Event monitoring in a small and business enterprise

This paper presents an overview of the role and responsibilities of the system administrator, focusing on the need to monitor its technological infrastructure. The informatics infrastructure monitoring is, nowadays without a doubt, one of the main key points in business support. Large enterprises are no longer the only ones to feel the need to use these monitoring tools, but small and medium-sized enterprises, which also have IT environments of an increasing complexity, feel such a need. This results directly from the operation of how the business is supported on IT platforms as support for people and processes. When a system, which is vital to the organization, fails either at the hardware or software level, compromises the operating capacity and consequently the business continuity. Having this always in mind, it is extremely important to adopt monitoring systems that proactively or reactively, reduce the overall time of breaks caused by failures. A monitoring system is the way to ensure confidence in all components and the operational readiness of IT infrastructure.

Continuous glucose monitoring in diabetic long distance runners

Marathon running is growing in popularity, and many diabetic patients are participating in various marathon races all over the world each year. This study aimed to investigate the prevalence and extent of glycemic excursions (hypo- and hyperglycemic) during a marathon run in patients with well-controlled diabetes mellitus using a continuous glucose monitoring system (CGMS). Five subjects with type 1 and one patient with type 2 diabetes mellitus were monitored with the Medtronic MiniMed CGMS during the 2002 Vienna City Marathon (n = 3) or the Fernwarme run (n = 3) long distance runs of 42.19/15.8 km. All six patients finished their course. The CGSM system was well tolerated in all patients over an average duration of 34 +/- 4.0 hours and it did not limit the patients' activities. The mean running time for the Vienna city marathon was 257 +/- 8 min (247 to 274 min) and for the Fernwarme run 134 +/- 118 min (113 to 150 min). A total of 1470 blood glucose measurements (mean 245 readings per subject) were performed. During and after the marathons frequent hypo and hyperglycemic episodes with and without clinical symptoms were measured. Our data confirm that the CGMS may help to identify asymptomatic hypoglycemia or hyperglycemia during and after a long distance run. The system may also be helpful to improve our understanding about the individual changes of glucose during and after a marathon and may protect hypoglycemic or hyperglycemic periods in future races.

Monitoring Infants By Automatic Video Processing

This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 0.2% live births, 1.1% for preterm neonates, and 1.3% for infants weighing less than 2500 g at birth. Neonatal seizures can be classified into four main categories: clonic, tonic, myoclonic, and subtle. Seizures in newborns have to be promptly and accurately recognized in order to establish timely treatments that could avoid an increase of the underlying brain damage. Respiratory diseases related to the occurrence of apnoea episodes may be caused by cerebrovascular events. Among the wide range of causes of apnoea, besides seizures, a relevant one is Congenital Central Hypoventilation Syndrome (CCHS) \cite{Healy}. With a reported prevalence of 1 in 200,000 live births, CCHS, formerly known as Ondine's curse, is a rare life-threatening disorder characterized by a failure of the automatic control of breathing, caused by mutations in a gene classified as PHOX2B. CCHS manifests itself, in the neonatal period, with episodes of cyanosis or apnoea, especially during quiet sleep. The reported mortality rates range from 8% to 38% of newborn with genetically confirmed CCHS. Nowadays, CCHS is considered a disorder of autonomic regulation, with related risk of sudden infant death syndrome (SIDS). Currently, the standard method of diagnosis, for both diseases, is based on polysomnography, a set of sensors such as ElectroEncephaloGram (EEG) sensors, ElectroMyoGraphy (EMG) sensors, ElectroCardioGraphy (ECG) sensors, elastic belt sensors, pulse-oximeter and nasal flow-meters. This monitoring system is very expensive, time-consuming, moderately invasive and requires particularly skilled medical personnel, not always available in a Neonatal Intensive Care Unit (NICU). Therefore, automatic, real-time and non-invasive monitoring equipments able to reliably recognize these diseases would be of significant value in the NICU. A very appealing monitoring tool to automatically detect neonatal seizures or breathing disorders may be based on acquiring, through a network of sensors, e.g., a set of video cameras, the movements of the newborn's body (e.g., limbs, chest) and properly processing the relevant signals. An automatic multi-sensor system could be used to permanently monitor every patient in the NICU or specific patients at home. Furthermore, a wire-free technique may be more user-friendly and highly desirable when used with infants, in particular with newborns. This work has focused on a reliable method to estimate the periodicity in pathological movements based on the use of the Maximum Likelihood (ML) criterion. In particular, average differential luminance signals from multiple Red, Green and Blue (RGB) cameras or depth-sensor devices are extracted and the presence or absence of a significant periodicity is analysed in order to detect possible pathological conditions. The efficacy of this monitoring system has been measured on the basis of video recordings provided by the Department of Neurosciences of the University of Parma. Concerning clonic seizures, a kinematic analysis was performed to establish a relationship between neonatal seizures and human inborn pattern of quadrupedal locomotion. Moreover, we have decided to realize simulators able to replicate the symptomatic movements characteristic of the diseases under consideration. The reasons is, essentially, the opportunity to have, at any time, a 'subject' on which to test the continuously evolving detection algorithms. Finally, we have developed a smartphone App, called 'Smartphone based contactless epilepsy detector' (SmartCED), able to detect neonatal clonic seizures and warn the user about the occurrence in real-time.

