Wireless Sensor System Research Articles

Self-powered wireless sensor system utilizing a thermoelectric generator for photovoltaic module monitoring application

In this work, we demonstrate a self-powered wireless PV module monitoring system that utilizes a thermoelectric generator (TEG) to convert residual thermal energy from the PV module into electrical power. We investigated the TEG performance with and without the heat sink. Results show that the temperature difference between the hot and cold sides of the TEG increased to 7.2 °C with the heat sink, compared to only 1 °C without it, at a hot side temperature of 50 °C. We integrated the TEG/heat sink with the PV module, which served as the heat source, achieving a maximum output power of 0.981 mW at a voltage of 0.06 V under a temperature gradient of 3.6 °C in a 1 sun condition. We successfully demonstrated a self-powered wireless PV monitoring sensor system by integrating a step-up voltage converter, microcontroller, IR thermometer, Bluetooth communication module, and the TEG/heat sink, which generated sufficient power for the monitoring system operation. The findings introduce a novel solution for wireless PV module monitoring that operates independently of grid connections or battery power. This innovation not only signifies advancements in renewable energy management but also opens new opportunities in the Internet of Things (IoT) sector.

Development of a wireless smart sensor system and case study on lifting risk assessment

With the widespread adoption of Industry 4.0 and smart manufacturing concepts across industries, sensor development, system integration, and data analysis have become important aspects of efficient manufacturing operations. In addition to monitoring the performance of machines, significant importance is given to human condition monitoring in factories, using body-worn sensors to ensure the well-being of workers and for injury prevention. This research presents the development of a body-worn sensor system capable of sampling acceleration and rotation data up to 400 Hz and wirelessly transmitting the data over Bluetooth Low Energy (BLE). Further, the communication protocols for data acquisition, data communication within the device, Real Time Operating System (RTOS) programming, and multi-threading are described. This system is designed in such a way that multiple devices can be connected to the Data acquisition (DAQ) system simultaneously, and data is collected from the sensors in a synchronized manner. This information is valuable for the wider adoption of sensor systems for human condition monitoring in industry. Lastly, to test the system’s capabilities, a case study of lifting risk assessment is presented, where data collected from the accelerometer and gyroscope are used to determine a relative estimate of the physical stress associated with a manual lifting task by using different machine learning (ML) algorithms. The case study highlights how sensor placement, feature extraction, and sensor types influence machine learning models. As the sensor system can perform computations on the edge, a framework to carry out real-time lifting risk assessment using lightweight algorithms and the most important data features is proposed.

Assessing the accuracy of a wireless sensor system for estimating lumbar moments during manual lifting tasks considering the effects of load weight, asymmetry, and height

This study assessed the accuracy of L5/S1 moment estimates calculated with an Inertial Motion Capture (IMC) system during an asymmetrical and variable height lifting task. The effects of load weight, asymmetry, and lifting height on estimates of lumbar moment have not been comprehensively considered in studies using IMC systems. Thirty-six participants engaged in tasks involving three loads, lifting heights, and trunk rotation angles. Lumbar moments were calculated using bottom-up and top-down biomechanical models. Gold-standard Optical Motion Capture (OMC) and Force Plates (FP) were used as the reference. A randomized block partially confounded design was used to compare the root mean square errors (RMSE) between the IMC and OMC-based reference estimates. The IMC system's estimated peak moments were 12%–13% lower than those estimated using the gold standard OMC-BU inverse dynamics, while the RMSE varied between 19 and 21 Nm. A Load*Height interaction was found; a trend was identified where the RMSE values increased as both the load and height levels increased. The angle did not show a significant effect on any of the tested scenarios. A close correspondence between the IMC and OMC-based moment estimates was established, with the load being the main factor affecting the differences between systems. The IMC system shows potential for use in occupational settings to capture data on the lumbar moments of workers, which could be utilized to assess ergonomic risk.

