Digital Monitoring System Research Articles

Research on digital twin-based dual-hull yacht sewage pump monitoring and retrieval system

Research on digital twin-based dual-hull yacht sewage pump monitoring and retrieval system

ICardioMonitor Digital Monitoring System for People with Heart Failure: Development and Evaluation of Its Accessibility and Usability

Background/Objectives: The use of eHealth as a monitoring system in people with heart failure (HF) has been shown to be effective in promoting self-care and reducing re-admissions and mortality. The present study develops and evaluates the accessibility and usability of the web app iCardioMonitor HF monitoring system. Methods: This study consisted of two stages. The first stage (co-design) comprised two phases: (1) analysis of the scientific literature and expert opinions and (2) co-design of the iCardioMonitor (web app plus a knowledge-base algorithm) and definition of alert criteria. The second stage (cross-sectional descriptive study) analyzed system accessibility (% of people using the iCardioMonitor and % of parameters recorded) and usability, employing the Spanish version of the System Usability Scale for the Assessment of Electronic Tools. Results: The iCardioMonitor was configured by a web app and an algorithm with the capacity to detect decompensated HF automatically. A total of 45 patients with an average age of 55.8 years (standard deviation [SD] = 10.582) and an average time since diagnosis of 7.1 years (SD = 7.471) participated in the second stage. The percentage of iCardioMonitor use was 83.2%. The average usability score was 77.2 points (SD = 21.828), higher in women than men (89.2; SD = 1.443–76.0; SD = 1.443) (p = 0.004). The usability score was higher the shorter the time since diagnosis (r = 0.402; p = 0.025) and the higher the number of responses (r = 0.377; p = 0.031). Conclusions: The results obtained show that iCardioMonitor is a tool accepted by patients and has obtained a remarkable score on the usability scale. iCardioMonitor was configured by a web app and an algorithm with the capacity to detect decompensated HF automatically.

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.

Innovations in Sericulture an Advancements in Silk Production and Quality Improvement

Sericulture, the cultivation of silkworms for silk production, has a long and significant history, particularly in rural economies. In recent years, the industry has undergone transformative innovations that have enhanced efficiency, sustainability, and silk quality. This review explores key advancements in sericulture, focusing on technological innovations, genetic improvements, sustainable farming practices, and the role of biotechnology in reshaping the industry. Notable technological developments, such as automated silk reeling machines and climate-controlled rearing houses, have streamlined production, reducing labor demands while ensuring consistent silk quality. Additionally, digital monitoring systems now allow for real-time tracking of silkworm health and environmental conditions, empowering farmers with data-driven insights for better management. Genetic advancements, including selective breeding and genetic engineering, have led to high-yield, disease-resistant silkworm strains, significantly boosting silk output and quality. Moreover, innovations in producing naturally colored silk via genetic modification have minimized the need for chemical dyes, reducing the environmental footprint of the dyeing process. Sustainability has become a focal point, with organic farming methods, integrated pest management (IPM), and waste recycling practices becoming more widespread. These practices not only safeguard the environment but also enhance the economic viability of sericulture, benefiting rural communities and driving social development. Biotechnology has expanded the horizon of sericulture, enabling the engineering of silk proteins and the creation of transgenic silkworms for specialized medical and industrial applications. Overall, these advancements have transformed sericulture into a more efficient, sustainable, and economically viable industry, offering significant benefits to both global silk markets and rural livelihoods.

Semi-automatic line-system provisioning with an integrated physical-parameter-aware methodology: field verification and operational feasibility

We propose methods and an architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario. We demonstrate, for the first time to our knowledge, digital longitudinal monitoring (DLM) and optical line system (OLS) physical parameter calibration working together in real-time to extract physical link parameters for fast optical fiber line systems provisioning. Our methodology has the following advantages over traditional design: a minimized footprint at user sites, accurate estimation of the necessary optical network characteristics via complementary telemetry technologies, and the capability to conduct all operation work remotely. The last feature is crucial, as it enables remote operation to implement network design settings for immediate response to quality of transmission (QoT) degradation and reversion in the case of unforeseen problems. We successfully performed semi-automatic line system provisioning over field fiber network facilities at Duke University, Durham, North Carolina. The tasks of parameter retrieval, equipment setting optimization, and system setup/provisioning were completed within 1 h. The field operation was supervised by on-duty personnel who could access the system remotely from different time zones. By comparing Q-factor estimates calculated from the extracted link parameters with measured results from 400G transceivers, we confirmed that our methodology has a reduction in the QoT prediction errors ( ±0.3dB ) over existing designs ( ±0.6dB ).