Embedded progressive-three-layered fiber long-period gratings for respiratory monitoring

A long-period grating (LPG) was written into a progressive three-layered single-mode fiber that was embedded into a flexible platform as a curvature sensor. The spectral location and profile of the LPGs were unaltered after implantation in the platform. The curvature sensitivity was 3.747 nm m with a resolution of ± 1.1 × 10-2 m-1. The bend sensor is intended to be part of a respiratory monitoring system and was tested on a resuscitation training manikin. © 2003 society of Photo-Optical Instrumentation Engineers.

First in-vivo trials of a fibre Bragg grating based temperature profiling system

We describe the results of in-vivo trials of a portable fiber Bragg grating based temperature profile monitoring system. The probe incorporates five Bragg gratings along a single fiber and prevents the gratings from being strained. Illumination is provided by a superluminescent diode, and a miniature CCD based spectrometer is used for demultiplexing. The CCD signal is read into a portable computer through a small A/D interface; the computer then calculates the positions of the center wavelengths of the Bragg gratings, providing a resolution of 0.2°C. Tests were carried out on rabbits undergoing hyperthermia treatment of the kidney and liver via inductive heating of metallic implants and comparison was made with a commercial Fluoroptic thermometry system.

Embedded progressive-three-layered fiber long-period gratings for respiratory monitoring

A long-period grating (LPG) was written into a progressive three-layered single-mode fiber that was embedded into a flexible platform as a curvature sensor. The spectral location and profile of the LPGs were unaltered after implantation in the platform. The curvature sensitivity was 3.747 nm m with a resolution of ±1.1×10–2 m–1. The bend sensor is intended to be part of a respiratory monitoring system and was tested on a resuscitation training manikin.

First in-vivo trials of a fibre Bragg grating based temperature profiling system

We describe the results of in-vivo trials of a portable fiber Bragg grating based temperature profile monitoring system. The probe incorporates five Bragg gratings along a single fiber and prevents the gratings from being strained. Illumination is provided by a superluminescent diode, and a miniature CCD based spectrometer is used for demultiplexing. The CCD signal is read into a portable computer through a small A/D interface; the computer then calculates the positions of the center wavelengths of the Bragg gratings, providing a resolution of 0.2 °C. Tests were carried out on rabbits undergoing hyperthermia treatment of the kidney and liver via inductive heating of metallic implants and comparison was made with a commercial Fluoroptic thermometry system.

