Passive Monitoring System Research Articles

Wireless passive condition monitoring system for aircraft

Wireless passive condition monitoring system for aircraft

Monitoring holograms for therapeutic ultrasound using passive cavitation beamforming

Acoustic holograms can generate cavitation patterns of complex spatial distribution by shaping and steering the focal spot of therapeutic ultrasound systems. However, when monitoring these systems by passive cavitation detection, off-axis therapeutical targets and the receiver directivity may not be aligned. In this paper, we present passive cavitation beamforming to monitor a therapeutical ultrasound system using holograms targeted to arbitrary locations, in which both therapeutic and passive cavitation monitoring systems use 3D-printed acoustic lenses. The therapeutic system uses an acoustic hologram to focus the ultrasound beam on the target, which is off-axis. Then, a second lens is designed to beamform the cavitation signals which emerge from the therapeutic target, steering the directivity of the passive cavitation detector in the direction of the therapeutic focus and, in addition, compensating for skull aberrations. The system is experimentally tested with an ex-vivo macaque skull and a blood vessel phantom with microbubbles. In addition, results are compared with a standard confocal configuration and an off-axis configuration in the absence of the monitor lens. A parametric study is performed by varying the amplitude of the emitted signal and the impact on the behaviour of the microbubbles is analysed based on the cavitation index values. Results show that monitoring holograms align the passive cavitation detector response with the focal spot of the targeted therapeutic transducer. These holograms encode a fixed beamformer for cavitation signals in reception, increasing the sensitivity of cavitation emission at the target. In this way, cavitation doses can be used to locally monitor the cavitation activity of microbubbles, thus opening a new path to low-cost monitoring of therapeutic ultrasound systems.

Passive well monitoring systems and carbon, capture and storage (CCS) application

With an increasing number of ageing subsea wells and a tightening of global regulations for well management, assuring well integrity is a key feature of risk management for oil and gas operators. Baker Hughes, in collaboration with Sentinel Subsea, has successfully deployed patented passive well monitoring systems able to detect a range of subsea emissions and alert well owners. This early detection and warning technology harnesses the natural forces and processes of chemistry and physics but does not use any electrical power for the monitoring and detection of fluids. Static mechanical structures and the natural buoyancy of escaping fluids of interest are used to gather fluids in the subsea environment where they are detected chemically using specially developed Triggers. By using fluid-specific Triggers, systems respond only to the fluid(s) of interest, not to other fluids typically encountered around subsea assets. When the target fluid has been detected passively, a coded signal beacon (previously dormant) is mechanically released to the ocean surface using self-buoyancy where an alarm is transmitted via satellite and the responsible party alerted. Systems are currently supporting multiple major and independent operators mitigate the risks associated with subsea wells globally. Based on these experiences, this paper discusses the development process of a passive well integrity monitoring system with application for carbon, capture and storage (CCS) sites.

Optimized Design of an Ultrasonic-Based High-Efficiency Wireless Passive Monitoring System for Sealed Metal Compartments.

The condition monitoring (CM) of sealed metal compartments (SMCs) is an urgently required restructure. Ultrasound penetrates SMCs to power and communicate with built-in sensors, enabling the CM of SMCs. However, current ultrasonic wireless power transfer and data communication (UWPTADC) systems are large and complex, and limited by the efficiency of energy transfer and data reliability. In this paper, an optimized design of a high-efficiency wireless passive monitoring system using UWPTADC techniques is proposed for SMC. The circuit model of the system is developed and analyzed to achieve an optimal design for efficient wireless power transfer and effective data communication coupling. A test system was constructed using a steel wall of 11 mm thickness as a validation object. At the ultrasonic carrier frequency of 1.045 MHz, the system has an energy transfer efficiency of 60%, and a communication rate of 50 kbps. In addition, the system realizes temperature and humidity monitoring inside a 13 mm thick cylindrical SMC, simulating the process of ultrasonic CM of an actual engine compartment. The system provides a wiring-free and battery-free solution for CM in SMCs, advancing CM in aerospace, marine and other fields.