Implementation of a digital distress detection system in palliative care: qualitative data on perspectives of a multiprofessional palliative care team

BackgroundDigital health technologies such as sensor systems are intended to support healthcare staff in providing adequate patient care. In the Department of Palliative Medicine (University Medical Center Freiburg), we developed and implemented a noninvasive, bed-based sensor system in a pilot study. The aim was to detect distress in patients who were no longer able to express themselves by monitoring heart and respiratory rates, vocalizations, and movement measurements. The sensor system was intended to supplement standard care, which generally cannot guarantee constant monitoring. As there is a lack of data on how healthcare professionals experience such a techno-digital innovation, the aim of this study was to explore how the multiprofessional palliative care team who piloted the sensor system perceived its potential benefits and limitations, and how they experienced the broader context of healthcare technology and research in palliative care.MethodsWe conducted a qualitative interview study with 20 members of the palliative care team and analyzed the recorded, verbatim transcribed interviews using qualitative content analysis.ResultsThe sensor system was described as easy to use and as helpful support for patients, care staff, and relatives, especially against the backdrop of demographic change. However, it could not replace human interpretation of stress and subsequent treatment decisions: this remained the expertise of the nursing staff. A potential reduction in personnel was expected to be a risk of a digital monitoring system. The special conditions of research and digital health technologies in an end-of-life context also became clear. Specifically, healthcare staff were open to health technologies if they benefited the patient and were compatible with professional nursing and/or palliative care attitudes. Additionally, a patient-protective attitude and possible interprofessional differences in priorities and the resulting challenges for the team became apparent.ConclusionsA potential digital solution for distress monitoring was considered useful by palliative care practitioners. However, interprofessional differences and compatibility with existing palliative care practices need to be considered before implementing such a system. To increase user acceptability, the perspectives of healthcare professionals should be included in the implementation of technological innovations in palliative care.

The Comparative Field Evaluation of Four Different Traps for Mosquito Surveillance in the Republic of Korea.

Monitoring mosquito populations is essential for controlling mosquito-borne diseases, and the selection of mosquito traps should be tailored to specific surveillance objectives. Here, we tested four mosquito traps for their efficiency and applicability: the Nozawa-style black light trap (BLT), BG-sentinel trap II (BGT), UV-LED Blackhole Plus Mosquito Buster trap (LED), and digital mosquito monitoring system (DMS). The traps were rotated weekly for a 24 h cycle at the same location for 13 weeks. Overall, 1649 female mosquitoes belonging to seven genera and sixteen species were collected by the traps. The traps exhibited differences in both the number of collected individuals and species composition. The BLT showed superior collection efficiency in terms of the number of collected individuals and species evenness, whereas the BGT showed the highest species diversity among all the traps. Thus, the BLT and BGT are the best choices for effective mosquito surveillance based on trap performance. Additionally, despite the relatively low efficiency of the LED and DMS observed in this study, the LED is known to be efficient when used for indoor conditions such as cowsheds, while the DMS has an advanced function that can automatically count the number of mosquitoes. Thus, our findings provide significant guidelines for planning new mosquito surveillance projects in the ROK.

