Remote Monitoring System Research Articles

Acoustic Monitoring Efficiently Identifies Pipeline Leaks

A Pennsylvania water utility was facing nonrevenue water loss of 20%. By implementing a remote acoustic monitoring system, the utility significantly decreased water loss, reduced costs and employee overtime, and improved customer service.

INFORMATION SYSTEM OF STREET LIGHTING CONTROL IN A SMART CITY

Context. In the context of the rapid development of technologies and the implementation of the concept of smart cities, smart lighting becomes a key element of a sustainable and efficient urban environment. The research covers the analysis of aspects of the use of sensors, intelligent lighting control systems with the help of modern information technologies, in particular such as the Internet of Things. The use of such technologies makes it possible to automate the regulation of lighting intensity depending on external conditions, the movement of people or the time of a day. This contributes to the efficient use of electricity and the reduction of emissions into the atmosphere. Objective. The purpose of the paper is to analyze the procedures for creating an information system as a tool for monitoring and evaluating the level of illumination in a smart city with the aim of improving energy efficiency, safety, comfort and effective lighting management. The implementation of a smart lighting system for Lviv will help improve energy efficiency and community safety. Method. A content analysis of scientific publications was carried out, in which the results of research on the creation of street lighting monitoring systems in real urban environments were presented. The collection and analysis of data on street lighting in the city, such as energy consumption, illumination level, lamp operation schedules, and others, was carried out. Machine learning methods were used to analyze data and predict lighting needs. Using the UML methodology, the conceptual model of the street lighting monitoring information system was developed based on the identified needs and requirements. Results. The role of data processing technologies in creating effective lighting management strategies for optimal use of resources and meeting the needs of citizens is highlighted. The study draws attention to the challenges and opportunities of implementing smart lighting in cities, maximizing the positive impact of smart lighting on modern urban environments. The peculiarities of the development and use of an information system for controlling street lighting in a smart city are analyzed. The potential advantages and limitations of using the developed system are determined. Conclusions. The project on the creation of an information system designed to provide an energy-efficient lighting system in a smart city will contribute to increasing security, particularly, ensuring the safety of the community through integration with security systems, reducing energy consumption, through minimizing the electricity usage in periods when the need for lighting is not necessary. It has been determined that to implement an information system for remote monitoring and lighting control in a smart city, it is advisable to consider the possibility of using a complex lighting control system. Calculations were made on the example of Lviv for the city’s lighting needs. The use of motion sensors to determine the need to turn on lighting was analyzed. A conceptual model of the information system was developed using the object-oriented methodology of the UML notation. The main functionality of the information system is defined.

Optimization Analysis of Tennis Player Training Mode Based on 3D Simulation Model

This paper is based on 3D simulation technology and deeply analyzes the optimization strategy of tennis player training mode. The research focuses on two core systems: one is a remote motion monitoring system based on architecture, which captures and analyzes athletes’ motion data in real time, providing coaches with accurate motion feedback and training effectiveness evaluation; The second is a 3D-based safety monitoring system, which uses 3D simulation technology to simulate the training environment, monitor and warn potential safety risks in real time, and ensure the safety of athletes during training. These two systems are designed for different demand scenarios in tennis training, with complementary functions, and together constitute an intelligent solution for optimizing the training mode of tennis players. By continuously improving algorithms, optimizing data storage and computation methods, and improving the accuracy of data analysis and mapping, this study aims to enhance the scientific, efficient, and safe training of tennis players, providing strong support for the comprehensive improvement of their skills and physical fitness.

IoT Leak Detection System for Onshore Oil Pipeline Based on Thermography.

The vast expanses of remote onshore areas in oil-producing countries are home to a network of flow and collection pipelines that are susceptible to leaks. Most of these areas lack the infrastructure to enable the use of remote monitoring systems equipped with sensors and real-time data analysis to provide early detection of anomalies. This paper proposes a proof of concept for a monitoring system based on the Internet of Things (IoT) for real-time detection of pipeline leaks in onshore oil production fields. The proposed system, based on a thermal imaging leak detection method, informs the operator of the system's operating status via a web page. The leak detection system communicates via a Zigbee network between the IoT devices and a 4G mobile network. The results of the tests carried out show that a visual and automatic IoT-based leak detection system is possible and plausible. The proposed leak detection system enables supervisors at remote stations and field workers to monitor the operating status of pipelines via computers, tablets, or smartphones, regardless of where they are.

