Sensor Alarms Research Articles

Trackside sensors in unattended train mainline systems - A case study of alarm logs from Sweden

Implementing unattended train operation on the mainline could make the railway more competitive by reducing operating costs since there will be no staff onboard the train. This will, however, lead to new challenges. One of those challenges is how to deal with manually controlling trackside sensor alarms. In this paper, we study all trackside sensor alarms (hotbox/hotwheel and wheel damage) in Sweden for one year (2019) to study their frequency and context. The results show that freight trains have 10 times higher frequency for alarms per train kilometer than passenger trains. There are statistically significant seasonal and climate zone differences. The highest frequency of trackside alarms occurs in wintertime in the colder climate zone. The results can be used in the development of unattended train operation support systems on the mainline.

The experiences of older adults with cognitive impairment in using falls prevention alarms in hospital: A qualitative descriptive study.

Bed and chair sensor alarms are commonly used for falls prevention in hospitals, despite questionable efficacy. Research analysing older adults' experiences of alarms is scarce, and adults with cognitive impairment are consistently excluded. The aim of this study was to explore how older adults with cognitive impairment perceive and experience falls prevention alarms in hospital. A qualitative descriptive design investigated older adults' experiences of alarms in a Geriatric Evaluation and Management ward in Melbourne. Patients were included if they had been provided an alarm. Semi-structured interviews were the primary method of data collection with two observation sessions and medical record analyses completed to enable triangulation of findings. Data were subjected to thematic analysis, and the Person-Environment-Occupation framework was chosen to add insight into the complexities of older adults' experiences of alarms. All 11 participants had a level of cognitive impairment with delirium, confusion, or impulsiveness recorded in their medical file. Two overarching themes were identified: communication and collaboration with staff and rationalisation of alarm use. Participants' perceived staff were focussed on falls prevention but experienced a lack of communication about the purpose of alarms. Participants wanted an individualised approach to alarms. Some were comforted with the thought of alarms alerting staff, making them feel well cared for and believed alarms were a useful 'back-up'. Others found alarms uncomfortable, frustrating, and restricting. Application of the Person-Environment-Occupation framework provided insight into how enabling and restrictive factors can impact whether the alarm is experienced positively or negatively. Seven unwitnessed falls occurred during the participants' admissions. Thirty-four per cent of alarm triggers observed were considered false alerts. Older adults commonly reported negative experiences using bed/chair sensor alarms. Occupational therapists have the training to collaborate with people with cognitive impairment and assess the usefulness of alarms in reducing falls, based on how they interact with the older adult's unique person, environment, and occupation domains.

Smart Greenhouse Monitoring System Using Blynk IoT App

Aims: A smart greenhouse system that utilizes the Blynk IoT app is an innovative technology designed to automate greenhouse operations, thereby reducing labor and resource costs and optimizing plant growth.
 Study Design: In this paper we propose a real-time mobile app-based monitoring system to automate greenhouse agriculture. The system involves the usage of Blynk mobile application that allows users to monitor, control both manually and remotely as well as automation of various aspects of the greenhouse environment in real-time.
 Place and Duration of Study: Department of Computer Science and Engineering, American International University-Bangladesh (AIUB), Dhaka, Bangladesh between February 2023 to April 2023.
 Methodology: Multiple environmental sensors, temperature, humidity, soil moisture, light intensity, and Light Dependent Resistor (LDR) sensors continuously collect data. Farmers can remotely monitor and control the greenhouse using the Blynk IoT application. A fire sensor alarms it. Farmers can tailor alerts for environmental changes like irrigation or heating. They can manually and remotely control fans, lights, and humidifiers. If temperature, light intensity, or humidity drop below a specified threshold, the system turns on fans, lights, and humidifiers. A water pump that kicks on automatically based on soil moisture and can be regulated remotely ensures the plants get enough water.
 Results: The proposed system allows for real-time updates of sensor data and enables remote control of connected devices via the mobile app from any location, with notable fast processing subject to the quality of the internet connection.
 Conclusion: Upon successful implementation of this research, we anticipate the emergence of an advanced automated smart greenhouse monitoring system that will greatly benefit farmers in Bangladesh. This new method could change greenhouse and farm management, improving efficiency, cost, and crop yields.

