Distant Monitoring Research Articles

Prognostic Value of Inflammation Biomarkers in Penile Squamous Cell Carcinoma Patients Without Distant Metastasis.

To investigate the value of the presurgical inflammatory biomarkers including C-reactive protein (CRP), albumin (ALB), C-reactive protein to albumin ratio (CAR), Glasgow prognostic score (GPS), the modified GPS (mGPS), and the high-sensitivity modified GPS (Hs-mGPS) in penile squamous cell carcinoma (PSCC) without distant metastasis and develop a tool to predict the overall survival (OS) of PSCC patients. We retrospectively enrolled 271 PSCC patients without distant metastasis from 2006 to 2021. Patients were divided into 2 cohorts by a 7:3 ratio-a training cohort (n=191) and a validation cohort (n=80). We performed cox regression analyses on the training cohort and constructed a nomogram to predict OS over 1, 3, and 5 years. Data from the validation cohort was used to validate the nomogram's predictive power. According to Kaplan-Meier analysis, elevated CRP (P < .001), hypoalbuminemia (P=.008), higher CAR (P < .001), higher GPS score (P < .001), higher mGPS score (P < .001), and higher Hs-mGPS score (P=.015) were associated with a decreased overall survival. GPS score, along with age, pathology N stage, and grade, was found to be an independent risk factor for poor prognosis in the multivariate analysis. We constructed a nomogram based on the prespecified variables predicting 1-, 3- and 5-year OS. The C-indexes of the nomogram in the training and validation cohorts were 0.871 and 0.869, respectively. The decision curve analysis showed that the nomogram had a larger net benefit. The Kaplan-Meier curves showed significant differences between the risk groups categorized according to the nomogram (P < .001). Inflammation biomarkers of systemic inflammation and nutritional status play an important role in individual OS predictions for PSCC patients without distant monitoring. The establishment of the nomogram provided a tool to predict the survival of 1-, 3-, and 5-year OS in PSCC patients without distant metastasis.

Analysis and Implementation of 5G-IoT based Smart Residential Buildings using Cisco Packet Tracer 8.1

Integration of IoT and 5G enables us to fulfil today’s need to create smart residential buildings to enhance life quality and safety in various aspects. This paper proposes the design and implementation of a 5G IoT based Smart Residential Building using the most recent version of CISCO Packet Tracer (a simulation software). Different smart IoE devices were used for automation which allow distant monitoring and controlling. Since these buildings are vulnerable to cyber-attacks and security threats, this paper also analyzes the proposed security framework and how such an implementation on using various sensors and actuators enables us to enhance the security and safety. In addition to this, we also outline the measures to be taken by the government and building owners to strengthen the security. The simulation results show that integrating 5G and IoT is a promising and cost-effective if it gets implemented practically in the real world.

Perceptions of Indonesian Nurses Toward the Application of the Internet of Things in the Future

In the healthcare industry, Internet of Things (IoT) based systems are utilized for phone care delivery, smart healthcare, smart health sensors and wearable technology, preventative systems, and distant monitoring. No studies have assessed nurses’ perspectives of IoT applications in Indonesia. The purpose of this study was to identify health professionals’ perspectives on future health and technology trends, to identify their readiness to adopt new health technologies, and to identify the use of IoT technology in healthcare applications. This study was conducted using a descriptive and cross-sectional approach. Nurses with a Diploma III and at least one year of experience were selected from three different departments (medical surgical, pediatrics, maternity). About 76% of 350 nurses had little knowledge of IoT technology and 95% said they do not keep up to date with IoT publications. About 50% of nurses believed that IoT technology will have a large impact on the health and education sectors. These results indicated that IoT technology and informatics should be included in nursing education and further studies should be conducted to integrate technological trends into healthcare and nursing practices.&#x0D; Keywords: perceptions, nurses, internet of things, healthcare

Имплантируемые кардиовертеры-дефибрилляторы в профилактике внезапной сердечной смерти: технические аспекты и дальнейшие перспективы применения. Что нужно знать практикующему врачу?