Indoor Air Quality System: A Design of Monitoring CO and CO2 Substances for Elderly Home Using IoT

The use of an IoT-based monitoring system for CO and CO2 gases in elderly homes is a necessary innovation for remotely monitoring air quality. This work was successful in establishing a remote monitoring system that can measure CO and CO2 gases utilizing IoT technology combined with Blynk software. The MQ-7 sensors detect CO gas, while the MQ-135 sensors detect CO2. Data from these sensors is delivered to a central server, which then sends it to the I2C 16X2 LCD panel and Blynk software, allowing data visualization via an internet connection. The study's findings indicate that this system can detect and monitor CO and CO2 gas levels with a high degree of precision. This device can also monitor air quality in real time using the Blynk software. As a result, users may accurately monitor air quality (CO and CO2 gases) in elderly homes.

Remote management of worsening heart failure events and subsequent rate of emergency department admission

Abstract Background Worsening heart failure (WHF) is the leading cause of hospitalization among individuals aged ≥ 65 years and constitutes a substantial burden for both the patient and the healthcare systems. Moreover, heart failure contributes to exacerbate the pressure on emergency departments which are involved in 64% of heart failure hospital admission (1). Remote management of heart failure as been shown to reduce the number of days lost due to unplanned cardiovascular hospitalizations and all-cause mortality (2, 3), but little is known about the effect on the emergency healthcare use. We aimed to describe the effect of a telemonitoring program on the rate of emergency admissions for WHF in chronic heart failure patients. Methods All patients enrolled in the heart failure remote management program of two French centers between 13 April 2020 and 31 January 2023 were included in the study. Follow-up data were collected until 31 January 2023. Inclusion criteria were chronic heart failure (HF) with New York Heart Association ≥II and an elevated B-type natriuretic peptide (BNP > 100 pg/mL or N-terminal-pro-BNP > 1000 pg/mL). Remote evaluation included measurements of body weight, blood pressure, heart rate, symptoms, biochemical parameters, and data from cardiac implantable electronic devices when available. Results A total of 1,095 patients (72±11.8 years old, 69.7% male), were followed for a median [IQR] of 437 [182; 739] days with a mean adherence to the remote monitoring system of 67.6±30.3%. Over this period, 198 (18.1%) patients had 949 WHF events, the majority of whom were remotely detected: 830 (87.5%). Overall, 246 (26%) of the WHF episodes required hospitalisation and 109 (11%) prompted an emergency department visit. When the WHF event was remotely detected, hospitalization was only required in 127 (15%) cases and the rate of emergency department visit was reduced to 3%. Conclusion In HF patients engaged in a multiparametric remote management program, the rate of emergency department admission is very low. Adopting such a strategy for patients with chronic HF may be useful in reducing emergency department overcrowding.Baseline characteristics of patientsPatients course and use of resources

Digital literacy of patients with chronic heart failure using telemedicine in france: a national observational cohort study