Post-discharge surgical site infection surveillance using patient smartphones: a single-centre experience in cardiac surgery

Background/Aims Surgical site infections following cardiac surgery pose significant risks and financial burdens to both patients and healthcare systems. This study aimed to explore the implementation and outcomes of a novel surgical wound monitoring system using patient smartphones for post-discharge surveillance. Methods The study was conducted at a London-based cardiothoracic tertiary referral centre, where 1358 patients undergoing cardiac surgery between January 2021 and March 2023 were enrolled onto the surgical wound monitoring system. Data were collected from the National Cardiac Audit Programme dataset, the monitoring syste and Hospital Episode Statistics data. Comparisons between patients who did or did not respond to surveillance requests were performed. A nested confirmatory analysis assessed antibiotics reported by patients through the digital route compared with antibiotics given by GPs or in outpatients. Results The overall response rate for surgical wound monitoring using patient smartphones was 86.6%. Patients who were female, from areas of higher deprivation and lived closer to the hospital were less likely to engage with surgical wound monitoring. Although not statistically significant, the current study suggests that patients with surgical site infections who used smartphones for surgical wound monitoring were less likely to be re-admitted or have further surgery and had shorter readmission stays. The accuracy of antibiotic use for surgical site infections using the surgical wound monitoring system was 96.5%. Conclusions This study underscores the potential of digital technologies, particularly smartphones, in efficient and accurate post-surgical monitoring. The findings suggest that the use of digital monitoring systems may improve patient outcomes, with potential for wider system-level benefits.

Research on digital twin monitoring system for hot stamping

Research on digital twin monitoring system for hot stamping

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

While digital twins (DTs) have recently gained prominence as a viable option for creating reliable asset representations, many existing frameworks and architectures in the literature involve the integration of different technologies and paradigms, including the Internet of Things (IoTs), data modeling, and machine learning (ML). This complexity requires the orchestration of these different technologies, often resulting in subsystems and composition frameworks that are difficult to seamlessly align. In this paper, we present a scalable compositional framework designed for the development of a DT-based production management system (PMS) with advanced production monitoring capabilities. The conducted approach used to design the compositional framework utilizes the Factory Design and Improvement (FDI) methodology. Furthermore, the validation of our proposed framework is illustrated through a case study conducted in a phosphate screening station within the context of the mining industry.

Post-discharge surgical site infection surveillance using patient smartphones: a single-centre experience in cardiac surgery

Background/Aims Surgical site infections following cardiac surgery pose significant risks and financial burdens to both patients and healthcare systems. This study aimed to explore the implementation and outcomes of a novel surgical wound monitoring system using patient smartphones for post-discharge surveillance. Methods The study was conducted at a London-based cardiothoracic tertiary referral centre, where 1358 patients undergoing cardiac surgery between January 2021 and March 2023 were enrolled onto the surgical wound monitoring system. Data were collected from the National Cardiac Audit Programme dataset, the monitoring system and Hospital Episode Statistics data. Comparisons between patients who did or did not respond to surveillance requests were performed. A nested confirmatory analysis assessed antibiotics reported by patients through the digital route compared with antibiotics given by GPs or in outpatients. Results The overall response rate for surgical wound monitoring using patient smartphones was 86.6%. Patients who were female, from areas of higher deprivation and lived closer to the hospital were less likely to engage with surgical wound monitoring. Although not statistically significant, the current study suggests that patients with surgical site infections who used smartphones for surgical wound monitoring were less likely to be re-admitted or have further surgery and had shorter readmission stays. The accuracy of antibiotic use for surgical site infections using the surgical wound monitoring system was 96.5%. Conclusions This study underscores the potential of digital technologies, particularly smartphones, in efficient and accurate post-surgical monitoring. The findings suggest that the use of digital monitoring systems may improve patient outcomes, with potential for wider system-level benefits.

Perancangan Monitoring Coal Handling System PLTU Kaltim Teluk Berbasis Internet of Things