Currently, the prevention of sudden cardiac death (SCD) is an urgent issue as never, i.e., more than a half of patients with cardiovascular disorders die suddenly, one third of patients are young and middle-aged adults. The primary preventive strategy of SCD is an implantable cardioverter defibrillator (ICD) due to the lack of highly effective and, more important, safe antiarrhythmics. Forty years after the first ICD insertion, SCD is still the cause of more than 5 million of deaths annually worldwide. Therefore, a real need for ICD is significantly higher than the number of insertions. Meanwhile, primary physicians are not aware of this preventive tool. This paper reviews current approaches to ICD use for the primary and secondary prevention of SCD, types of ICDs, selection of electrode insertion sites, relevant aspects of ICD programming to detect and addresses arrhythmias by antitachycardial pacing or shock discharge, standards for outpatient follow-up after ICD insertion, distant monitoring and telemetry, and future perspectives of ICD insertion. KEYWORDS: sudden cardiac death, implantable cardioverter defibrillator, distant monitoring, perspectives. FOR CITATION: Talibullin I.V., Lebedeva N.B., Parfenov P.G., Mamchur S.E. Implantable cardioverter defibrillators for the prevention of sudden cardiac death: technical aspects and future perspectives. What a practitioner needs to know? Russian Medical Inquiry. 2022;6(1):21– 25 (in Russ.). DOI: 10.32364/2587-6821-2022-6-1-21-25.

Strategic perspectives of the oil and gas sector industrial development

The authors study oil and gas industry, its condition and perspective trends of industrial development. One of them involves applying low carbon and low cost technologies. The authors introduce new strategic imperatives in oil and gas sector to perform energy transition. They study the types of categories of perspective trends of the industry’s development: scaling up the development and implementation of a carbon capture and storage system, using low carbon raw materials, making it possible to take granular measurements. The article deals with perspectives of the oil and gas industry for the current year. The perspectives are built with the consideration of the previous year’s indicators and include all the past disasters and the dynamics of their solution and the results for the society. The authors show wider implementation of drones used for abnormal emissions of hydrogen sulfide to carry out distant monitoring, observations, inspections and preventive maintenance, change tracking, methane management, emergency response and material processing. The article describes precision drilling which reduces the risk of accidents, oil spills, fires and increases rate of penetration. The authors present microwave hydraulic fracturing which can become the next significant achievement in the perspective development of the industry.

STUDY OF TRITIUM MIGRATION AND RETENTION MECHANISMS IN THE GEOLOGICAL ENVIRONMENT (BY THE EXAMPLE OF THE KYIV RADIOACTIVE WASTE STORAGE FACILITY)

Radioactive waste storage facilities (RWSF) are a potential source of tritium in the biosphere. Engineered concrete constructions are not sufficiently reliable forasmuch as water leaks contaminated with tritium from the storage facilities into the geological environment has been detected. The barrier properties of the natural environment at the storage sites are determined by the ability to absorb and retain heavy isotopes of hydrogen during a considerable period of time and thus exclude its circulation in the biosphere. Various elements of the natural ecosystem take part in the absorption of tritium – the geological environment, soil organic matter, annual and perennial vegetation, micro- and macrobiota. A certain part of tritium in the gaseous and aerosol form is released into the air. The highest concentrations of tritium are recorded in the area close to the concrete radioactive waste (RW) storage facilities, where the vapor-gas emanation plume is least dispersed. With distance from the storage facilities, the tritium concentration in the soil humus layer significantly decreases due to the spatial dispersion of the tritium in the atmospheric plume. Tritium from the air enters the soil with the atmospheric precipitation and is partially retained in the humified layer of the soil. Most of the tritium from the atmospheric precipitation is transported by the vertical infiltration flow through the sedimentary layers represented by loess sandy loams and loams, where it is finally retained. In the area close to RWSFs, the concentration of heavy hydrogen isotope in pore, interstitial and film water (1 fraction) is up to 87 % of its total content in an elementary block. In the more tightly bound forms (2 and 3 fractions), it is 9 % and 4 %, respectively. Farther from the RW storage facilities in the predominant air flow direction, the tritium concentration in free water decreases to 75 %. In this area, more intensive redistribution of tritium between the structural sites is observed. At the more distant monitoring points (wells), from 25 % to 37 % of the total tritium amount in the soils is retained in more tightly bound forms in the structure of rock-forming, mainly clay minerals

Экономические аспекты телемедицины

Introduction. For the recent years telemedicine (TM) has been actively integrated into daily life, and its growth was especially significant during COVID-19 pandemic. However, its economic component has its own specificities depending on the health financing system. The aim of this article is to analyze reasons of economical inefficiency of TM technologies in different health financing systems and to determine its further development path in economic terms. Results. It’s not justified to expect cost reduction of health care after integrating TM technologies into medical practice. In private health-care system TM technologies in the form of TM consultation aren’t cost-effective for beneficiaries. Representatives of private clinics use TM as a part of lead generation. From private clinics’ point of view, it’s cost-effective to use distant monitoring technologies integrated into programs of patients’ management. It’s economically appropriate to apply all varieties of TM including TM consultation on the voluntary health insurance (VHC) system. However, due to the low prevalence of VHC in Russia we can’t expect significant growth of TM in Russia based on using this sector. Conclusions. TM technologies require financing in its formative stage, implementation, development and further functioning phases.