Design of a Vibration Alert System

Homes, businesses, industries, and military situations must all be protected from invaders by security systems. They comprise cameras, motion detectors, and alarms that offer round-the-clock surveillance and quick alerts. Modern technology makes it possible to operate and monitor security systems remotely. There are home security systems, CCTV surveillance, motion sensor alarms, and biometric systems like fingerprint or facial recognition. The system that best suits a homeowner's demands and offers peace of mind is theirs to select. In this work we have designed an alarm system which reduces false alarms and increases home security by using cutting-edge sensor technology to detect vibrations from attempted break-ins. It simply interacts with current systems, guaranteeing a complete home security solution.

Interventions for preventing and reducing the use of physical restraints of older people in general hospital settings.

Interventions for preventing and reducing the use of physical restraints of older people in general hospital settings.

Optimizing the Physical & Social Environment Within Hospitals for Patients with Dementia: a Systematic Review.

BackgroundAs the population ages, the number of individuals living with dementia is increasing. This has implications for the health-care system, as people living with dementia are hospitalized more frequently and for longer periods. Because patients living with dementia are at increased risk for adverse events during admission, understanding how the acute care physical and social environments influence their outcomes is imperative. Thus, the objective of this review was to identify studies that modified the physical and/or social environment in acute care in order to improve care for hospitalized patients living with dementia.MethodsMEDLINE, Embase, and CINAHL databases were used to search for articles up to and including June 2021. PRISMA guidelines were followed. Two independent reviewers assessed citations and full texts against the following inclusion criteria: patients living with dementia/cognitive impairment, presence of a control group, and evidence of clinical or health systems outcomes. All published English-language articles meeting inclusion criteria were retrieved.ResultsFollowing the database search, 12,901 citations were retrieved with 11,334 remaining after duplication removal. Of these, 15 papers met inclusion criteria. Seven studies evaluated the physical environment (e.g., addition of electronic sensor alarms and environmental cues). The remaining studies evaluated specific programs (e.g., art, music, exercise, volunteer engagement, and virtual reality). The majority of studies were low to very low quality; only three studies were RCTs. Environmental cues may initially improve wayfinding, and exercise may reduce neuropsychiatric symptoms.ConclusionsAlthough there are several interventions, there is a lack of high-quality evidence available to determine what exactly needs to be incorporated into acute care settings to reduce adverse outcomes for patients with dementia.

HOSPITAL EMERGENCY SECURITY SYSTEM

The fire detection system combines the simultaneous measurements of smoke, carbon monoxide, and carbon dioxide. The security of campus against intruders moving in laboratories, class rooms, staffrooms or washrooms. The fire alarm system consists of Fire detectors (with can be smoke detector, heat, or Infra-Red detectors), control unit and alarm system. A fire detection system is developed based on the simultaneous measurements of temperature and smoke. The fire detection system with the alarm algorithm detected fires that were not alarmed by smoke sensors, and alarmed in shorter times than smoke sensors operating alone. Previous fire detection algorithms used data from sensors for temperature, smoke, and combustion products. The smoke sensor alarms when the analog output signal exceeds or equal the threshold value. The node includes analog sensors to measure smoke, carbon monoxide (CO) and temperature. A fire alarm system should reliably and in a timely way notify building occupants about the presence of fire indicators, such as smoke or high temperatures.

Effectiveness of adding alarms to flash glucose monitoring in adults with type 1 diabetes under routine care

AimWhether glucose sensor alarms improve metabolic control and are accepted by individuals with diabetes is unclear. Here, we investigated whether switching from a standard flash glucose monitoring system (FGM1) to a system equipped with hypo- and hyperglycemia alarms (FGM2) improves glycemic control and psychological outcomes in adults with type 1 diabetes (T1D).MethodsSubjects with T1D and > 4% of time in hypoglycemia or > 40% of time in hyperglycemia were studied while wearing FGM1 (4 weeks) and after switching to FGM2 for 8 weeks. The primary endpoint was the change in time in range (TIR 70–180 mg/dl [3.9–10.0 mmol/L]) after 4 weeks of FGM2 use. Time below range (TBR), time above range (TAR), mean glucose, coefficient of variation (CV), sensor scans, treatment satisfaction, and hypoglycemia fear were secondary outcomes.ResultsWe included 38 subjects aged 33.7 ± 12.6 year. During 4 weeks of FGM2 use, TIR increased from 52.8 to 57.0% (p = 0.001), TBR decreased from 6.2 to 3.4% (p < 0.0001) as did time < 54 mg/dl (from 1.4 to 0.3%, p < 0.0001) and CV (from 39.6% to 36.1%, p < 0.0001). These changes were confirmed after 8 weeks of FGM2 use. Treatment satisfaction improved and fear of hypoglycemia decreased.Subjects who had > 4% of time in hypoglycemia at baseline showed the greatest improvements in glucose control and treatment satisfaction.ConclusionSwitching from FGM1 to FGM2 improved TIR and treatment satisfaction and reduced fear of hypoglycemia. Participants who benefited most from switching from FGM1 to FGM2 were those prone to hypoglycemia.