Abstract Introduction Remote patient monitoring (RPM) is increasingly considered for chronic care management. However, several challenges exist for its implementation such as funding resources, lack of standardizations and gaps in digital literacy. Objective The aim of this study was to describe patients using RPM to manage chronic heart failure (CHF) according to their digital literacy at a national scale in France. Methods A national retrospective study was conducted using a remote monitoring system for the management and therapeutic guidance of patients with CHF. Patients were categorized according to their digital literacy (digitally literate vs poor digital literacy). The latter were identified as requiring nurse assistance in medical data entry. Data collection included baseline characteristics, comorbidities, RPM status, heart failure-related hospitalizations and mortality. Results Of the 12,072 patients with CHF enrolled for RPM follow-ups (male: 65.4%, mean age: 74.2±13.1 years), 43.3% had poor digital literacy. These patients were older (79.4±10.2 vs 70.2±13.6 years) and were less among males (39.7% vs 60.3%). Overall, digitally literate patients had more comorbidities, including diabetes (61.8%) and obesity (69.4%). Over a third of all patients withdrew from RPM (37.0%). Continued use of RPM was higher in digitally literate patients (60.1% vs 39.9%, p<0.001). Mortality was higher in patients with poor digital literacy (OR: 0.71, 95%CI: 0.66 to 0.78, p<0.0001). Poor digital literacy was linked to increased occurrences of HF episodes in contrast to digitally literate patients (34.1% vs 25.8%) who had an uHR of 0.66 (95%CI: 0.62 to 0.71, p<0.0001), and an aHR of 0.68 (95%CI: 0.64 to 0.73, p<0.0001). Conclusion Patients with poor digital literacy form a sizable subgroup in heart failure management and may require specialized tools tailored to their needs. Prevalence of poor digital literacy may increase the risk of HF hospitalization and mortality and reduce RPM adherence.

IMPLEMENTATION OF INNOVATIVE INDUSTRY 4.0 TECHNOLOGIES FOR THE RECONSTRUCTION OF THE ENERGY SECTOR OF UKRAINE

Abstract. The article explores the implementation of innovative Industry 4.0 technologies in the energy sector of Ukraine. It investigates key issues in the energy sector, including the reduction of electricity production capacities due to destruction, capture, and damage to property, low levels of innovation activity in energy enterprises, high energy intensity of production, moral and physical aging of equipment, and a low influx of foreign direct investments into Ukraine's energy sphere. The majority of the analyzed period indicates a relatively low level of interest from foreign investors in the examined sector of the domestic economy. The study identifies the Industry 4.0 toolkit applicable for the restoration of damaged and modernization of outdated infrastructure, enhancing the efficiency of Ukraine's energy sector. It is noted that among the tools, special attention should be paid to monitoring and forecasting systems, the Internet of Things (IoT), big data, integrated digital platforms, smart financial technologies, smart meters, remote monitoring systems, and artificial intelligence. The author emphasizes the peculiarities of applying this toolkit to solve the diagnosed problems in the energy sector of Ukraine. It is noted that the use of Industry 4.0 tools, namely the Internet of Things and big data analytics, can significantly improve the monitoring and management of energy processes. The problem of low innovation activity of Ukrainian energy companies can be solved by creating integrated digital platforms and developing partnerships between companies to share innovations. The use of smart financial technologies can make Ukraine's energy sector more attractive to investors. The high level of electricity losses during generation and distribution can be addressed by introducing smart meters and remote monitoring systems.

Smart Building, Nuisance Electrical Failure, Remote Monitoring and Fault Recovery System

Smart Buildings are the fastest growing buildings compared to conventional buildings and are expected to grow at a rate of 8.3% for the next decay. The global commercial building automation market was valued at US$32.96 billion in 2020 and is expected to reach US76.49 billion by the year 2031. The implementation of technological advancement, demand for energy-efficient construction, low operational cost, and occupant comfortability have helped Smart Building to grow. However, Smart Buildings are still facing issues, from various sensor network diversity, clear definitions of Smart Buildings, and continuous smartness during full or partial electrical internal fault occurrence. This indicates the building is smart as long as a continuous power supply is present. Thus, this research study investigated Smart Building's drawbacks and designed a circuit to be a solution to one of the drawbacks to rectify the issues. The design provides full monitoring for real and nuisance failures and enables the performance of fault recovery procedures remotely. The circuit interfaces with the safety Residual Current Devices (RCD) and the wireless smart Wi-Fi-controlled socket outlets. Food industries, hotels, and restaurants could be the beneficiaries of this circuit. This is due to cold stores and fridges, which can lead to significant production loss/reduction when failure time increases.

Hydrogel Sensors in an IoT System for Self-Monitoring and Remote Monitoring of Massage Pressure.