Magnetic transfer piezoelectric wind energy harvester with dual vibration mode conversion

Wind-induced vibration piezoelectric energy harvesters have garnered significant interest in recent years as a means to power autonomous wireless sensor systems. A magnetic transfer piezoelectric wind energy harvester (MT-PWEH) is proposed and its durability, power generation performance and environmental adaptability are improved utilizing dual mode conversion. This MT-PWEH incorporated a downstream rectangular baffle, which facilitated the transition of the hollow cylinder from a traditional single vortex-induced vibration to a coupled vibration involving both vortex-induced vibration and galloping (i.e., the first vibration mode conversion). Besides, the vibration direction of the hollow cylinder was perpendicular to the vibration direction of the transducer, which achieved the purpose of limiting the amplitude (i.e., the second vibration mode conversion). The feasibility of MT-PWEH was confirmed through theoretical analysis, CFD simulation, fabrication and experiments. The experimental results demonstrated that the working characteristics of MT-PWEH were significantly affected by position and size of the baffle. Specifically, the ratio of the maximum cut-in wind speed of 12.5 m/s to the minimum cut-in wind speed of 1.2 m/s reached 10.4. Additionally, a maximum power output of 0.78 mW was recorded at 10 m/s with an optimal load resistance of 800 kΩ and 10 LEDs were drove successfully.

Enhanced In‐Plane Omnidirectional Energy Harvesting from Extremely Weak Magnetic Fields via Fourfold Symmetric Magneto‐Mechano‐Electric Coupling

AbstractMagneto‐mechano‐electric (MME) energy harvesters (EHs) have emerged as a promising solution for powering Internet of Things (IoT) sensor networks by capturing ambient stray magnetic fields in urban circumstance. Despite significant advancements, achieving milliwatt‐level power generation from extremely weak (<1 Oe) and randomly oriented magnetic fields remains challenging. Drawing inspiration from the configuration of cross‐shaped spider legs, this study introduces an innovative X‐shaped MME‐EH featuring fourfold symmetric architecture with symmetrically distributed magnets at each end, enabling near‐isotropic in‐plane omnidirectional energy harvesting. Under extremely weak magnetic fields 0.75 and 0.3 Oe at 60 Hz, the device achieves a record‐high output power of 7.31 and 1.67 mWRMS, respectively, representing a 362% improvement in normalized power over the state‐of‐the‐art results. The theoretical model attributes these gains to the synergistic enhancement effect of the second bending mode and the dual‐mode structure, collectively improving both magnetomechanical and electromechanical coupling by augmenting the magnetic moments and suppressing the clamp loss. The device further demonstrates robust real‐world applications, efficiently powering a wireless IoT sensor system by harvesting multidirectional magnetic field energy from household appliances. This work opens new avenues for developing efficient multimodal MME‐EHs capable of harnessing omnidirectional, weak magnetic fields for widespread IoT applications.

Comparison of continuous temperature measurement methods in the intensive care unit: standard bladder catheter measurements versus non-invasive transcutaneous sensors.

The purpose of this study was to compare a wearable system for body core temperature measurement versus bladder and tympanic thermometers in an intensive care setting. The question was, if continuous non-invasive sensors in the intensive care unit represent an alternative to current standard methods of invasive continuous bladder temperature measurement methods?Between May and September 2023, a comparative investigation involving 112 patients was conducted in a 20-bed surgical intensive care unit to assess various temperature probes, including those placed in the tympanic tube, bladder, and skin. To achieve this, a wireless non-invasive sensor system provided by greenTEG AG, Switzerland, was affixed to different body locations (clavicular and lateral chest) of each catheterized patient (equipped with a temperature probe) admitted to the intensive care unit. Furthermore, tympanic temperatures were recorded at specified intervals. The measurement duration ranged from a minimum of six hours to a maximum of six days, resulting in the analysis of a total of 355 simultaneous temperature measurements.In this study, a wearable temperature measurement system attached to two different body sites revealed a consistent negative bias compared to bladder temperature. In addition, the measurements were particularly influenced by body constitution. The tested system in all patients showed a mean absolute error (MAE) of 0.45°C for the lateral chest and 0.50°C for the clavicular position. Tympanic measurements had a mean absolute error of 0.35°C. In patients with body mass index (BMI) ≥ 25 the MAE increased to 0.5°C for the lateral chest and 0.56°C for the clavicular position. In contrast, the tympanic measurement had a reduced MAE of 0.32°C, which is well below this threshold when compared to bladder measurements.In conclusion the investigated system did not meet the clinically relevant acceptance criteria and showed low precision in correctly identifying fever episodes compared to invasive temperature probes, however its main advantage lies in its continuity and non-invasiveness. This makes it a potential alternative to intermittent tympanic measurement devices. In this study we were able to show, that in at least one subset of patients, the non-invasive and continuous device demonstrated a precision comparable to tympanic measurements.The accuracy of all non-invasive methods was lower than in previous studies, suggesting that the use of bladder temperature as reference and user related variations may have introduced additional errors.