Assistive technologies and aging in place for people with dementia and disabilities: a proof-of-concept study with in-home passive remote monitoring with interactive communication functions

Purpose Can assistive technologies (ATs) support aging in place for people with dementia and disability? In seeking to go beyond the persistent institutional care delivery paradigm, this proof-of-concept study tested the feasibility of home care delivery using sensors and remote communication devices. This article reports the collaborative efforts among care professionals, care recipients and family caregivers in their private home environment and the impact of in-home passive remote monitoring (PRM) system on the users. The purpose of this study was to investigate the usability and impact of a PRM system combining in-house passive remote monitoring and an interactive communication function. Methods In order to realize AT-supported, person-centered aging in place, a new care delivery model was designed, developed and tested for the duration of 12 weeks. The study was conducted with 5 older people (1 with severe disability and 4 with dementia), their primary family carers with 15 care professionals as users. Results The findings indicate that there were some technical issues. However, the overall assessment of the system performance was positive, and the users expressed favorable views regarding its preventive and interactive nature. The importance of team-based care delivery, adjusted to fit the PRM equipment, was also highlighted. Faced with the challenge of meeting the increasing demand for person-centered care with limited resources, there will be a greater need for better integration of improved ATs. The study indicates ATs’ potential for enhancing the quality of life for those involved in caregiving, while stressing the significance of stakeholders’ engagement, skills and teamwork.

Reading Between the Heat

Stress impacts our physical and mental health as well as our social life. A passive and contactless indoor stress monitoring system can unlock numerous important applications such as workplace productivity assessment, smart homes, and personalized mental health monitoring. While the thermal signatures from a user's body captured by a thermal camera can provide important information about the "fight-flight" response of the sympathetic and parasympathetic nervous system, relying solely on thermal imaging for training a stress prediction model often lead to overfitting and consequently a suboptimal performance. This paper addresses this challenge by introducing ThermaStrain, a novel co-teaching framework that achieves high-stress prediction performance by transferring knowledge from the wearable modality to the contactless thermal modality. During training, ThermaStrain incorporates a wearable electrodermal activity (EDA) sensor to generate stress-indicative representations from thermal videos, emulating stress-indicative representations from a wearable EDA sensor. During testing, only thermal sensing is used, and stress-indicative patterns from thermal data and emulated EDA representations are extracted to improve stress assessment. The study collected a comprehensive dataset with thermal video and EDA data under various stress conditions and distances. ThermaStrain achieves an F1 score of 0.8293 in binary stress classification, outperforming the thermal-only baseline approach by over 9%. Extensive evaluations highlight ThermaStrain's effectiveness in recognizing stress-indicative attributes, its adaptability across distances and stress scenarios, real-time executability on edge platforms, its applicability to multi-individual sensing, ability to function on limited visibility and unfamiliar conditions, and the advantages of its co-teaching approach. These evaluations validate ThermaStrain's fidelity and its potential for enhancing stress assessment.

Evaluating passive physiological data collection during Spravato treatment

Spravato and other drugs with consciousness-altering effects show significant promise for treating various mental health disorders. However, the effects of these treatments necessitate a substantial degree of patient monitoring which can be burdensome to healthcare providers and may make these treatments less accessible for prospective patients. Continuous passive monitoring via digital devices may be useful in reducing this burden. This proof-of-concept study tested the MindMed Session Monitoring System™ (MSMS™), a continuous passive monitoring system intended for use during treatment sessions involving pharmaceutical products with consciousness-altering effects. Participants completed 129 Spravato sessions with MSMS at an outpatient psychiatry clinic specializing in Spravato treatment. Results indicated high rates of data quality and self-reported usability among participants and health care providers (HCPs). These findings demonstrate the potential for systems such as MSMS to be used in consciousness-altering treatment sessions to assist with patient monitoring.

Research and experiment the wireless passive surface acoustic wave technology for conductor temperature monitoring of high voltage equipment

This paper presents the research and design of a passive thermal monitoring system using wireless temperature sensors based on the principle of surface acoustic wave (SAW). The monitoring system is employed on components that need to be monitored for heat generation, including switch contacts, busbars, and cable connections at switchgears or ring main units (RMUs). The basic impulse insulation level (BIL), or voltage spike tolerance, of the wireless SAW temperature sensor utilised in this study, means that it is not necessary to power it with sensors that meet the high criteria for equipment installed in closed cabinets or medium voltage cabinets. The research team’s activities in this study included software development, data transmission design and manufacture, and sensor selection. The system functions steadily, with a temperature error of no more than 2oC, according to the test findings under laboratory settings.