The effectiveness of massage can be enhanced if the pressure applied can be monitored continuously. In this study, we described an Internet-of-Things (IoT) system based on hydrogel sensors, which allows for self-monitoring and remote monitoring of massage pressure. The piezoresistive hydrogel with the compressive energy loss coefficient of 15.7% was developed, which was attributed to the strong polarization of ammonium phosphate on water molecules, which was evidenced by nuclear magnetic resonance (NMR) transverse relaxation analyses and atomic force microscopy. Using this hydrogel as a pressure-sensing component, we assembled a wearable sensor capable of quantifying and transmitting massage pressure with insignificant energy dissipation. By integrating RGB LED arrays, the message pressure was indicated by the color states of the LEDs. Furthermore, the wearable sensors and LEDs were connected to a microcontroller (MCU) chip, an IoT chip, and a cloud server to form a sensing-controlled IoT system, enabling visible and remote monitoring of massage pressure.

Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 2: Implementation

The economic cost of repairing corrosion-affected reinforced concrete structures (RCSs) means that reliable and accurate assessment and early detection methods must be sought after. Conventional techniques, such as visual inspections, or measuring either cover layer resistivity or the corrosion potential, are methods that require accessibility and involve personnel having to travel to take in situ measurements. Monitoring by embedded sensors is a much more efficient approach that allows early detection by remote sensing. This work presents the implementation of a new measurement protocol regarding the existing monitoring system called INESSCOM (Integrated Sensor Network for Smart Corrosion Monitoring). Along with the corrosion intensity measurement in embedded sensors, it also proposes monitoring the double layer capacity of the sensors’ responses. It aims to determine, along with the rebars’ corrosion rate, the triggering agent of the corrosion process. This study was carried out using three reinforced concrete scaled columns that were exposed to different environments. The results demonstrate with this new protocol that the remote INESSCOM monitoring system can establish the corrosion rate and identify the precursor agent of corrosion (carbonation or chlorides), even when the recorded corrosion rates are similar.

Patient Experience and Feasibility of a Remote Monitoring System in Parkinson's Disease.

Remote monitoring systems have the potential to measure symptoms and treatment effects in people with Parkinson's disease (PwP) in the home environment. However, information about user experience and long-term compliance of such systems in a large group of PwP with relatively severe PD symptoms is lacking. The aim was to gain insight into user experience and long-term compliance of a smartwatch (to be worn 24/7) and an online dashboard to report falls and receive feedback of data. We analyzed the data of the "Bringing Parkinson Care Back Home" study, a 1-year observational cohort study in 200 PwP with a fall history. User experience, compliance, and reasons for noncompliance were described. Multiple Cox regression models were used to identify determinants of 1-year compliance. We included 200 PwP (mean age: 69 years, 37% women), of whom 116 (58%) completed the 1-year study. The main reasons for dropping out of the study were technical problems (61 of 118 reasons). Median wear time of the smartwatch was 17.5 h/day. The online dashboard was used by 77% of participants to report falls. Smartphone possession, shorter disease duration, more severe motor symptoms, and less-severe freezing and balance problems, but not age and gender, were associated with a higher likelihood of 1-year compliance. The 1-year compliance with this specific smartwatch was moderate, and the user experience was generally good, except battery life and data transfer. Future studies can build on these findings by incorporating a smartwatch that is less prone to technical issues.

Artificial intelligence in action: Improving breast disease management through surgical robotics and remote monitoring

ObjectivesThis article aims to discuss the transformative impact of artificial intelligence (AI) on the identification and management of breast diseases, with a specific focus on breast cancer. Materials and methodsHealthcare providers have integrated AI technologies such as surgical robots and remote monitoring systems to improve the accuracy and efficiency of breast disease diagnosis and treatment. ResultsSurgical robots equipped with AI algorithms provide real-time guidance to surgeons, analyze imaging data, and ensure precise procedures for better outcomes in breast cancer surgeries. AI-driven remote monitoring systems allow for close monitoring of patient health data, disease progression prediction, and personalized treatment recommendations. ConclusionsThe incorporation of AI technology into healthcare practices for breast diseases has revolutionized patient care delivery, enhancing outcomes, promoting patient engagement, and improving overall quality of care. These advancements offer personalized and tailored healthcare strategies that meet the unique needs of each patient, reshaping the healthcare industry.