Piezoelectric nanogenerator enabled fully self-powered instantaneous wireless sensor system

Self-powered real-time wireless sensor networks (WSNs) are vital for smart manufacturing, intelligent healthcare, and smart cities etc. Various nanogenerators have extensively exploited for powering these systems. Compared with triboelectric nanogenerators (TENGs), piezoelectric nanogenerators (PENGs) have smaller dimensions and can be easier to integrate into ICs, offering broader applications. However, fully self-powered instantaneous wireless sensor systems with PENGs are yet to be realized. Here, we present a PENG based, self-powered, instantaneous wireless (PSIW) sensor system. The integration of the PENG with an RLC sensing circuit facilitates the spontaneous generation of oscillating signals with encoded sensing information. To address the high internal impedance issue of PENGs, a piezoelectric voltage driven electronic switch is employed, ensuring that the oscillating signal's frequency and amplitude remain highly stable. The effects of variables on signal frequency are investigated in detail. The sensor system is utilized to sense bending (strain), and to monitor physical actions such as elbow swing, wrist bending, walking, running etc. Results showed that the PSIW sensor system can effectively monitor strain and bending angles, and judiciously detect body’s physical movements. By employing either frequency-based or amplitude-based sensing methods, the PSIW sensor system demonstrates versatility and adaptability for various sensing applications.

A Wireless Network for Monitoring Pesticides in Groundwater: An Inclusive Approach for a Vulnerable Kenyan Population.

Safe drinking water is essential to a healthy lifestyle and has been recognised as a human right by numerous countries. However, the realisation of this right remains largely aspirational, particularly in impoverished nations that lack adequate resources for water quality testing. Kenya, a Sub-Saharan country, bears the brunt of this challenge. Pesticide imports in Kenya increased by 144% from 2015 to 2018, with sales data indicating that 76% of these pesticides are classified as highly hazardous. This trend continues to rise. Over 70% of Kenya's population resides in rural areas, with 75% of the rural population engaged in agriculture and using pesticides. Agriculture is the country's main economic activity, contributing over 30% of its gross domestic product (GDP). The situation is further exacerbated by the lack of monitoring for pesticide residues in surface water and groundwater, coupled with the absence of piped water infrastructure in rural areas. Consequently, contamination levels are high, as agricultural runoff is a major contaminant of surface water and groundwater. The increased use of pesticides to enhance agricultural productivity exacerbates environmental degradation and harms water ecosystems, adversely affecting public health. This study proposes the development of a wireless sensor system that utilizes radio-frequency identification (RFID), Long-range (LoRa) protocol and a global system for mobile communications (GSM) for monitoring pesticide prevalence in groundwater sources. From the system design, individuals with limited literacy skills, advanced age, or non-expert users can utilize it with ease. The reliability of the LoRa protocol in transmitting data packets is thoroughly investigated to ensure effective communication. The system features a user-friendly interface for straightforward data input and facilitates broader access to information by employing various remote wireless sensing methods.

A Wireless Wearable Ecosystem for Social Network Analysis in Free-living Animals.

Studying animal social systems requires understanding variations in contact and interaction, influenced by factors like environmental conditions, resource availability, and predation risk. Traditional observational methods have limitations, but advancements in sensor technologies and data analytics provide new opportunities. We developed a wireless wearable sensor system, "Juxta," with features such as modular battery packs and a smartphone app for data collection. A pilot study on free-living prairie voles (Microtus ochrogaster), a species with complex social behavior, demonstrated Juxta's potential for studying social networks and behavior. We propose a framework for merging temporal, spatial, and event-driven data, which can help explore complex social dynamics across species and environments.