Predicting and Preventing Nocturnal Hypoglycemia in Type 1 Diabetes Using Big Data Analytics and Decision Theoretic Analysis.

Background: Despite new glucose sensing technologies, nocturnal hypoglycemia is still a problem for people with type 1 diabetes (T1D) as symptoms and sensor alarms may not be detected while sleeping. Accurately predicting nocturnal hypoglycemia before sleep may help minimize nighttime hypoglycemia. Methods: A support vector regression (SVR) model was trained to predict, before bedtime, the overnight minimum glucose and overnight nocturnal hypoglycemia for people with T1D. The algorithm was trained on continuous glucose measurements and insulin data collected from 124 people (22,804 valid nights of data) with T1D. The minimum glucose threshold for announcing nocturnal hypoglycemia risk was derived by applying a decision theoretic criterion to maximize expected net benefit. Accuracy was evaluated on a validation set from 10 people with T1D during a 4-week trial under free-living sensor-augmented insulin-pump therapy. The primary outcome measures were sensitivity and specificity of prediction, the correlation between predicted and actual minimum nocturnal glucose, and root-mean-square error. The impact of using the algorithm to prevent nocturnal hypoglycemia is shown in-silico. Results: The algorithm predicted 94.1% of nocturnal hypoglycemia events (<3.9 mmol/L, 95% confidence interval [CI], 71.3-99.9) with an area under the receiver operating characteristic curve of 0.86 (95% CI, 0.75-0.98). Correlation between actual and predicted minimum glucose was high (R = 0.71, P < 0.001). In-silico simulations showed that the algorithm could reduce nocturnal hypoglycemia by 77.0% (P = 0.006) without impacting time in target range (3.9-10 mmol/L). Conclusion: An SVR model trained on a big data set and optimized using decision theoretic criterion can accurately predict at bedtime if overnight nocturnal hypoglycemia will occur and may help reduce nocturnal hypoglycemia.

Arduino based Fire Detection and Alarm System Using Smoke Sensor

The fire detection system combines the simultaneous measurements of smoke, carbon monoxide, and carbon dioxide. The security of campus against intruders moving in laboratories, class rooms, staffrooms or washrooms. The fire alarm system consists of Fire detectors (with can be smoke detector, heat, or Infra-Red detectors), control unit and alarm system. A fire detection system is developed based on the simultaneous measurements of temperature and smoke. The fire detection system with the alarm algorithm detected fires that were not alarmed by smoke sensors, and alarmed in shorter times than smoke sensors operating alone. Previous fire detection algorithms used data from sensors for temperature, smoke, and combustion products. The smoke sensor alarms when the analog output signal exceeds or equal the threshold value. The node includes analog sensors to measure smoke, carbon monoxide (CO) and temperature. A fire alarm system should reliably and in a timely way notify building occupants about the presence of fire indicators, such as smoke or high temperatures.

Data-Driven Event Diagnosis in Transmission Systems With Incomplete and Conflicting Alarms Given Sensor Malfunctions

Accurate fault event diagnosis with incomplete and conflicting alarms given sensor malfunctions is a challenging problem for power system operators. To solve this problem, this study proposes a data-driven approach based on Mixed Integer Linear Programming (MILP) for fast determination of fault event scenarios with uncertainties. The uncertainties include failures and malfunction of relays and circuit breakers (CBs) as well as incomplete/incorrect sensor alarms at the control center. To improve the accuracy for fault event diagnosis, redundant alarms from multiple sources, i.e., Phasor Measurement Units (PMUs), Supervisory Control and Data Acquisition (SCADA), and Sequence of Events Recorders (SERs) are jointly used in this study. The temporal correlation of sensor alarms is incorporated in the constraints of the MILP model. The resulting data-driven algorithm determines the most credible fault scenario that is well supported by the available sensor alarms at the control center. Simulation results of the IEEE 14-bus system, the synthetic South Carolina 500-bus system, and a real-world complex event scenario demonstrate the effectiveness of the proposed approach for accurate and efficient fault event diagnosis.