Prolonged Effects of the COVID-19 Pandemic on Sleep Medicine Services-Longitudinal Data from the Swedish Sleep Apnea Registry.

The worldwide COVID-19 pandemic has affected the operation of health care systems. The direct impact of obstructive sleep apnea (OSA) on COVID-19 infection outcome remains to be elucidated. However, the coincidence of common risk factors for OSA and severe COVID-19 suggests that patients with OSA receiving positive airway pressure therapy may have an advantage relative to those untreated when confronted with a COVID-19 infection. The ongoing COVID-19 pandemic has led to a substantial reduction of sleep medicine services, and the long-term consequences may be considerable. New strategies for the management of sleep disorders are needed to overcome the current underdiagnosis and delay of treatment.

Vegetative indices dynamics modeling based on multispectral distant monitoring data analysis

The article deals with the problems of monitoring the dynamics of vegetation indices on the basis of multispectral data obtained using technical means of remote monitoring. The effectiveness and validity of the application of vegetation indices was proved by comparing the values of plant indices with reference measurements at test sites of various types of plantings. A review of foreign sources and the results of statistical analysis allowed us to conclude that there is a non-linear relationship between productivity indices and crop yields.

High spatial resolution IoT based air PM measurement system

Air pollution is one of the global problems of the current era. According to World Health Organization more than 80% of the people living in metropolitan areas breathe air which exceeds the guideline limits. Particulate matter, the mixture of liquid and solid particles having diameters less than 10 μm, is one of the important pollutants in the air. The main source of the Particulate matter is mostly burning reactions associated with industry, vehicles and homes. Several studies have shown the lethal impact of particulate matter to public health and environment. The rise of particulate matter amount in air has been linked to several health problems such as not only respiratory diseases but also mortality in infants and heart attacks. Currently, bulky stations which are high-cost and have limited spatial resolution are used to monitor the air quality. In this study we developed an alternative particulate matter measurement system which is portable and low-cost (less than 200 USD) and also integrated with cloud computing. The system allows real time distant monitoring of PM particles with high spatial resolution (meter range). The developed sensor system is able to provide air quality data in correlation with the existing stations (R2 = 0.87). The statistical comparison between the developed system and the reference methods revealed that two systems produced statistically equal results in detecting the variations of the particulate matter.

Cognitive intelligence in fog computing-inspired veterinary healthcare

A comprehensive smart home-based health monitoring framework for veterinary is proposed in this research. It focuses on the distant monitoring of the health condition of domestic animals within the home environment by utilizing Internet of Medical Things (IoMT) technology. Fog computing is used to formulate a time-based data accumulation and the corresponding Health Severity Index (HSI) is established for determining the animal’s health severity. Also, Time Sensitivity Parameter (TSP) is specified for time-sensitive veterinary healthcare, for which Self Organized Mapping (SOM) is incorporated. Furthermore, Recurrent Neural Network (RNN) model is utilized to provide predictive healthcare services in a time-sensitive manner. The system is implemented over several challenging datasets for validation purposes. Based on the results, the presented framework can acquire a high measure of Precision (94.60%), Accuracy (94.71%), Sensitivity (94.55%), and F-measure (93.48%).

Причины прогрессирования глаукомы во время пандемии COVID-19

The novel coronavirus infection (COVID-19) provides powerful effects on all pathogenic aspects of the primary open-angle glaucoma (POAG). The property of this virus to initiate disseminated intravascular coagulation, damage endotheliocytes, and impair coagulation result in numerous severe complications affecting all organs and systems. This disorder provokes retinal ischemia and hypoxia and spurs apoptosis of ganglionic cells. Cytokine storm and oxidative stress resulting from the COVID-19 potentially contribute to the progression of glaucomatous optic neuropathy. Distressing effect of the pandemic, a growing number of patients with depressive and anxiety disorders increase the risk of POAG and ocular hypertension, reduce treatment compliance, and exacerbate glaucoma course. Ophthalmic patients should be informed on potential risks and consequences of the COVID-19 and educated on the safety and efficacy of vaccination and the need for these preventive measures for elderly patients (in particular, with glaucoma). A year of the COVID-19 pandemic has radically changed the attitude to many processes of doctor-patient relationships. There is a need for the development of the technologies of distant monitoring of patients with glaucoma. Keywords: primary open-angle glaucoma, COVID-19, telemedicine, pandemic, SARS-CoV-2, cytokine storm, oxidative stress, intraocular pressure, apoptosis of ganglionic cells, glaucomatous optic neuropathy, post-COVID-19 syndrome. For citation: Korelina V.E., Gazizova I.R., Kuroyedov A.V., Didur M.D. Glaucoma progression during the COVID-19 pandemics. Russian Journal of Clinical Ophthalmology. 2021;21(3):147–152 (in Russ.). DOI: 10.32364/2311-7729-2021-21-3-147-152.