Ambient nano RF-Energy driven self-powered wearable multimodal real-time health monitoring

As the trend of population aging intensifies, the demand for continuous and efficient health monitoring for solitary elderly individuals and those with limited self-care capabilities is growing. Traditional wearable health monitoring devices primarily rely on battery power, which not only incurs high maintenance costs but also risks interruption of monitoring due to battery depletion. To address these issues, this paper introduces a self-powered flexible wearable monitoring device utilizing far-field Radio Frequency Energy Harvesting (RFEH) technology. This device powers integrated sensors and Bluetooth by harvesting RF energy from ambient Wi-Fi and other wireless signals, enabling real-time monitoring of the wearer's physical behaviour and health status with immediate feedback via mobile terminals. Under conditions of 100 cm distance and a power intensity of 0.8 dBm, the system can charge a 220 μF capacitor to 4.12 V within just 23.24 seconds, ensuring stable operation of the device. Moreover, the monitoring device is equipped with a low-power wireless sensor system capable of sampling up to 100 Hz, which accurately and promptly tracks and analyzes key health indicators such as walking, physiological activities, and respiratory status. This technology provides a reliable health monitoring solution for elderly individuals living alone and those with difficulties in self-care, significantly enhancing the effectiveness of remote medical services, improving their quality of life, and reducing the occurrence of emergency medical events. This research not only advances wearable device technology but also paves new paths for health management in an aging society.

Wireless wearable sensors can facilitate rapid detection of sleep apnea in hospitalized stroke patients.

To evaluate wearable devices and machine learning for detecting sleep apnea in patients with stroke at an acute inpatient rehabilitation facility (IRF). A total of 76 individuals with stroke wore a standard home sleep apnea test (ApneaLink Air), a multimodal, wireless wearable sensor system (ANNE), and a research-grade actigraphy device (ActiWatch) for at least one night during their first week after IRF admission as part of a larger clinical trial. Logistic regression algorithms were trained to detect sleep apnea using biometric features obtained from the ANNE sensors and ground truth apnea rating from the ApneaLink Air. Multiple algorithms were evaluated using different sensor combinations and different apnea detection criteria based on the Apnea-Hypopnea Index (AHI≥5, AHI≥15). Seventy-one (96%) participants wore the ANNE sensors for multiple nights. In contrast, only forty-eight participants (63%) could be successfully assessed for OSA by ApneaLink; 28 (37%) refused testing. The best-performing model utilized photoplethysmography (PPG) and finger temperature features to detect moderate-severe sleep apnea (AHI≥15), with 88% sensitivity and a positive likelihood ratio (LR+) of 44.00. This model was tested on additional nights of ANNE data achieving 71% sensitivity (10.14 LR+) when considering each night independently and 86% accuracy when averaging multi-night predictions. This research demonstrates the feasibility of accurately detecting moderate-severe sleep apnea early in the stroke recovery process using wearable sensors and machine learning techniques. These findings can inform future efforts to improve early detection for post-stroke sleep disorders, thereby enhancing patient recovery and long-term outcomes.

A compact-size and high-power energy harvester using stacked flexible-PCB coils for rotational shaft applications

In this Letter, a compact-size and high-power energy harvester (EH) based on multilayer flexible printed circuit board (F-PCB) sheets is presented for wireless sensor system (WSS) applications on propulsion shafts. A 2 mm thin rotor is designed using two F-PCB sheets that integrate 12 coil bundles with a total number of coil turns of 368. A stator is designed in a fixture that can be installed in the bearing housing. Voltage and power of the fabricated EH were measured and analyzed at a rotational speed of 10–100 rpm. At 80–100 rpm, the average voltage and output increased linearly with increasing speed. In particular, at 100 rpm, the average voltage and power were 5.43 V and 1714 mW, respectively. This performance represents a significant improvement compared to previously published EHs. The proposed EH features the straightforward structure, facilitating easier power design and prediction, and it is adaptable to various rotational shaft applications.