Interventions for preventing falls in older people in care facilities and hospitals.

Cochrane review, hvor hensikten var a vurdere effekten av intervensjoner designet for reduksjon av fall blant eldre mennesker i sykehjem og sykehus.

RESEARCH OF CHARACTERISTICS OF SOLID IMPURITIES AND LIQUID SENSOR-ALARMS DURING OPERATION OF WELLS WITH DIFFERENT CONSTRUCTIONS OF PRODUCTION HORIZON TAPPING

The use of sensor-alarms (SA) of Sigma-Optic JSC integrated into the remote control system of the Cenomanian boreholes of the Kharvutinskaya area Yamburgskoye oil and gas condensate field is carried out to control the content of solid impurities and liquid in the gas flow at five levels in the DSP-EAC-2 modification and seven levels in the modification of DSP-EAC-2. The article presents the results of research on characteris- tics and a comparative analysis of indications of regular and upgraded SA in the frame of complex gas dynamic studies. Analysis of field data for the period of standard sensors operation has shown the need for separate signals extraction for the content of the phase components of mechanical impurities: sand and hydrate structures. When studying the SA character- istics in laboratory conditions, different forms of pulses-responses of the action of elastoplastic impacts of hydrate particles and elastic impacts of sand particles were experimentally established. The main differences between the modifications of DSP-EAC-2 are as follows: an improved signal processing algorithm, a variable power supply scheme and an extended range of levels of excess phase components in the formation mixture. A controlled range of SA operation is established for the content of the dropping liquid in the gas flow from 6 to 100 liters per hour (0.144- 2.4 m³ per day). Synchronous registration and satisfactory comparative readings of SA are shown in conditions of constant fluid flow from the bottom of the well.

Contamination source identification based on sequential Bayesian approach for water distribution network with stochastic demands

ABSTRACTEfficient identification of the source of contamination in a water distribution network is crucial to the safe operation of the system. In this article, we propose a real-time sequential Bayesian approach to deal with this problem. Simulations are conducted to simulate hydraulic information and the propagation of contamination in the network. Sensor alarms are recorded in multiple simulations to establish the observation probability distribution function. Then this information is used to compute the posterior probability of each possible source for the observed alarm pattern in real time. Finally, the contamination source is identified based on a ranking of the posterior probability. The key contribution of this work is that the probability distributions for all possible observations are organized into a concise hierarchical tree structure and the challenge of combinatorial explosion is avoided. Furthermore, a variation analysis of the posterior probability is conducted to give significance probability to the obtained identification result. The effectiveness of this method is verified by a case study with a realistic water distribution network.

Assessment of continuous acoustic respiratory rate monitoring as an addition to a pulse oximetry-based patient surveillance system.

Technology advances make it possible to consider continuous acoustic respiratory rate monitoring as an integral component of physiologic surveillance systems. This study explores technical and logistical aspects of augmenting pulse oximetry-based patient surveillance systems with continuous respiratory rate monitoring and offers some insight into the impact on patient deterioration detection that may result. Acoustic respiratory rate sensors were introduced to a general care pulse oximetry-based surveillance system with respiratory rate alarms deactivated. Simulation was used after 4324 patient days to determine appropriate alarm thresholds for respiratory rate, which were then activated. Data were collected for an additional 4382 patient days. Physiologic parameters, alarm data, sensor utilization and patient/staff feedback were collected throughout the study and analyzed. No notable technical or workflow issues were observed. Sensor utilization was 57%, with patient refusal leading reasons for nonuse (22.7%). With respiratory rate alarm thresholds set to 6 and 40breaths/min., the majority of nurse pager clinical notifications were triggered by low oxygen saturation values (43%), followed by low respiratory rate values (21%) and low pulse rate values (13%). Mean respiratory rate collected was 16.6±3.8breaths/min. The vast majority (82%) of low oxygen saturation states coincided with normal respiration rates of 12-20breaths/min. Continuous respiratory rate monitoring can be successfully added to a pulse oximetry-based surveillance system without significant technical, logistical or workflow issues and is moderately well-tolerated by patients. Respiratory rate sensor alarms did not significantly impact overall system alarm burden. Respiratory rate and oxygen saturation distributions suggest adding continuous respiratory rate monitoring to a pulse oximetry-based surveillance system may not significantly improve patient deterioration detection.