Type-testing of the TLD system used for the assessing the eye lens doses due to ionising radiation

Individual monitoring service at the Department for Radiation and Environmental Protection of Vinca Institute of Nuclear Sciences performs individual whole-body and extremities monitoring of exposed workers, using thermoluminescent dosimetry (TLD) method. The dosemeters for eye-lens personal dose equivalent measurements, Hp(3), are not regularly used at the workplaces in Serbia, even though the individual monitoring method is accredited and available at the dosimetry service. Type testing of Hp(3) dosemeters based on LiF: Mg,Ti, placed in modified ring holders was done following the changes in ISO 4037:2019 and IEC 62387:2020. The type testing was done by varying radiation-based influence quantities: photon energies ranging from 33.3 keV up to 1.25 MeV, angle of incidence values of 0°, 45°, 60°, 75°, dose range from 0.05 mSv to 10 Sv. The results show that the passive dosimetry monitoring system satisfies IEC 62387:2020 requirements in the mandatory range of influence quantities, except for the lowest tested energy of 33 keV, when incident radiation angle is ±60° and higher.

A New Technique for the Passive Monitoring of Particulate Matter: Olive Pollen Grains as Bioindicators of Air Quality in Urban and Industrial Areas

A new technique for the passive monitoring of particulate matter was developed, exploiting olive pollen as a bioindicator. We tested the pollen bioaccumulation efficiency when exposed to atmospheric particulate at three different sites in the Umbria region (Central Italy). Pollen grains, placed into sampling holders, were exposed in Perugia, a polluted town impacted by traffic emissions; in Terni, an industrial hotspot; and at Monte Martano, a regional rural site. At the end of the exposure period, the daily deposition fluxes of the soluble and insoluble elements and soluble molecular ions present in particulate were determined, and the bioaccumulation factor (BAF) and bioaccumulation index over time (BAIt) were derived to validate the passive monitoring system, distinguish the deposition contribute from natural pollen composition, and interpret the temporal dependence of the pollen exposure to pollutants. We observed BAFs greater than 1, which means that bioaccumulation occurs, and pollen can be considered a good passive sampler for several crustal and anthropic ions and toxic elements at all sites. BAIt values greater than 1 were detected only for some of the ions and metals previously present in the pollen, like Ca, Cr, and Mn at Terni; and nitrate, Ca, and Mn at Monte Martano and Perugia.

Ivycide: Smart Intrusion Detection System Against E-IoT Driver Threats

The rise of Internet of Things (IoT) devices has led to the proliferation of smart environments worldwide. Although commodity IoT devices are employed by ordinary end-users, complex environments such as smart buildings, government, or private offices, or conference rooms require customized and highly reliable IoT solutions. Enterprise Internet of Things (E-IoT) connect such environments to the Internet and are professionally managed solutions usually offered by dedicated vendors As E-IoT systems require specialized training, closedsource software, and proprietary equipment to deploy. In effect, E-IoT systems present an unprecedented, under-researched, and unexplored threat vector for an attacker. In this work, we focus on E-IoT drivers, software modules used to integrate devices into E-IoT systems, as an attack mechanism. We first present PoisonIvy, a series of generalized proof-of-concept attacks used to demonstrate that an attacker can use a malicious driver to perform denial-of-service attacks, gain remote control, and abuse E-IoT system resources. To defend against E-IoT driverbased threats, we introduce IVYCIDE, a novel intrusion detection system used to detect unexpected E-IoT network traffic from an E-IoT system. IVYCIDE operates as a passive monitoring system within an E-IoT system using machine learning and signature-based classification to detect POISONIVY attacks. We evaluated the performance of IVYCIDE in a realistic E-IoT deployment. Our detailed evaluation results show that IVYCIDE achieves an average accuracy of 97% in classifying the type of POISONIVY attack and operates without modifications or operational overhead to existing E-IoT systems.

On the impact of advanced driver assistance systems on driving distraction and risky behaviour: An empirical analysis of irish commercial drivers

Advanced driver assistance systems (ADAS) present promising benefits in mitigating road collisions. However, these benefits are limited when risky drivers continue engaging in distraction events. While there is evidence that real-time warnings help improve driving behaviour, the sustained benefits of warning-based ADAS on reducing driving distraction in light commercial vehicle (LCV) drivers remain unclear. This research determines the effect of receiving instant distraction warnings over two years using a naturalistic driving dataset comprising around one million trips from 373 LCV drivers in the Republic of Ireland. Furthermore, the study applies Association Rule Mining (ARM) to find the contextual variables (e.g., speed limit, road type, traffic conditions) that increase the likelihood of distraction events. The results show that warning-based ADAS providing real-time warnings helps reduce distraction events triggering driver inattention, forward collision, and lane departure warnings. Over half of the studied fleet reduced these warnings by at least 50% – lane departure after two months and driver inattention and forward collision after six months. It is found that both passive and active monitoring systems, coupled with coaching and rewards, significantly reduce aggressive driving behaviours tied to harsh acceleration (by 76%) and harsh braking (by 65%). The results of ARM show that the driving context introduces explanatory information for road safety programs. Low-speed urban roads and the summer season increase the likelihood of driver inattention and forward collision warnings. In contrast, high-speed rural roads increase the likelihood of lane departure warnings. These research findings support road safety stakeholders in developing risk assessments based on warning-based ADAS, targeted campaigns to reduce driving distraction, and driving coaching programs.

