Implementation Of Monitoring System Research Articles

A study on AI driven mental health monitoring system

Mental health challenges have become a global concern, with millions affected by conditions such as depression, anxiety, and stress. Despite the growing need for mental health services, barriers such as stigma, limited accessibility to care, and a shortage of trained professionals hinder timely interventions. The integration of artificial intelligence (AI) into mental health monitoring systems offers a transformative approach to addressing these challenges. AI-driven systems leverage machine learning algorithms, natural language processing (NLP), and data analytics to monitor and assess mental health in real time. These systems can analyze diverse data sources, including speech patterns, text inputs, facial expressions, and physiological signals, to identify early signs of mental health issues. By providing continuous, scalable, and non-invasive monitoring, AI enhances traditional methods by offering personalized insights and timely interventions. Recent advancements in AI, such as deep learning and emotion recognition, have significantly improved the accuracy and reliability of these systems. Moreover, the incorporation of wearable technology and mobile health applications enables individuals to track their mental well-being seamlessly. While promising, these systems also raise ethical concerns around privacy, bias, and the need for robust validation in clinical settings. This paper explores the design, implementation, and ethical considerations of AI-driven mental health monitoring systems, highlighting their potential to revolutionize mental health care and improve patient outcomes.

Harnessing artificial intelligence for enhanced veterinary diagnostics: A look to quality assurance, Part II External validation.

Artificial intelligence (AI) is emerging as a valuable diagnostic tool in veterinary medicine, offering affordable and accessible tests that can match or even exceed the performance of medical professionals in similar tasks. Despite the promising outcomes of using AI systems (AIS) as highly accurate diagnostic tools, the field of quality assurance in AIS is still in its early stages. Our Part I manuscript focused on the development and technical validation of an AIS. In Part II, we explore the next step in development: external validation (i.e., in silico testing). This phase is a critical quality assurance component for any AIS intended for medical use, ensuring that high-quality diagnostics remain the standard in veterinary medicine. The quality assurance process for evaluating an AIS involves rigorous: (1) investigation of sources of bias, (2) application of calibration methods and prediction of uncertainty, (3) implementation of safety monitoring systems, and (4) assessment of repeatability and robustness. Testing with unseen data is an essential part of in silico testing, as it ensures the accuracy and precision of the AIS output.

Advanced Autonomous System for Monitoring Soil Parameters

Context: This research investigates the advantages of real-time monitoring of soil quality for various land management practices. It also highlights the significance of spatio-temporal soil modeling and mapping in providing a clear and visual understanding of how aridity changes over time and across different locations. Aims: This paper aims to provide a comprehensive guide to the key processes required for the development of a laboratory-based soil quality monitoring system. Methods: The applied methodologies involved the processes of sensor deployment, data acquisition infrastructure establishment, and sensor calibration. These procedures culminated in the development of a soil quality assessment model that was subsequently subjected to two months of laboratory testing using three distinct soil types. The analysis yielded a strong positive linear correlation between the measured and predicted soil quality values. Key Results: As expected, the assimilation of prior soil quality estimates within the modeling framework demonstrated a significant enhancement in the accuracy of real-time soil quality estimations. Conclusions: This research promotes the importance of iterative improvements of the soil quality monitoring system. The need for a long-term perspective and a plan for maintenance and continuous improvement of such systems in the ecosystem is important to improve the ease of making predictions to avoid soil aridization. The results of this research will be useful for researchers and practitioners involved in the design and implementation of soil monitoring systems.

Pearl Catfish Pond Water Quality Monitoring System Using the ThingSpeak Server

The research is centered around the implementation of an IoT-based water quality monitoring system for Pearl catfish ponds. This system uses ThingSpeak server to monitor pH, turbidity, temperature, and ammonia levels to maintain ideal conditions for fish growth. Data is processed using fuzzy logic. The results are sent in real time to the ThingSpeak server for continuous monitoring. The overarching goal of this system is to optimize production efficiency and improve the quality of fish for catfish farmers. The research has successfully developed an Internet of Things (IoT)-based water quality monitoring system for catfish ponds, demonstrating the positive impact of probiotics on both water quality and fish growth. Notably, Fishpond A, which received probiotic treatment, demonstrated notably superior water quality in comparison to Pond B without probiotics. Additionally, fuzzy logic testing indicated a high degree of accuracy, underscoring the system's effectiveness in real-time water condition monitoring.