Abstract— Balikpapan Bay PLTU is a large capacity power plant located in the city of Balikpapan, which is located in East Kalimantan. This PLTU with a capacity of 2X110 MW meets the electricity needs of the Barito Mahakam network, which consists of the East Kalimantan, North Kalimantan, Central Kalimantan and South Kalimantan regions. The main fuel for electricity generation is low grade coal (LRC) or low calorie coal. High Speed Diesel (HSD) oil is used as initial fuel. DCS (Distributed Control System) is used for wood management at PLTU Kaltim Teluk. DCS helps operations by monitoring and controlling the main and supporting components, however, management, supervisors and other staff have difficulty knowing the operating conditions of the generating unit remotely because the monitoring system can only be accessed by the control room operator at the CCR. The aim of this research is to design an Internet of Things-based coal handling system control system for PLTU Kaltim Teluk. This real time based digital monitoring system can collect and display data from every sensor in the field. The research method is a literature study method and a field method to apply the design results and collect monitoring data at the two Balikpapan Bay PLTUs. The results show that testing, which includes integration testing with MySQL, functional testing, and URL and Endpoint testing, was carried out successfully. As expected, all the main features and functions of the PLTU monitoring system are running well. This system has averagepercentage error 0.1%. So this study has an accuracy rate of 99.9%. This system has the ability to make it easier for managers to monitor the system.

Fortifying Uzbekistan's integrity landscape: Harnessing India's tech-driven anti-corruption strategies

Corruption poses significant challenges to sustainable development and social justice in Uzbekistan. This paper explores how Uzbekistan can strengthen its anti-corruption framework by leveraging emerging technologies and drawing lessons from India's experience in using information and communication technology (ICT) to combat corruption. The study employs a qualitative research methodology, analysing data from government reports, case studies, and expert interviews to identify specific areas where Uzbekistan can learn from India's successes and challenges in applying ICT solutions. The findings highlight several key ways ICT can bolster anti-corruption efforts in Uzbekistan, such as increasing transparency through e-governance platforms, improving accountability via digital monitoring systems, and enabling citizen participation with online reporting tools. The paper provides concrete examples and data from India demonstrating how technologies like biometrics, blockchain, and data analytics have helped detect fraud, streamline bureaucratic processes, and empower citizens to report corruption. However, the research also reveals critical legal, institutional and cultural barriers Uzbekistan must address to effectively implement these tech-based approaches, such as outdated regulations, lack of technical expertise, and public distrust. Comparing India and Uzbekistan's contexts, the paper offers tailored recommendations for how Uzbekistan can adapt India's ICT models to overcome its unique constraints. The study concludes that while technology is not a panacea, strategically integrating ICT into Uzbekistan's anti-corruption arsenal – with insights from India's experience – can be a powerful tool to promote good governance, curb corruption, and ultimately advance social justice for citizens. More research is needed to assess the long-term impacts and scalability of specific ICT interventions.

A Digital Vaccination Pass Using Fast Healthcare Interoperability Resources: A Proof of Concept

The traditional manual recording of vaccination records in Germany faced challenges during the COVID-19 pandemic, prompting the introduction of a COVID smartphone app with QR codes. However, this solution brought new challenges, emphasizing the need for a centrally managed European digital vaccination record for efficiency and validity. This study assesses the feasibility of using the HL7 FHIR standard in the healthcare industry for implementing a digital vaccination pass management and monitoring system. The system aims to offer convenience and improved efficiency for both patients and healthcare providers while promoting interoperability with other healthcare systems. To this end, we developed a prototype using modern technologies, such as React, Quarkus, and Keycloak. Results indicate potential benefits for patients and healthcare providers, offering access to immunization records, personalized recommendations, and streamlined management. However, integrating nuanced vaccination processes into the standardized FHIR system requires custom extensions, which might hinder interoperability. Manual data entry and the integration of an identity provider present further obstacles in industry scenarios. Despite these challenges, this study suggests that implementing HL7 FHIR can enhance efficiency, data accessibility, and accuracy in the vaccination process, supporting broader digitization efforts in the German healthcare system and beyond.

Application of Clustering Algorithm in Fault State Classification of Low Voltage Watt-Hour Meter

In this paper, a low-voltage digital watt-hour meter monitoring system for smart grid is designed. The system includes information acquisition system, low-voltage digital meter and power service system. The low-voltage digital meter uses RFID chip inside, which can accurately locate the target through high-speed transmission and remote identification. It can effectively overcome the security risks caused by information collision and the problem of slow recognition speed. According to different fault categories, community clustering method is used to classify them. In the actual determination of the fault causes of 32 electric energy meters with this method correctly analyzed the fault causes of 26 electric energy meters. The accuracy rate reached 81.25%.