Design and Development of Wearable Remote Temperature Monitoring Device for Smart Tracking of COVID-19 Fever

Covid19 has emerged out as a pandemic spreading over a total of 235 countries affecting millions of lives has put global healthcare scenarios in front of multiple new challenges. Due to its highly contagious nature scientists have to counteract with new noncontact distant monitoring techniques in clinical infrastructure using modern web and server-based communications. It is quite possible to monitor and track an individual’s health with the help of the Internet of Things (IoT). A practical approach of the design is proposed and developed for a remote temperature monitoring device which is experimentally proven to perform with 98% accuracy. A buzzer is integrated with the device for alarming when the temperature level crosses a set threshold temperature (100.4 °F). Due to the small integrated design, it is comfortably wearable for individuals and can be implemented in our daily lives amid the current covid19 pandemic.

INTERNET OF THINGS IMPLICATIONS FOR THE ADEQUATE DEVELOPMENT OF THE SMART AGRICULTURAL FARMING CONCEPTS

It is essential to increase the productivity of agricultural and farming processes to improve yields and cost-effectiveness with innovated technologies such as the Internet of Things (IoT). In particular, IoT can make agricultural and farming industry processes more efficient through automation by reducing human intervention. The aim of this research paper is to prescribe recently developed IoT applications in the agriculture and farming industries to provide an overview of sensor data collections, technologies like embedded electronics, and sub-verticals such as water management and crop management. This article highlights the potential of wireless sensors and IoT in agriculture, as well as the challenges expected to be faced when integrating this technology with the traditional farming practices. This paper includes the description of systems with the electronic circuitry of the systems, used network protocols and smart distant monitoring systems for PCs and Smartphones, etc. Later it includes some propositions and finally, the paper concludes with describing the future scopes of relevant technologies in smart farming.

Distant mood monitoring for depressive and bipolar disorders: a systematic review

BackgroundBroadening our knowledge of the longitudinal course of mood symptoms is cardinal to providing effective long-term treatments. Research indicates that patients with mental illness are willing to engage in the use of telemonitoring and mobile technology to assess and monitor their mood states. However, without the provision of distant support, adverse outcomes and events may be difficult to prevent and manage through self-monitoring. Understanding patient perspectives is important to achieving the best balance of self-monitoring, patient empowerment, and distant supporter involvement.MethodsThis systematic review synthesises quantitative and qualitative evidence of the effectiveness and feasibility of daily/weekly/monthly remote mood monitoring that includes distant support in participants with mood disorders. Inclusion criteria comprised mood monitoring of mood disorder patients as main intervention, study design, method of monitoring, and presence of psychotherapy and psychoeducation. Effectiveness was defined by the change in depression and/or mania scores. Feasibility was determined on participant feedback and completion/attrition rates. Studies were assessed for quality using the Mixed Methods Appraisal Tool version 2018.ResultsNine studies of acceptable quality met the inclusion criteria. Distant mood monitoring was effective in improving depression scores but not mania scores. Feasibility, as measured through compliance and completion rates and participant feedback, varied.ConclusionDistant mood monitoring with support may be a useful, acceptable, and feasible intervention for diverse groups of patients in terms of age and ethnicity. Further, it may be effective in improving symptoms of depression, increasing treatment adherence, and facilitating the prevention and management of adverse outcomes. As a task-shifting intervention, distant mood monitoring may help to alleviate the burden on mental health providers in developing countries.