Prediction for Loosening Life of Bolted Joints Using IMUs With Dimensionality Reduction

Bolted joints are widely employed as fasteners, but the loosening of them leads to severe safety risks. Prediction for Remaining Bolt Loosening Life (RBLL) allows for more proactive management of equipment and can help to optimize maintenance schedules, which hence reduces maintenance costs. Due to the complex structure and various working conditions of bolted joints, it is difficult to describe the loosening process with an intrinsic mechanism. The lack of understanding on mechanism makes it difficult to predict RBLL using conventional approaches. This paper develops a passive monitoring system based on Inertial Measurement Units (IMUs) for monitoring multi bolts in complex structures. By analyzing the vibration signals obtained by bonded sensors around joints, the changes in structural properties caused by loosening can be detected and used to evaluate RBLL. A novel prediction algorithm for RBLL is presented in this paper: with a pipeline of preprocessing, signal feature extraction, dimensionality reduction, and regression, a mapping from vibration signals to RBLL are established. The dimensionality reduction methods compress original features into fewer but informative and non-redundant ones. The compression elimination undesirable noise and prevent overfitting, resulting in improvements in both prediction accuracy and training speed. Specifically, the number of features is compressed from 972 to 200, and Rooted Mean Squared Error (RMSE) is reduced to about 19.0% with Training Time Cost (TTC) to about 22.3%.

Application of Passive Wireless Temperature Online Monitoring System Based on Internet of Things Technology in Substation

With the improvement of the automation level of the power system, the number of operation and maintenance personnel continues to decrease, but the use of switchgear is quite large. Since the switchgear is a metal armoured device with a closed shell, the hot spots inside the switchgear cannot be detected in time during operation. Effective temperature measurement and the safety of equipment cannot be effectively guaranteed. In order to avoid the aging caused by the excessive current load of the switch cabinet, poor contact of cable joints and contacts, or long-term operation, which will cause heat in the place, forming a vicious circle and eventually leading to insulation breakdown or fire accidents, Establish a wireless temperature measurement system for switch cabinets to monitor the temperature of the parts where the equipment is prone to overheat, and issue an alarm message when the temperature rises abnormally. At present, the manual inspection of switch cabinets in the power supply system cannot effectively and timely detect fire hazards, so the problem of online monitoring of switch cabinet temperature is particularly prominent. Using the Internet of Things sensing technology and communication technology, build an Internet of Things-based electrical connection point temperature online monitoring system, the all-weather real-time monitoring of the connection parts of high-voltage electrical equipment can effectively reduce the equipment failure rate, promote the condition maintenance of power equipment, and ensure the safe and economical operation of the power system.

A PON Monitoring System Integrating Fault Detection and Localization

We propose and experimentally demonstrate an integrated passive optical network monitoring system for fault detection and localization. Fault detection technology is based on the recognition of reflection spectrum generated by each single fiber Bragg grating, which can support large-capacity user fiber fault monitoring. Fault localization method uses two different total received powers measured by an optical power meter to solve the established equation, and it shows a good accuracy compared with the OTDR measurement results. Fault detection and localization are carried out separately but share the same transmitter module. The introduction of the additional module ensures that the troubleshooting does not affect other normal user data communication. We also investigate the dynamic range requirements of the fault detection technology and the measurement error of the fault localization method. The calculation results show the required dynamic range for the recognition device can be maintained within a small range and the use of high-accuracy optical power meter can reduce the measurement error. The proposed monitoring system can simultaneously provide a large-capacity fault detection technology and high-accuracy fault localization method in a cost-sensitive passive optical network market.