Novel Implementation of Vehicle Drivers Alcohol and Temperature Monitoring System

Novel Implementation of Vehicle Drivers Alcohol and Temperature Monitoring System

Impact Of Accountability, Public Transparency, And Internal Oversight Functions On The Performance Of The Regional Government Of Bengkulu District Central

The study aims to investigate the influence of accountability, public transparency, and internal supervision responsibilities on the performance of the Bengkulu District Regional Government in relation to the Central District Development Unit. This investigation conducts quantitative research by administering questionnaires to each SKPD and employing survey methodologies to gather data. The method of purposive sampling is employed to select samples according to predetermined criteria. In the district of Bengkulu Central, the sample was composed of 40 respondents who were selected from 40 Working Units of Regional Devices (SKPD). The methodology utilized is double linear regression analysis. This study's results suggest that the regional government's operations are significantly influenced by both internal supervision and accountability responsibilities. However, regional administration's efficacy is minimally affected by the degree of public transparency. It is evident from the test results that the Regional Government's performance is not guaranteed to be improved by the presence of Public Transparency. Nevertheless, the potential enhancement of the regional government's efficacy could be positively influenced by the implementation of transparent and internal monitoring systems within the local administration, which are accountable to the public.

Hardware and software complex for remote monitoring of the objects state and their control of digital television and radio broadcasting network

The creation and subsequent implementation of domestic systems for automatic monitoring of the telecommunications services quality is an important scientific and practical task in light of the need to ensure the technological sovereignty of the Russian critical information infrastructure. The article presents the results of research and development work on the creation of a hardware and software complex that can be used as a basic structural element in the construction of a system for remote monitoring and control of communication objects of a digital television and radio broadcasting network. Keywords diagnostics, communication object, design, performance, development, television and radio broadcasting, quality management, digital technologies

Towards digitalized and automated substations: implementation of adaptive protection control unit and monitoring system for modern distribution networks under increased hosting capacity of distributed renewable sources

Towards digitalized and automated substations: implementation of adaptive protection control unit and monitoring system for modern distribution networks under increased hosting capacity of distributed renewable sources

Research and implementation of monitoring system of disc cutter rotation speed

Research and implementation of monitoring system of disc cutter rotation speed

GRAIN EXPORT FROM UKRAINE: CHANGES DURING THE PERIOD OF MARTIAL LAW

This article delves into the complexities and challenges faced by Ukraine’s grain export sector amid the ongoing conflict and evolving legislative landscape. The analysis begins by exploring the significance of grain exports for Ukraine’s economy, particularly during wartime, and the critical role they play in ensuring food security both domestically and globally. The article examines recent legislative initiatives aimed at enhancing transparency and accountability in the grain export process, specifically focusing on new laws intended to combat the issue of “black” grain exports, which have raised concerns about corruption and mismanagement. It discusses the implications of these laws for exporters, government agencies, and regulatory bodies, highlighting the need for effective implementation and oversight. A significant portion of the article is dedicated to the importance of railway logistics as a primary mode of transportation for grain exports, especially in light of disruptions caused by the conflict. The analysis considers how new transportation routes and strategies are being developed to facilitate the movement of grain despite the ongoing challenges. Additionally, the article examines trade disputes with Poland, which have complicated Ukraine’s export efforts and created further barriers to trade. It concludes that while recent legislative measures are crucial for stabilizing grain exports, their effectiveness depends on timely implementation of subordinate regulations and strong monitoring systems. The findings indicate that the Ukrainian government must enhance coordination among state bodies to ensure compliance and reduce corruption risks. Ultimately, the article emphasizes the importance of navigating the complexities of grain exports during wartime to safeguard national interests and contribute to global food security.

AI for Creating Safer School in Indonesia

While Indonesia's access to education has improved, its quality remains a concern, particularly in addressing widespread social issues like bullying. Schools need innovative solutions that provide real-time insights and enable timely interventions, and AI offers promising advancements in this area. However, the implementation of AI-based monitoring systems faces challenges, not only due to technological limitations but also significant ethical concerns. This study examines the ethical considerations surrounding the use of AI video analytics in detecting and preventing bullying in schools. By applying the ethical frameworks of Utilitarianism, Deontology, and Virtue Ethics, the research provides a comprehensive evaluation of whether AI can be ethically integrated into school surveillance systems. The findings suggest that while AI video analytics can enhance student safety and well-being by reducing harm, there are significant ethical concerns related to privacy, potential biases, and the risk of undermining the role of teachers. The study concludes that AI systems can be ethically justified if implemented with transparent privacy safeguards, continuous refinement to avoid bias, and careful integration to support teachers. These findings offer practical recommendations for policymakers and educators on the responsible implementation of AI in educational environments.