Conformal, stretchable, breathable, wireless epidermal surface electromyography sensor system for hand gesture recognition and rehabilitation of stroke hand function

Surface electromyography (sEMG) plays a significant role in the everyday practice of clinic hand function rehabilitation. The materials and design of current typical clinic sEMG electrodes are rigid Ag/AgCl or flexible polyimide (PI) film, which cannot provide a stable interface between electrodes and skin for adequate long-term high-quality data. Thus, conformal, soft, breathable, wireless epidermal sEMG sensor systems have broad potential relevance to clinic rehabilitation settings. Herein, we demonstrate a stretchable epidermal sEMG sensor array system with optimized materials and structure strategies for hand gesture recognition and hand function rehabilitation. The optimized serpentine structures with marvelous stretchability and improved fill ratio, provide lower impedance and high-quality sEMG signals. Moreover, the easy-to-use airhole method further ensures stable and long-term contact with the skin for recording. In addition, integrated with a customized flexible wireless data acquisition system, the capability for real-time 8-channel sEMG monitoring is developed, and taking together with the CNN-based algorithm, the system can automatically and reliably realize the 7 kinds of hand gestures with an accuracy of 81.02%. Moreover, the low-cost yet high-performance epidermal sEMG sensor system demonstrated its conceptual feasibility in quantitatively evaluation of stroke patient’s hand and facilitating human-robot collaboration in hand rehabilitation by proof-of-the-concept clinical testing.

Ternary nano-composite wireless ammonia sensor based on Polyaniline/CuTsPc/AgNPs for food intelligent packaging

The integration of gas sensing unit and low-cost wireless communication equipment enables real-time detection of various environmental gases, which is of great significance for food safety, medical diagnosis and environmental monitoring. In this study, copper phthalocyanine powder (CuTsPc) was prepared by high temperature solid phase melting technology. Ternary ammonia sensors with exceptional sensitivity to ammonia and conductivity were successfully fabricated by growing polyaniline/copper phthalocyanine/silver nanoparticles (PANI/CuTsPc/AgNPs) composites on polyethylene terephthalate films by in-situ polymerization. The morphology and composition of the films were characterized by FTIR, XRD and SEM, respectively. The ammonia sensing performance of the films at room temperature was systematically investigated. It is found that the flexible PANI/CuTsPc/AgNPs gas sensor exhibited rapid response time (61 s), fast recovery time (19 s), low theoretical detection limit (0.234 ppm), high response value (3.6 towards 500 ppm NH3), and excellent stability at room temperature. These remarkable response characteristics can be attributed to the synergistic effect between protonic acid-doped PANI, CuTsPc derivatives with an electron-withdrawing group, and AgNPs possessing both chemical sensitisation and electron sensitisation. Finally, the sensor material was transformed into a label antenna pattern as well as sensor transducer through series and parallel antenna loop access methods to create a wireless sensor system based on near-field communication (NFC). This system can offer real-time sensing and monitoring of changes in food packaging environment by non-contact recognition way, making it highly promising for future applications in intelligent packaging.

Wireless wearable system based on multifunctional conductive PEG-HEMA hydrogel with anti-freeze, anti-UV, self-healing, and self-adhesive performance for health monitoring

Polymer gels, such as hydrogels, have been widely applied in biomedicine, flexible electronics, and soft robotics. However, due to the complexity of application environments, preparing hydrogels that can maintain comprehensive performance under harsh conditions remains a challenge. Herein, based on polyethylene glycol (PEG) and water as a mixed solvent and using hydroxyethyl methacrylate (HEMA) as a monomer, a conductive dual-network PEG-HEMA hydrogel with anti-freezing, anti-ultraviolet, self-healing, and self-adhesive functions was prepared. The results show that PEG-HEMA hydrogel remained unfrozen even at ‐20°C, with tensile strength and elongation at break of 49.946 KPa and 529.7%, high resolution (able to measure strains as low as 0.2%), good sensitivity and linearity (GF=1.076, R2=0.999), fatigue resistance (over 1000 cycles), and long-term storage capability (over one week). Furthermore, a small wireless wearable strain sensor system was developed by integrating the hydrogel with a microcontroller, which is capable of monitoring various human motion and physiological signals in real time and exhibiting excellent sensing performance. This work provides a straightforward approach for multifunctional hydrogels, and it is expected to attract widespread attention and applications in fields such as electronic skin, human-machine interaction, and human health monitoring.

Wireless Sensor System Based on Organohydrogel Ionic Skin for Physiological Activity Monitoring.