Resilience of Delay-Sensitive Services With Transport-Layer Monitoring in SD-WAN

Today, more and more enterprises are embarking on a digital transformation where most of their applications are hosted in the Cloud. As a result, a reliable Wide Area Network (WAN) has become a primary need to interconnect their distributed branch offices and data centers that accommodate those applications. Software-Defined Wide Area Network (SD-WAN) represents the most promising technology solution for next-generation enterprise networks, being able to increase network agility and reduce costs. In this paper, we present an experimental SD-WAN solution capable of running and optimizing delay-sensitive high-priority services, such as real-time video streaming, while minimizing downtime caused by network failures. This solution comprises a monitoring and a traffic engineering system for SD-WAN. The first consists of a Transport-layer Passive Monitoring (TPM) system based on extended Berkeley Packet Filter (eBPF) technology with the goal of monitoring TCP flows; the second consists of an application, running inside the SD-WAN controller, with the goal of orchestrating the network traffic in consideration of the monitoring measurements by ensuring rapid recovery and resilience in case of unexpected congestion events. We validate our solution over two SD-WAN testbeds: the first is hosted in our laboratory at Politecnico di Milano, while the second is deployed in a municipal network of an Italian city. Results show that our SD-WAN solution can increase the overall service availability while meeting the stringent QoS requirements of delay-sensitive services.s

Safety of mRNA COVID-19 vaccines during pregnancy

Safety of mRNA COVID-19 vaccines during pregnancy

Passive Sweat-Based Pruritic Cytokine Detection and Monitoring System

Interleukin-31 has been reported to be involved with chronic skin conditions like atopic dermatitis (AD). This work focuses on the development of a portable IL-31 detection system that works with passive sweat over the physiologically relevant range-150–620 pg ml−1. Four simulated flaring profiles were used to benchmark the IL-31 rise and fall detection capabilities of the sensor. These temporal profiles were generated according to the SCORAD range for severity of AD and were spanned across different dosing regimens. The sensing platform displays good sensitivity with a limit of detection of 50 pg ml−1 and dynamic range of 50–750 pg ml−1 for the flaring profiles in synthetic and human sweat, and with coupled portable electronics. Furthermore, in order to create a robust and predictive system, a machine learning algorithm was incorporated to create a flare prediction system. This algorithm shows high accuracy for the test data sets and provides the proof-of-concept for the use of ml coupled electrochemical systems for chronic diseases like AD.

Three-dimensional reconstruction of large non-uniform surface wave plasma using multi-lens array attached to a single viewing port

A new passive monitoring system applied to large surface wave plasmas (SWP) is experimentally tested. In the first experiment, spatial distributions of the electron density and temperature are measured using double probes. Subsequently, integral photography with deconvolution techniques is applied to identify the three-dimensional emissivity distribution of SWP. The result obtained from the first experiment seems to identify the localization of SWP around the antenna launching an 860 MHz microwave.

Stakeholder Perspectives on In-home Passive Remote Monitoring to Support Aging in Place in the Province of New Brunswick, Canada: Rapid Qualitative Investigation.

BackgroundThe province of New Brunswick (NB) has one of the oldest populations in Canada, providing an opportunity to develop and test innovative strategies to address the unique health challenges faced by older adults. Passive remote monitoring technology has the potential to support independent living among older adults. Limited research has examined the benefits of and barriers to the adoption of this technology among community-dwelling older adults.ObjectiveThis study aimed to explore perceptions of in-home passive remote monitoring technology designed to support aging in place from the perspective of older adults, their family or friend caregivers, social workers, and government decision-makers in the province of NB, Canada.MethodsBetween October 2018 and March 2020, a rapid qualitative investigation of 28 one-on-one interviews was conducted in person or via telephone. Participants included 2 home support services clients and 11 family or friend caregivers who had used passive remote monitoring technology in their homes; 8 social workers who had worked as case managers for home support services clients; and 7 individuals who were key government decision-makers in the adoption, policy development, and use of the technology in the province of NB. The interviews focused on the following topics: decision to adopt the passive remote monitoring system, barriers to adopting the passive remote monitoring system, benefits of the passive remote monitoring system, impact on client health outcomes, and privacy concerns. The interviews were audio recorded, transcribed, and analyzed by a team of 6 researchers. Data analysis was conducted using a rapid assessment process approach that included matrix analysis.ResultsParticipants reported that the use of the remote monitoring system allowed older adults to live at home longer and provided caregiver relief. Stakeholders were invested in meeting the home support (home care) needs of older adults. However, when it came to the use of remote monitoring, there was a lack of consensus about which clients it was well-suited for and the role that social workers should play in informing clients and caregivers about the service (role ambiguity, gatekeeping, and perceived conflicts of interest).ConclusionsOur findings highlight many benefits and challenges of the adoption of passive remote monitoring for clients, their family or friend caregivers, and public provincial health and social services systems. Passive remote monitoring is a valuable tool that can provide support to older adults and their family or friend caregivers when it is a good fit with client needs. Further work is needed in NB to increase public and social workers’ awareness of the service and its benefits.