Advancing horizons in vegetable cultivation: a journey from ageold practices to high-tech greenhouse cultivation-a review.

Vegetable cultivation stands as a pivotal element in the agricultural transformation illustrating a complex interplay between technological advancements, evolving environmental perspectives, and the growing global demand for food. This comprehensive review delves into the broad spectrum of developments in modern vegetable cultivation practices. Rooted in historical traditions, our exploration commences with conventional cultivation methods and traces the progression toward contemporary practices emphasizing the critical shifts that have refined techniques and outcomes. A significant focus is placed on the evolution of seed selection and quality assessment methods underlining the growing importance of seed treatments in enhancing both germination and plant growth. Transitioning from seeds to the soil, we investigate the transformative journey from traditional soil-based cultivation to the adoption of soilless cultures and the utilization of sustainable substrates like biochar and coir. The review also examines modern environmental controls highlighting the use of advanced greenhouse technologies and artificial intelligence in optimizing plant growth conditions. We underscore the increasing sophistication in water management strategies from advanced irrigation systems to intelligent moisture sensing. Additionally, this paper discusses the intricate aspects of precision fertilization, integrated pest management, and the expanding influence of plant growth regulators in vegetable cultivation. A special segment is dedicated to technological innovations, such as the integration of drones, robots, and state-of-the-art digital monitoring systems, in the cultivation process. While acknowledging these advancements, the review also realistically addresses the challenges and economic considerations involved in adopting cutting-edge technologies. In summary, this review not only provides a comprehensive guide to the current state of vegetable cultivation but also serves as a forward-looking reference emphasizing the critical role of continuous research and the anticipation of future developments in this field.

An online monitoring method of milling cutter wear condition driven by digital twin

Real-time online tracking of tool wear is an indispensable element in automated machining, and tool wear directly impacts the processing quality of workpieces and overall productivity. For the milling tool wear state is difficult to real-time visualization monitoring and individual tool wear prediction model deviation is large and is not stable and so on, a digital twin-driven ensemble learning milling tool wear online monitoring novel method is proposed in this paper. Firstly, a digital twin-based milling tool wear monitoring system is built and the system model structure is clarified. Secondly, through the digital twin (DT) data multi-level processing system to optimize the signal characteristic data, combined with the ensemble learning model to predict the milling cutter wear status and wear values in real-time, the two will be verified with each other to enhance the prediction accuracy of the system. Finally, taking the milling wear experiment as an application case, the outcomes display that the predictive precision of the monitoring method is more than 96% and the prediction time is below 0.1 s, which verifies the effectiveness of the presented method, and provides a novel idea and a new approach for real-time on-line tracking of milling cutter wear in intelligent manufacturing process.

Digital Technology: A Step to Protect Cave Art of Indian Subcontinent as National Heritage – A Review

Abstract The integration of digital technology, particularly virtual reality, is proving to be a pivotal tool in preserving and sharing the rich cultural heritage found within Cave art sites. This article deliberates on the use and application of digital technology in the field of cave painting conservation that provides an authentic and effective method of Cave art preservation for the future. Employing advanced techniques of photogrammetry, terrestrial laser scanning, structured light scanning, and high-resolution photography can digitally preserve the intricate details of Cave art, while the utilization of humidity, temperature, and CO2 sensors may provide a comprehensive digital monitoring system to track the condition of Cave art over time. This paper deals with the evolving landscape of technologies and their application to safeguard Cave art from environmental degradation and anthropogenic factors. The digitization of cave art has the potential to accurately conserve a site if used in an effective manner while also allowing visitors to experience this art form in ways never before feasible. The application of advanced digital technology in cave art conservation is not merely a choice but a necessity, considering the impermanent nature of these paintings in their natural environment. This paper underscores the urgency and significance of leveraging digital tools to ensure the enduring legacy of Cave art, an example of how digital technologies, as they evolve, will play an increasingly essential role in the conservation and dissemination of our world’s extraordinary cultural heritage.