Design of intelligent remote monitoring and diagnosis system for equipment

Design of intelligent remote monitoring and diagnosis system for equipment

Development and implementation of a digital remote symptom monitoring program (RESPONSe) to support patients undergoing IV chemotherapy at a community ambulatory cancer clinic in Richmond, BC, Canada.

406 Background: We identified delays in accessing symptom management during treatment as an existing care gap at the Richmond Cancer Clinic. Patient-reported outcome measures (PROMs) have been demonstrated to communication, quality of life, and reduce symptom burden and acute care utilization. The RESPONSe program was initiated to address this gap by implementing a digital remote symptom monitoring (RSM) system paired with a supporting Symptom Management Nurse (SMN). Methods: We designed a digital RSM system to collect PROMs at specific timepoints during the first 6 months of IV chemotherapy initiation, with automated triaging logic to flag symptoms of concern that would result in a phone call from the SMN. Routine surveys include baseline, health-checks on days 3 and 10 post-chemotherapy, and pre-doctor’s-appointment; with optional health checks available anytime. Through competitive procurement, SeamlessMD was selected as the technology partner. From Aug 2023 to Jan 2024, multiple design cycles with dry run testing were held to incorporate branching logic, COSTARS oncology symptom specific questionnaires, automatic triaging flags, immediate self—management tips and links to educational resources. Concurrent development of SMN clinical workflows included in-person patient enrolment, digital dashboard monitoring and integration with the clinical chart. Results: From Jan 22-Apr 30, 2024, 32 patients have been enrolled with 42% over the age of 70. 90% of patients completed the baseline survey, 79% of patients completed at least 1 post-treatment health check and 45% completed at least 1 pre-doctors’-appointment survey. An average of 22 library resources were accessed per patient. Through the system, 19 severe and 34 moderate symptoms were identified. The dashboard prompted 63 telephone calls from the SMN, with a further 28 follow-up calls required. Early 3-month patient experience surveys (n=8) indicate high satisfaction, with 100% of patients saying they would recommend the program to others undergoing treatment. 87.5% of patients felt the system was very helpful in communicating their issues to the clinical team, with 100% reporting very high/extreme satisfaction with the support provided by the SMN. Additionally, 67% of patients felt very satisfied with the RESPONSe program overall. Conclusions: The RESPONSe program demonstrates the potential of digital RSM systems in improving patient-centered care and assisting with symptom reporting and management. Initial results suggest high engagement and patient satisfaction, showing this is a feasible approach in community oncology settings. We will be reviewing acute care utilization to assess the impact of the RESPONSe program on emergency room visits and hospitalization.

Information Technology Support for Athlete Health Monitoring and Medical Diagnosis

The paper uses WSN to monitor athletes’ medical diagnosis information remotely. The aim is to strengthen the monitoring and management of athletes’ medical diagnosis data. The method of wireless sensor node and IPv6 routing based on IPv6 is proposed. The terminal-to-terminal network structure based on IP can carry long-distance transmission and share athlete medical diagnosis information. The monitoring system’s bottom structure design is realized using Contiki technology. At the same time, it also realizes the data acquisition and management in the monitoring system. The component interface is designed based on TinyOS. The design of the wireless client based on GPSR is completed based on GPSR. This paper uses the VanetMobiSim platform to complete a remote monitoring system’s software development and simulation test based on wireless medical diagnosis information. The results show that this system’s medical diagnosis information covers a wide range, and the information search efficiency is high.

Implementing a remote self-screening programme for atrial fibrillation using digital health technology among community-dwellers aged 75 years and older: a qualitative evaluation

ObjectiveTo examine the feasibility of implementing remote atrial fibrillation (AF) self-screening among older people supported by a remote central monitoring system.DesignProcess evaluation of the Mass AF randomised clinical trial (ACTRN12621000184875)...