Proactive environmental systems:the next generation of environmental monitoring

In this article we envision factors and trends that shape the next generation of environmental monitoring systems. One key factor in this respect is the combined effect of end-user needs and the general development of IT services and their availability. Currently, an environmental (monitoring) system is assumed to be reactive. It delivers measurement data and computational results only if the user explicitly asks for it either by query or subscription. There is a temptation to automate this by simply pushing data to end-users. This, however, leads easily to an "advertisement strategy", where data is pushed to end-users regardless of users' needs. Under this strategy, the mere amount of received data obfuscates the individual messages; any "automatic" service, regardless of its fitness, overruns a system that requires the user's initiative. The foreseeable problem is that, unless there is no overall management, each new environmental service is going to compete for end-users' attention and, thus, inadvertently hinder the use of existing services. As the main contribution we investigate the nature of proactive environmental systems, and how they should be designed to avoid the aforementioned problem. We also discuss how semantics, participatory sensing, uncertainty management, and situational awareness link to proactive environmental systems. We illustrate our proposals with some real-life examples.

Clinical evaluation of a novel test strip technology for blood glucose monitoring:accuracy at hypoglycaemic glucose levels

Aim: To evaluate OneTouch® Verio™ test strip performance at hypoglycaemic blood glucose (BG) levels (<3.9mmol/L [<70mg/dL]) at seven clinical studies. Methods: Trained clinical staff performed duplicate capillary BG monitoring system tests on 700 individuals with type 1 and type 2 diabetes using blood from a single fingerstick lancing. BG reference values were obtained using a YSI 2300 STAT™ Glucose Analyzer. The number and percentage of BG values within ±0.83. mmol/L (±15. mg/dL) and ±0.56. mmol/L (±10. mg/dL) were calculated at BG concentrations of <3.9. mmol/L (<70. mg/dL), <3.3. mmol/L (<60. mg/dL), and <2.8. mmol/L (<50. mg/dL). Results: At BG concentrations <3.9. mmol/L (<70. mg/dL), 674/674 (100%) of meter results were within ±0.83. mmol/L (±15. mg/dL) and 666/674 (98.8%) were within ±0.56. mmol/L (±10. mg/dL) of reference values. At BG concentrations <3.3. mmol/L (<60. mg/dL), and <2.8. mmol/L (<50. mg/dL), 358/358 (100%) and 270/270 (100%) were within ±0.56. mmol/L (±10. mg/dL) of reference values, respectively. Conclusion: In this analysis of data from seven independent studies, OneTouch Verio test strips provide highly accurate results at hypoglycaemic BG levels. © 2012 Elsevier Ireland Ltd.

Model of Active Structural Monitoring and Decision-making for Dynamic Identification of Buildings, Monuments and Engineering Facilities

Structural monitoring and dynamic identification of the manmade and natural hazard objects is under consideration. Math model of testing object by set of weak stationary dynamic actions is offered. The response of structures to the set of signals is under processing for getting important information about object condition in high frequency band. Making decision procedure into active monitoring system is discussed as well. As an example the monitoring outcome of pillar-type monument is given.

Structural Health Monitoring using Index Based Reasoning for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

Modelling of an efficient dynamic smart solar photovoltaic power grid system

A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.

The viability of a tool for fetal health monitoring

Health monitoring has become widespread these past few years. Such applications include from exercise, food intake and weight watching, to specific scenarios like monitoring people who suffer from chronic diseases. More and more we see the need to also monitor the health of new-born babies and even fetuses. Congenital Heart Defects (CHDs) are the main cause of deaths among babies and doctors do not know most of these defects. Hence, there is a need to study what causes these anomalies, and by monitoring the fetus daily there will be a better chance of identifying the defects in earlier stages. By analyzing the data collected, doctors can find patterns and come up with solutions, thus saving peoples’ lives. In many countries, the most common fetal monitor is the ultrasound and the use of it is regulated. In Sweden for normal pregnancies, there is only one ultrasound scan during the pregnancy period. There is no great evidence that ultrasound can harm the fetus, but many doctors suggest to use it as little as possible. Therefore, there is a demand for a new non-ultrasound device that can be as accurate, or even better, on detecting the FHR and not harming the baby. The problems that are discussed in this thesis include how can accurate fetus health be monitored non-invasively at home and how could a fetus health monitoring system for home use be designed. The first part of the research investigates different technologies that are currently being used on fetal monitoring, and techniques and parameters to monitor the fetus. The second part is a qualitative study held in Sweden between April and May 2016. The data for the qualitative study was collected through interviews with 21 people, 10 mothers/mothers-to-be and 11 obstetricians/gynecologists/midwives. The questions were related to the Swedish pregnancy protocol, the use of technology in medicine and in particular during the pregnancy process, and the use of an ECG based monitoring device. The results show that there is still room for improvements on the algorithms to extract the fetal ECG and the survey was very helpful in understanding the need for a fetal home monitor. Parents are open to new technologies especially if it doesn't affect the baby's growth. Doctors are open to use ECG as a great alternative to ultrasound; on the other hand, midwives are happy with the current system. The remote monitoring feature is very desirable to everyone, if such system will be used in the future.