Ball Street Bridge Conservation Management Plan

This Conservation Management Plan focuses on Ball Street Bridge, a Grade II listed Victorian-era bridge in Sheffield, England, recognized for its architectural and historical significance. The plan identifies key management challenges, including structural aging, environmental impacts, community use, and the absence of heritage interpretation. A detailed action plan outlines strategies to address these issues, ensuring the bridge’s structural integrity, environmental sustainability, and role as a community and heritage resource. The plan emphasizes regular structural inspections, the implementation of environmental monitoring systems, and measures to engage the community while mitigating vandalism. Additionally, it recommends the installation of interpretive signage and the development of educational programs to enhance public understanding of the bridge’s historical and cultural importance. Through these initiatives, the plan aims to preserve Ball Street Bridge as a vital part of Sheffield's industrial heritage and a resource for future generations.

Design and Implementation of Sports Safety Mechanics Signal Monitoring System in Sports Training

Design and Implementation of Sports Safety Mechanics Signal Monitoring System in Sports Training

Applying Multi-Purpose Commercial Inertial Sensors for Monitoring Equine Locomotion in Equestrian Training.

Inappropriate, excessive, or overly strenuous training of sport horses can result in long-term injury, including the premature cessation of a horse's sporting career. As a countermeasure, this study demonstrates the easy implementation of a biomechanical load monitoring system consisting of five commercial, multi-purpose inertial sensor units non-invasively attached to the horse's distal limbs and trunk. From the data obtained, specific parameters for evaluating gait and limb loads are derived, providing the basis for objective exercise load management and successful injury prevention. Applied under routine in-the-field training conditions, our pilot study results show that tri-axial peak impact limb load increases progressively from walk to trot to canter, in analogy to stride frequency. While stance and swing phases shorten systematically with increasing riding speed across subjects, longitudinal and lateral load asymmetry are affected by gait at an individual level, revealing considerable variability between and within individual horses. This individualized, everyday approach facilitates gaining valuable insights into specific training effects and responses to changing environmental factors in competitive sport horses. It promises to be of great value in optimizing exercise management in equestrian sports to benefit animal welfare and long-term health in the future.

Monitoring of Directed Energy Deposition Laser Beam of Nickel-Based Superalloy via High-Speed Mid-Wave Infrared Coaxial Camera

Directed Energy Deposition Laser Beam (DED-LB) is a promising additive manufacturing technique that uses a laser source and a powder stream to build or repair metal components. Repair applications offer significant economic and environmental benefits but are more challenging to develop, especially for components that are difficult to process due to their intricate geometries and materials. Process conditions can change precipitously, and it is essential to implement monitoring systems that ensure high process stability and, consequently, superior end-product quality. In the present work, a mid-wave infrared coaxial camera was used to monitor the melt pool geometry. To simulate the challenging repair process conditions of the DED-LB process, experimental tests were carried out on substrates with different thicknesses. The stability of the deposition process on nickel-based superalloys was analyzed by means of MATLAB algorithms. Thus, the effect of open-loop and closed-loop monitoring with back control on laser power on the process conditions was assessed and quantified. Metallographic analysis of the produced samples was carried out to validate the analyses performed by the monitoring system. The occurrence of production defects (lack of fusion and porosity) related to parameters not directly controllable by monitoring systems, such as penetration depth and dilution, was determined.

USE OF GEO-INFORMATION SYSTEMS FOR GROUNDWATER MONITORING

Abstract . The article is devoted to the study of the possibilities of using geographic information systems (GIS) for monitoring the state of groundwater, which is important for ensuring environmental safety and sustainable management of water resources. Groundwater is an important source of fresh water for the population, industry and agriculture, but it is vulnerable to various pollutions caused by both natural and anthropogenic factors. Therefore, the implementation of reliable monitoring systems that allow timely detection, assessment and forecasting of changes in water quality is necessary to prevent the deterioration of the ecological situation and prevent the spread of pollution. Geographic information systems (GIS ) offer significant opportunities for the collection and integration of large volumes of spatial data, including satellite images, remote sensing results, automated sensor data, and field observations. GIS allow creating multi-layered maps reflecting the ecological state of underground aquifers, modeling pollution processes and predicting their possible impact on nearby ecosystems and water sources. Thanks to the use of GIS, it is possible to combine data from different sources in a single interactive system, which simplifies analysis and provides the ability to quickly respond to any detected deviations. The article examines in detail the key methods used within GIS for groundwater monitoring, including satellite sounding to analyze changes in the earth's surface, spectral indices to assess the state of vegetation and soil salinity, and radar methods to determine soil electrical conductivity. Particular attention is paid to the application of three-dimensional modeling, which allows visualization of the spread of pollution in underground aquifers, which facilitates decision-making regarding the optimal location of monitoring stations and the design of protective structures. In combination with automated sensors recording water parameters in real time, GIS provides continuous monitoring of the physico-chemical indicators of groundwater and allows for prompt assessment of their condition. The article also analyzes the possibilities of using predictive modeling in GIS to assess the further spread of pollution and develop environmental risk management measures. It is described how mathematical models in GIS can help predict the impact of anthropogenic and natural factors on groundwater, which ensures the development of scientifically based solutions to reduce pollution and maintain water quality at a safe level. The implementation of GIS in groundwater monitoring is an important step towards increasing the efficiency of water resources management, ensuring their protection from pollution and preserving the ecological stability of the regions.