Managing Patients With COVID-19 in Armenia Using a Remote Monitoring System: Descriptive Study.

The COVID-19 pandemic has imposed immense stress on global health care systems, especially in low- and middle-income countries (LMICs). Armenia, a middle-income country in the Caucasus region, contended with the pandemic and a concurrent war, resulting in significant demand on its already strained health care infrastructure. The COVID@home program was a multi-institution, international collaboration to address critical hospital bed shortages by implementing a home-based oxygen therapy and remote monitoring program. The objective of this study was to describe the program protocol and clinical outcomes of implementing an early discharge program in Armenia through a collaboration of partner institutions, which can inform the future implementation of COVID-19 remote home monitoring programs, particularly in LMICs or low-resource settings. Seven hospitals in Yerevan participated in the COVID@home program. A web app based on OpenMRS was developed to facilitate data capture and care coordination. Patients meeting eligibility criteria were enrolled during hospitalization and monitored daily while on oxygen at home. Program evaluation relied on data extraction from (1) eligibility and enrollment forms, (2) daily monitoring forms, and (3) discharge forms. Over 11 months, 439 patients were screened, and 221 patients were managed and discharged. Around 94% (n=208) of participants safely discontinued oxygen therapy at home, with a median home monitoring duration of 26 (IQR 15-45 days; mean 32.33, SD 25.29) days. Women (median 28.5, mean 35.25 days) had similar length of stay to men (median 26, mean 32.21 days; P=.75). Despite challenges in data collection and entry, the program demonstrated feasibility and safety, with a mortality rate below 1% and low re-admission rate. Opportunities for operational and data quality improvements were identified. This study contributes practical evidence on the implementation and outcomes of a remote monitoring program in Armenia, offering insights into managing patients with COVID-19 in resource-constrained settings. The COVID@home program's success provides a model for remote patient care, potentially alleviating strain on health care resources in LMICs. Policymakers can draw from these findings to inform the development of adaptable health care solutions during public health crises, emphasizing the need for innovative approaches in resource-limited environments.

МАТЕМАТИЧЕСКАЯ МОДЕЛЬ ПРОЦЕССА ДОСТАВКИ ТЕЛЕМЕТРИЧЕСКИХ СООБЩЕНИЙ В СИСТЕМЕ МЕДИЦИНСКОГО ИНТЕРНЕТА ВЕЩЕЙ

Currently, research and development are relevant aimed at increasing the efficiency of transmission of telemetry messages in wireless remote monitoring systems used by medical workers to provide timely assistance to patients under observation. The technical basis for transmitting such messages is provided by medical Internet of Things systems. The article is devoted to the development of a mathematical model of the process of delivering telemetric messages in such a system. In the course of the study, analytical expressions were obtained that make it possible to estimate the average delivery time of messages from the patient’s sensory device to the healthcare worker’s wireless device, depending on the response intervals of the retransmission timers installed in the transmitting and receiving elements of the system. The results obtained allow us to theoretically substantiate the choice of retransmission timeout values that ensure minimization of the average message delivery time at the current level of bit error intensity.

Arduino-Powered Remote Monitoring System for Real-Time Heart Rate Detection via Bluetooth

With the increasing need for continuous health monitoring, this study presents the development of an Arduinopowered remote monitoring system for real-time heart rate detection via Bluetooth. The system uses an Arduino microcontroller connected to a pulse sensor to measure heart rate, with data wirelessly transmitted via Bluetooth to a remote device, enabling continuous monitoring without direct patient interaction. Initial self-monitoring trials showed consistent heart rate detection within the normal range of 62-70 beats per minute (BPM), suggesting proper functionality for preliminary use. The system also maintained a stable Bluetooth connection with no noticeable data loss. This cost-effective and efficient system is a valuable tool for telemedicine and remote patient care. Future enhancements may include integrating advanced microcontrollers and developing a more sophisticated mobile app with expanded health monitoring features.