photoacoustic Gas Sensor Using Aspherical Beam Shaping for Rapidly Measuring Greenhouse Gases

A high-precision low-cost mid-infrared photoacoustic sensor for greenhouse composite gases based on aspherical beam shaping is proposed and demonstrated. The assembled optical source module and luminous characteristics of infrared source are innovatively investigated and analyzed with aspherical beam shaping. The proposed aspherical-beam-shaping-technique could effectively reduce optical loss and enhance system sensitivity, achieving an effective power utilization ratio of a radiation source of 91% and sidewall noise ratio of 8.9%. Experiments verify the 1.7 times improvement in responsivity and 50% enhancement in minimum detection limit (MDL) on average. In terms of comprehensive greenhouse gas composites and with short integration time of 1 s, MDLs of CO2, CH4, N2O, NF3, SF6, PFC-14, and HFC-134a are 73 ppb, 267 ppb, 72 ppb, 81 ppb, 14 ppb, 9 ppb and 115 ppb, respectively. Furthermore, a 48 h continuous monitoring of H2O, CO2 and CH4 in the atmosphere is conducted and verifies the performance of the gas sensor. The developed sensor allows for the rapid route of low-cost and high-precision detection of multiple greenhouse gases.

Research on a smart bra design strategy and platform for breast health risk monitoring

To reduce the risk of breast disease in women, we proposed a new smart bra design scheme. We implanted high-precision temperature sensors into the bra for real-time data monitoring, and used multipoint comparison technology to obtain early warnings of breast lesions based on abnormal temperature data. The proposed monitoring system can perform functions such as real-time data feedback, periodic report recording, remote consultation, health management, and electronic medical record generation. Compared with previous approaches, the functionality of this smart bra is not affected by dynamic body movements or environmental temperature, and its monitoring range for breast diseases is wider. This study promotes the monitoring and prevention of breast diseases in women, leading to a shift from disease treatment to disease prevention.

Vibration damping method of cantilever structure considering redundant constraint of monocrystalline blade casting mold shell

Excessive vibrations of the mold shell during the manufacturing process of monocrystalline blades lead to dendirite and frekle defects in directional solidification. The dynamics of the casting lifting device-mold shell system is analysed theoretically to reveal the influence of key parameters such as excitation force, damping and stiffness on the monocrystalline blade casting. The effect of redundant constraint onto the system is analysed via the developed vibration model. A lifting device-mold shell system test bench is developed, a slide-support arm device is designed to provide redundant constraint. A self-developed high-precision sensor is used to test the vibration signals, and the effectiveness of the damping method is verified. The experimental results show that the redundant constraint can reduce the undesired vibration of mold shell by more than 77 %, which ensures the casting quality of monocrystalline blades. The proposed vibration damping method can provide a reference for the vibration damping of the cantilever machine.