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94 articles for “Risk-based monitoring”
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Smart City Based Manhole Monitoring System
Abstract: Urban environments are increasingly reliant on complex underground infrastructure networks, with manholes serving as critical access points for maintenance, inspection, and drainage. However, traditional manhole monitoring methods, often manual and labour-intensive, can be inefficient and prone to human error. This can lead to serious safety and health hazards, such as accidents caused by open manholes, exposure to harmful gas leaks, and infrastructure damage from overflows due to undetected blockage This …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 27–34 Read article
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A Review on Social Distancing ID Card
Abstract: The frequency of fire accidents in homes, industries, and public spaces has increased due to electrical faults, human negligence, and flammable materials. Traditional fire-fighting systems often depend on human presence and manual intervention, which delays the response time. To overcome this limitation, this project presents an Automatic Fire Extinguisher System based on Arduino and IoT technology for real- time detection and suppression of fire. Gas, temperature, and flame sensors are …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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A Study on High-Risk Pregnancy and Its Management: Role of Obstetric Nurses in Improving Maternal and Fetal Outcomes
Abstract: High-risk pregnancy is a major challenge in maternal and neonatal healthcare and is associated with increased morbidity and mortality among mothers and new-borns, particularly in developing regions where access to quality healthcare services remains uneven, this article examines the concept, classification, risk factors, pathophysiology, and management of high-risk pregnancy with a strong focus on the role of obstetric nurses in improving maternal and fetal outcomes, obstetric nurses play a central …
Published in International Journal of Midwifery Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 26–43 Read article
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IoT-Enabled Sustainable Development: Architectures, Applications, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) has developed into a powerful technology that can help tackle key global sustainability issues by enabling real-time monitoring, supporting data-based decisions, and facilitating smart automation. By interconnecting physical devices, sensors, and communication networks, IoT enables continuous data collection and analysis that supports efficient resource utilization across multiple sectors such as energy, agriculture, water management, transportation, and urban infrastructure. Through smart sensing and automated control systems, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Impact of Groundwater Pollution on Carcinogenic and Non-Carcinogenic Health Effects: A Review
Abstract: Groundwater is a critical source of drinking water in many regions worldwide, particularly in South and Southeast Asia, where dependence on untreated groundwater remains high. However, increasing groundwater contamination poses serious risks to human health. This review synthesizes recent peer-reviewed studies to examine the sources, distribution, and health impacts of major groundwater contaminants, with a focus on both carcinogenic and non-carcinogenic risks. Emphasis is placed on fluoride, nitrate, chromium, and …
Published in Research & Reviews : Journal of Ecology · Vol. 15, Issue 1, 2026 · pp. 40–46 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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IoT-based Patient Fall Detection and Alerting System for Patient Safety
Abstract: This paper presents an Internet of Things (IoT) based patient fall detection and alerting system designed to enhance patient safety in healthcare settings. Falls among patients, especially in hospitals or care facilities, can lead to severe injuries and complications. The proposed system utilizes wearable sensors integrated with IoT technology to continuously monitor the movements and activities of patients. Machine learning algorithms are employed to analyze sensor data in real time, …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 9–14 Read article
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The Role of Artificial Intelligence in Enhancing Athlete Performance and Training Strategies
Abstract: Artificial Intelligence (AI) is transforming modern sports by improving athlete performance, training methods, and decision-making processes. The integration of AI technologies such as machine learning, data analytics, wearable sensors, and computer vision has enabled coaches and sports scientists to analyze large amounts of performance data with greater accuracy and efficiency. Athletes' physiological indicators, movement patterns, injury risks, and recuperation processes are all monitored by these technology. Training regimens can therefore …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article
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Reviewing Threat Detection Methods in SaaS Platforms Through the Use of Adaptive Cloud Security Models
Abstract: Software as a Service (SaaS) solution has revolutionized the contemporary business processes as scalable and service-on-demand solution on cloud networks. Yet, this expansion has brought in sophisticated cybersecurity risks because of a multi-tenant environment facing the internet in the SaaS environment. The key to assure the service availability and protection of the data stored off-site is effective threat detection in such dynamic ecosystems. This review article seeks to discuss the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 Read article
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IoT-Based Public Toilet Monitoring System
Abstract: Public restroom maintenance is critical to urban hygiene and requires good resource management to secure hygiene, sustainability, and costs. This project presents the design and implementation of a real-time monitoring system for public restrooms, including IoT-based sensors, to measure key environmental factors, such as ammonia concentration, ambient light, and water level. The system can continuously monitor ammonia concentrations to detect poor air quality, opening an intervention window to remedy the …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 15–25 Read article
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IoT-enhanced Real-time Monitoring and Hazard Detection
Abstract: This research explores the innovative application of internet of things (IoT) technology within occupational health and safety management systems (OHSMS) to substantially improve real-time monitoring and hazard detection in industrial settings. IoT sensors and wearable devices are deployed to enable continuous and thorough collection of data on environmental conditions, equipment status, and worker health. Real-time data analysis facilitated by IoT technology allows for the rapid identification and mitigation of potential …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 20–24 Read article
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The Impact of Climate Change on Infectious Diseases: Potential Risks and Mitigation Strategies
Abstract: As we confront the pressing challenge of climate change, it's vital to recognize its intertwined connection with infectious diseases. We must now navigate a future that combines strong public health interventions, environmental stewardship, and strong policy actions as we stand at the crossroads of crises. In an attempt to lessen the drastic effects of climate change on the dynamics of disease transmission, this study identifies potential risks and creative solutions. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 21–32 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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A Trust-Enhanced Security Architecture for Authenticating Customer Records in Banking Institutions
Abstract: The growing digital disruption of banking and financial services has completely altered the face of customer onboarding, money transactions, and financial service deliveries. Even as digital technologies provide unparalleled levels of efficiency and accessibility for consumers of financial services, they have also presented new challenges that are equally daunting. Among the growing number of financial threats that digital technology has spawned is the risk of synthetic identity fraud. Unlike identity …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 16–22 Read article