A Digital Respiratory Ward in Leicester, Leicestershire, and Rutland, England, for Patients With COVID-19: Economic Evaluation of the Impact on Acute Capacity and Wider National Health Service Resource Use.

The COVID-19 pandemic stressed global health care systems' acute capacity and caused a diversion of resources from elective care to the treatment of acute respiratory disease. In preparing for a second wave of COVID-19 infections, England's National Health Service (NHS) in Leicester, Leicestershire, and Rutland sought to protect acute capacity in the winter of 2020-2021. Their plans included the introduction of a digital ward where patients were discharged home early and supported remotely by community-based respiratory specialists, who were informed about patient health status by a digital patient monitoring system. The objective of the digital ward was to maintain acute capacity through safe, early discharge of patients with COVID-19 respiratory disease. The study objective was to establish what impact this digital ward had on overall NHS resource use. There were no expected differences in patient outcomes. A cost minimization was performed to demonstrate the impact on the NHS resource use from discharging patients into a digital COVID-19 respiratory ward, compared to acute care length of stay (LOS). This evaluation included all 310 patients enrolled in the service from November 2020 (service commencement) to November 2021. Two primary methods, along with sensitivity analyses, were used to help overcome the uncertainty associated with the estimated comparators for the observational data on COVID-19 respiratory acute LOS, compared with the actual LOS of the 279 (90%) patients who were not discharged on oxygen nor were in critical care. Historic comparative LOS and an ordinary least squares model based on local monthly COVID-19 respiratory median LOS were used as comparators. Actual comparator data were sourced for the 31 (10%) patients who were discharged home and into the digital ward for oxygen weaning. Resource use associated with delivering care in the digital ward was sourced from the digital system and respiratory specialists. In the base case, the digital ward delivered estimated health care system savings of 846.5 bed-days and US $504,197 in net financial savings across the 2 key groups of patients-those on oxygen and those not on oxygen at acute discharge (both P<.001). The mean gross and net savings per patient were US $1850 and US $1626 in the base case, respectively, without including any savings associated with a potential reduction in readmissions. The 30-day readmission rate was 2.9%, which was below comparative data. The mean cost of the intervention was US $223.53 per patient, 12.1% of the estimated gross savings. It was not until the costs were increased and the effect reduced simultaneously by 78.4% in the sensitivity analysis that the intervention was no longer cost saving. The digital ward delivered increased capacity and substantial financial savings and did so with a high degree of confidence, at a very low absolute and relative cost.

Bulk Power Systems Emergency Control Based on Machine Learning Algorithms and Phasor Measurement Units Data: A State-of-the-Art Review

Modern electrical power systems are characterized by a high rate of transient processes, the use of digital monitoring and control systems, and the accumulation of a large amount of technological information. The active integration of renewable energy sources contributes to reducing the inertia of power systems and changing the nature of transient processes. As a result, the effectiveness of emergency control systems decreases. Traditional emergency control systems operate based on the numerical analysis of power system dynamic models. This allows for finding the optimal set of preventive commands (solutions) in the form of disconnections of generating units, consumers, transmission lines, and other primary grid equipment. Thus, the steady-state or transient stability of a power system is provided. After the active integration of renewable sources into power systems, traditional emergency control algorithms became ineffective due to the time delay in finding the optimal set of control actions. Currently, machine learning algorithms are being developed that provide high performance and adaptability. This paper contains a meta-analysis of modern emergency control algorithms for power systems based on machine learning and synchronized phasor measurement data. It describes algorithms for determining disturbances in the power system, selecting control actions to maintain transient and steady-state stability, stability in voltage level, and limiting frequency. This study examines 53 studies piled on the development of a methodology for analyzing the stability of power systems based on ML algorithms. The analysis of the research is carried out in terms of accuracy, computational latency, and data used in training and testing. The most frequently used textual mathematical models of power systems are determined, and the most suitable ML algorithms for use in the operational control circuit of power systems in real time are determined. This paper also provides an analysis of the advantages and disadvantages of existing algorithms, as well as identifies areas for further research.