Doing different things not doing things differently

IntroductionMajor business change is a complex process requiring clear direction, planning, specialist resources and above all a massive commitment from the organisation. Our Hospice has achieved such transformational change.AimsTo do...

Review: Use of continuous subcutaneous insulin infusion in special populations and circumstances in patients with type 1 diabetes

CSII (continuous subcutaneous insulin infusion) is a valuable therapeutic option for many patients with type 1 diabetes, specifically where hyperglycaemia or recurrent hypoglycaemia persist during MDI (multiple daily injection) therapy. Special situations under which the use of CSII requires consideration include pregnancy, surgery and exercise. There is no evidence that CSII and MDI therapy differ significantly in efficacy in relation to maternal or foetal outcomes. Accordingly, NICE (National Institute for Health and Clinical Excellence) recommends that pregnant women with insulin-treated diabetes should be offered CSII using the same criteria as the general population. While continuous intravenous insulin infusion may offer advantages over MDI in patients with diabetes undergoing surgery, the role of CSII is unclear. During sports, CSII can facilitate better glycaemic control by allowing the precise adjustment of the basal rate and the administration of small incremental doses, and this may be complemented by the use of CGM (continuous glucose monitoring). More generally, real-time CGM can substantially improve glycaemic control in poorly controlled patients and, using sensor alarms, reduce hyperglycaemia and hypoglycaemia, although the clinical role of this technology is not well defined. Further research should evaluate the potential value of CSII in other populations and clinical scenarios.

Reversing motor vehicle injuries: a preventable tragedy

In this letter to the editor, the authors review the problem of driveway motor vehicle injuries. They report their experience of treating two children within a short period of six months, both of whom had experienced major head trauma by an automobile being backed up in a home driveway. The authors briefly report the injuries sustained, including the first child's injuries that resulted in his death. They offer suggestions for preventive strategies, including fencing driveways off, adding sensor systems for when the automobile is in reverse, and using rear observing cameras. The authors propose that all new vehicles, not just those in the luxury class, be equipped with these reversing sensor systems, alarms, or cameras. The letter includes computed tomography (CT) brain scans of the two injured children.

Establishing a continuous glucose monitoring program.

Real-time continuous glucose monitoring (RT-CGM) devices provide detailed information on glucose patterns and trends, and alarms that alert the patient to both hyper- and hypoglycemia. This technology can dramatically improve the day-to-day management of patients with diabetes and promises to be a major advance in diabetes care. The safe and effective use of RT-CGM in diabetes management rests on an understanding of several physiological as well as technological issues. This article outlines the key issues that should be addressed in the training curriculum for patients starting on RT-CGM: (1) physiologic lag between interstitial and blood glucose levels and the implications for device calibration, and interpretation and use of data in diabetes management; (2) practical considerations with the use of sensor alarms and caveats in the setting of alarm thresholds; and (3) potential risk for hypoglycemia related to excessive postprandial bolusing by RT-CGM users, and the practical implications for patient training.

TECHNICAL NOTE—Spatial Queueing Analysis of an Interdiction System to Protect Cities from a Nuclear Terrorist Attack

We formulate and analyze a spatial queueing model concerning a terrorist who is attempting to drive a nuclear or radiological weapon toward a target in a city center. In our model, imperfect radiation sensors form a circular wall around the periphery of the city, and vehicles setting off sensor alarms (representing a terrorist or a nuisance alarm) arrive randomly at the perimeter of a circle (representing the wall of sensors) and drive toward the center of the circle. Interdiction vehicles, one in each wedge of the circle, chase the alarm-generating vehicles. We derive an accurate mathematical expression for the mean damage inflicted by a terrorist in this system in terms of the arrival rate of alarm-generating vehicles and the number of interdiction vehicles. Our results suggest that detection-interdiction systems using current technology are capable of mitigating the damage from a nuclear weapon made of plutonium, but not one made of uranium or a radiological weapon.