Supermolecular hydrogel ionic skin (i-skin) linked with smartphones has attracted widespread attention in physiological activity detection due to its good stability in complex scenarios. However, the low ionic conductivity, inferior mechanical properties, poor contact adhesion, and insufficient freeze resistance of most used hydrogels limit their practical application in flexible electronics. Herein, a novel multifunctional poly(vinyl alcohol)-based conductive organohydrogel (PCEL5.0%) with a supermolecular structure was constructed by innovatively employing sodium carboxymethyl cellulose (CMC-Na) as reinforcement material, ethylene glycol as antifreeze, and lithium chloride as a water retaining agent. Thanks to the synergistic effect of these components, the PCEL5.0% organohydrogel shows excellent performance in terms of ionic conductivity (1.61 S m-1), mechanical properties (tensile strength of 70.38 kPa and elongation at break of 537.84%), interfacial adhesion (1.06 kPa to pig skin), frost resistance (-50.4 °C), water retention (67.1% at 22% relative humidity), and remoldability. The resultant PCEL5.0%-based i-skin delivers satisfactory sensitivity (GF = 1.38) with fast response (348 ms) and high precision under different deformations and low temperature (-25 °C). Significantly, the wireless sensor system based on the PCEL5.0% organohydrogel i-skin can transmit signals from physiological activities and sign language to a smartphone by Bluetooth technology and dynamically displays the status of these movements. The organohydrogel i-skin shows great potential in diverse fields of physiological activity detection, human-computer interaction, and rehabilitation medicine.

A Self-Powered Wireless Sensor System (SP-WSS) for Real-Time Propulsion Shaft Monitoring

A Self-Powered Wireless Sensor System (SP-WSS) for Real-Time Propulsion Shaft Monitoring

Approach to Design of Piezoelectric Energy Harvester for Sensors on Electric Machine Rotors

The reliability and efficiency of components are key aspects in the automotive industry. Electric machines become the focus of development. Thus, improvements in efficiency and reliability have gained significance. While it is established to attach sensors to the fixed parts of machines, such as stators, moving parts like rotors pose a major challenge due to the power supply. Piezoelectric generators can operate as energy harvesters on rotors and thus enable the rotor-based integration of sensors. The research in this article proposes the first approach to the design of a piezoelectric energy harvester (PEH) for an electric machine rotor dedicated to powering a wireless sensor system. After introducing the field of PEHs, the integration of the proposed device on a rotor shaft is presented. Further, a gap between the provided and needed data for the design of a PEH is identified. To overcome this gap, a method is presented, starting with the definition of the rotor shaft dimensions and the applied mechanical loads, including a method for the calculation of the imbalance of the rotor. With the first set of dimensions of the shaft and PEH, a co-simulation is performed to calculate the power output of this rotor and PEH set. The results of the simulation indicate the feasible implementation of the PEH on the rotor, providing enough energy to power a temperature sensor.

Internet of Meta-Material Things: A New Paradigm for Passive Wireless Sensing Systems

Internet of Meta-Material Things: A New Paradigm for Passive Wireless Sensing Systems

A Flexible, Adaptive, and Self-Powered Triboelectric Vibration Sensor with Conductive Sponge-Silicone for Machinery Condition Monitoring.

Vibration sensors for continuous and reliable condition monitoring of mechanical equipment, especially detection points of curved surfaces, remain a great challenge and are highly desired. Herein, a highly flexible and adaptive triboelectric vibration sensor for high-fidelity and continuous monitoring of mechanical vibration conditions is proposed. The sensor is entirely composed of flexible materials. It consists of a conductive sponge-silicone layer and a fluorinated ethylene propylene film. It can detect vibration acceleration of 5 to 50 m s-2 and vibration frequency of 10 to 100Hz. It has strong robustness and stability, and the output performance barely changes after the durability test of 168000 working cycles. Additionally, the flexible sensor can work even when the detection point of the mechanical equipment is curved, and the linear fit of the output voltage and acceleration is very close to that when the detection point is flat. Finally, it can be applied to monitoring the working condition of blower and vehicle engine, and can transmit vibration signal to mobile phone application through Wi-Fi module for real-time monitoring. The flexible triboelectric vibration sensor is expected to provide a practical paradigm for smart, green, and sustainable wireless sensor system in the era of Internet of Things.