Novel efficient technologies in Europe for axle bearing condition monitoring – the MAXBE project

Axle bearing damage with possible catastrophic failures can cause severe disruptions or even dangerous derailments, potentially causing loss of human life and leading to significant costs for railway infrastructure managers and rolling stock operators. Consequently the axle bearing damage process has safety and economic implications on the exploitation of railways systems. Therefore it has been the object of intense attention by railway authorities as proved by the selection of this topic by the European Commission in calls for research proposals. The MAXBE Project (http://www.maxbeproject.eu/), an EU-funded project, appears in this context and its main goal is to develop and to demonstrate innovative and efficient technologies which can be used for the onboard and wayside condition monitoring of axle bearings. The MAXBE (interoperable monitoring, diagnosis and maintenance strategies for axle bearings) project focuses on detecting axle bearing failure modes at an early stage by combining new and existing monitoring techniques and on characterizing the axle bearing degradation process. The consortium for the MAXBE project comprises 18 partners from 8 member states, representing operators, railway administrations, axle bearing manufactures, key players in the railway community and experts in the field of monitoring, maintenance and rolling stock. The University of Porto is coordinating this research project that kicked-off in November 2012 and it is completed on October 2015. Both on-board and wayside systems are explored in the project since there is a need for defining the requirement for the onboard equipment and the range of working temperatures of the axle bearing for the wayside systems. The developed monitoring systems consider strain gauges, high frequency accelerometers, temperature sensors and acoustic emission. To get a robust technology to support the decision making of the responsible stakeholders synchronized measurements from onboard and wayside monitoring systems are integrated into a platform. Also extensive laboratory tests were performed to correlate the in situ measurements to the status of the axle bearing life. With the MAXBE project concept it will be possible: to contribute to detect at an early stage axle bearing failures; to create conditions for the operational and technical integration of axle bearing monitoring and maintenance in different European railway networks; to contribute to the standardization of the requirements for the axle bearing monitoring, diagnosis and maintenance. Demonstration of the developed condition monitoring systems was performed in Portugal in the Northern Railway Line with freight and passenger traffic with a maximum speed of 220 km/h, in Belgium in a tram line and in the UK. Still within the project, a tool for optimal maintenance scheduling and a smart diagnostic tool were developed. This paper presents a synthesis of the most relevant results attained in the project. The successful of the project and the developed solutions have positive impact on the reliability, availability, maintainability and safety of rolling stock and infrastructure with main focus on the axle bearing health.

Computer-based monitoring platform for renewable energy systems: Four experimental application cases using NI LabVIEW

Sustainability and responsible environmental behaviour constitute a vital premise in the development of the humankind. In fact, during last decades, the global energetic scenario is evolving towards a scheme with increasing relevance of Renewable Energy Sources (RES) like photovoltaic, wind, biomass and hydrogen. Furthermore, hydrogen is an energy carrier which constitutes a mean for long-term energy storage. The integration of hydrogen with local RES contributes to distributed power generation and early introduction of hydrogen economy. Intermittent nature of many of RES, for instance solar and wind sources, impose the development of a management and control strategy to overcome this drawback. This strategy is responsible of providing a reliable, stable and efficient operation of the system. To implement such strategy, a monitoring system is required.The present paper aims to contribute to experimentally validate LabVIEW as valuable tool to develop monitoring platforms in the field of RES-based facilities. To this aim, a set of real systems successfully monitored is exposed.