Implication of Radon Monitoring for Earthquake Surveillance Using Statistical Techniques: A Case Study of Wenchuan Earthquake

The seismotectonically induced changes in groundwater radon (Rn) are considered to be strong imputes for the surveillance of imminent major earthquakes. Groundwater facilitates the migration of soil gases as a result of tectonic stresses. In this regard, a radon time series is statistically analysed to identify the radon anomalies possibly induced by Wenchuan earthquake. The statistical analysis mainly involves the deterministic analysis of the Rn data and residual Rn analysis using a criterion x¯±2σ of anomaly selection having a confidence interval of 95%. The deterministic analysis reveals that the Rn time series follows a persistent trend 0.5≤H≤1 which confirms the absence of a chaotic regime. On the other hand, the residual Rn shows a notable upsurge straddling the time of the Wenchuan earthquake in the form of pre- and post earthquake changes at monitoring stations having RE/RD≤0.3. The residual Rn level passes the anomaly selection criterion x¯±2σ and is declared as a tectonically induced Rn anomaly. Contrary to this, the response of distant monitoring stations (RE/RD&gt;0.3) to this particular earthquake further validates the link between Rn and earthquake activity. In a nutshell, the present study highlights the potential implications of earthquake-induced radon anomalies for earthquake prediction research.

Smart solar photovoltaic panel cleaning system

With the increasing demand for renewable energy, solar photovoltaic technology is being a topic of concern. However, due to the accumulation of dust and dirt over the panel surface, the performance of the photovoltaic system degrades to a noticeable number. To address this issue: a fully automated, cost worthy and efficient system needs to be invented. This paper presents the design and fabrication process of a prototype able to clean the panel surface. The prototype of this system comprises of a cleaning robot and a cloud interface: the cleaning robot is mobile and able to clean the entire solar array back and forth, with its separately driven cleaning rotatory brush; whereas, the cloud interface is a human-machine interface featuring the distant monitoring and control of the robot. Additionally, to notify the performance of distantly placed solar farm, a sensing unit consisting of sensors was added to this system. Furthermore, to add an automatic cleaning feature, a month-long data of totally clean and dusty panel was processed with regression analysis, and the developed regression model was programmed into the sensing unit. The sensing unit added with the regression model is named as an autonomous unit, as it predicts the suitable time for cleaning action. According to the system evaluation done on a demonstration PV module, it was found that the designed system can clean dry dust accumulated over the panel’s surface. Moreover, by attaching the metal rail tracks on a long solar array, the system seems to be implementable on a large scale solar farm.

Solid-organ transplant surgeries in era of COVID-19 pandemic: How to go about it?

Solid-organ transplant surgeries in era of COVID-19 pandemic: How to go about it?

Smart Helmet: Thresh-Learner–Online Machine Learning on Data Streams

Today, with an enormous generation and availability of time series data and streaming data, there is an increasing need for an automatic analyzing architecture to get fast interpretations and results. One of the significant potentiality of streaming analytics is to train and model each stream with unsupervised Machine Learning (ML) algorithms to detect anomalous behaviors, fuzzy patterns, and accidents in real-time. If executed reliably, each anomaly detection can be highly valuable for the application. In this paper, we propose a dynamic threshold setting system denoted as Thresh-Learner, mainly for the Internet of Things (IoT) applications that require anomaly detection. The proposed model enables a wide range of real-life applications where there is a necessity to set up a dynamic threshold over the streaming data to avoid anomalies, accidents or sending alerts to distant monitoring stations.We took the major problem of anomalies and accidents in coal mines due to coal fires and explosions. This results in loss of life due to the lack of automated alarming systems. We propose Thresh-Learner, a general purpose implementation for setting dynamic thresholds. We illustrate it through the Smart Helmet for coal mine workers which seamlessly integrates monitoring, analyzing and dynamic thresholds using IoT and analysis on the cloud.

IoT Based Self-Cleaning and Automated Fault Detection of Solar Panel System

Solar photovoltaic panel tends to lose its performance, when foreign particles start accumulating over it. To get panel at its best, frequent cleaning action is required by some means. It would be beyond imagination, if there comes a task to clean entire solar farm covering miles squares and more, hence a better solution is required. Solar photovoltaic panel cleaning system is a robotic system designed to clean solar panel surface; in order to sustain the efficiency. To avoid frequent site visits, robots can be placed in each array, and by further deploying Internet of Things (IoTs), distant monitoring and cleaning can be achieved. The command for the robots can be given by distant operator through the cloud they are connected with. To make this system even smarter, a separate sensing unit shall be installed along with different sensors that can detect the limit of dust deposition and shall automatically order to perform cleaning action. This study presents the need of cleaning system, which is followed by design and fabrication of robot that meets the design specification and required performance. A month-long data is collected and analyzed to formulate and validate the automatic cleaning algorithm in real environment. From this study, it is concluded that, the IoT can be implemented in the solar PV cleaning system which can improve the system performance significantly.