Applied fault diagnosis with distributed monitoring systems: Bridging theory with practice

We address the feasibility of the pragmatic implementation of monitoring systems for real-time distributed fault diagnosis in complex processes. We delve into the integration of theoretical distributed estimation methods and practical distributed embedded systems. This study emphasizes the merger of distributed computing and signal processing to augment fault diagnosis in dynamic systems. We introduce a generic mathematical model for distributed fault diagnosis algorithms, laying the groundwork for a reference network computing architecture that details the essential components, organization, and operational characteristics necessary for distributed monitoring systems. Subsequently, we evaluate existing software and hardware solutions that facilitate the realization of these systems. The theoretical framework and system design are empirically validated through an experimental setup involving a liquid-level control system, demonstrating the efficacy and applicability of our approach.

Update in association between Lung Cancer and air pollution.

A significant portion of newly diagnosed lung cancer cases occur in populations exposed to air pollution. The World Health Organization has identified air pollution as a human carcinogen, prompting many countries to implement monitoring systems for ambient particulate matter (PM). PM consists of a complex mix of organic and inorganic particles, both solid and liquid, present in the air. Given the carcinogenic properties of PM and the prevalence of lung cancer in exposed populations, it is crucial to explore their connection and clinical implications to effectively prevent lung cancer in this group. This review examines the link between ambient PM and lung cancer. Epidemiological studies have shown a dose-response relationship between PM exposure and lung cancer risk. PM exposure leads to oxidative stress, disrupting the body's redox balance and causing DNA damage, a key factor in cancer development. Recent findings on the strong correlation between ambient PM and adenocarcinoma suggest that understanding the specific molecular and pathological background of pollution-related lung cancer is important. In addition to efforts to control emission sources at the international level, a more individualized approach is necessary to prevent PM-related lung cancer development.

Identification of Climate Change Risks to Surface and Groundwater Resources across the Central African Republic and Resilience Measures

The extensive hydrological and hydrogeological systems across the Central African Republic (CAR) provide essential urban and rural water supplies for the populations across the country. Hydrological and hydrogeological studies during the last 20 years are extremely limited, in part due to the complex security and socio-economic context. As a result, significant uncertainties exist related to water resource availability and infrastructure management. This paper examined the recent evolution of the meteorological, hydrological, and hydrogeological regimes across CAR and the potential future impacts of climate change on surface and water resource availability. This was undertaken by analyzing the available regional hydrometry data and using regional climate change projections to evaluate changes to rainfall and evapotranspiration patterns by 2050. A lack of long-term monitoring data and operational monitoring systems prevents a detailed assessment of these risks at local levels. Although the national scale findings suggest that water resources may slightly increase over the next 40 years, significant local risks remain due to intensifying, increasingly variable rainfall, and increasing demographic pressures. The lack of functional, national-scale water resource monitoring systems contributes to the fragile resilience of the populations across CAR in the face of increased climate-associated risks. Recommendations are included for measures to help characterize and manage the potential risks in the long-term including the implementation of robust water resource monitoring systems

Improving Energy Efficiency for Culinary MSMEs in Legok Village Through Electrical Management Trainin

This community service aims to empower Micro, Small, and Medium Enterprises (MSMEs) in the culinary sector in Legok Village, Tangerang, Banten through efficient electrical management training and the implementation of an energy consumption monitoring system. Legok Village, known for its diverse traditional culinary offerings, faces challenges in managing efficient electricity consumption in their daily operations. It is known that in the culinary field, various electrical appliances are needed to support the preparation of food and beverages. The use of these electrical devices needs to be closely monitored so that their management can be regulated to become more energy-efficient. This service includes practical training and education on energy-saving practices, efficient electrical equipment, and power management strategies to help culinary MSMEs in Legok Village reduce electricity costs and enhance the sustainability of their businesses.