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132 articles for “real-time detection”
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Machine Learning Approach for Analysis of Ionosphere Parameters for Earthquake Precursors
Abstract: This research explores the relationship between seismic events and predictive indicators, focusing on machine learning-based strategies for early earthquake prediction. It dissects existing prediction approaches, highlighting ionospheric anomalies' correlation with seismic occurrences, particularly preceding earthquakes of magnitudes higher than 5.5. By identifying a lack of comprehensive long-term analyses in the field, the study emphasizes future trends in machine learning-driven EQ-PD techniques using GPS-TEC data for real-time anomaly detection. The methodology …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 9, Issue 2, 2023 · pp. 37–46 Read article
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Automated Diagnosis and Drug Delivery System for Colon Cancer Using Biosensors and Nanostructures
Abstract: Colorectal cancer stands as a significant global health challenge, necessitating innovative approaches for early detection and effective treatment. This paper presents a novel framework for addressing this challenge by integrating biosensors with nano materials and nano structures to create an automated system for colon cancer diagnosis and treatment. The proposed system leverages the unique properties of biosensors for real-time disease detection and the advanced capabilities of nano materials and nano …
Published in International Journal of Nanomaterials and Nanostructures · Vol. 10, Issue 1, 2024 · pp. 10–23 Read article
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Semantic Segmentation for Object Detection in Videos using Mask RCNN
Abstract: The segmentation of object instances is an essential step in real-time video detection. Object detection is the problem of detecting the information of all types of items in an image by designating their location with a rectangular box. Using its remarkable feature-learning capabilities, deep learning promotes object detection research. Numerous researchers have utilised various machine learning algorithms for object detection and have focused on enhancing the accuracy of feature extraction. …
Published in International Journal of Digital Communication and Analog Signals · Vol. 8, Issue 2, 2022 · pp. 7–15 Read article
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Blind Assistance System Using Digital Image Processing
Abstract: This paper brings forth state-of-the-art blind assistance, and the system here provides a combination of an OpenCV-based DNN module based on YOLOv3’s algorithm; the system would support real-time object detection, with associated auditory notifications to enable visually impaired individuals to understand their autonomy couched with safety about improved fast recognition of objects allied with auditory responses. The live video captures from a webcam were done and further processed by the …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 13–19 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Nanorobotics in Cancer Treatment: A Study
Abstract: Cancer, a complex and devastating disease, continues to plague humanity. There have been great advancements achieved in conventional treatments, such as chemotherapy and radiation; however, these treatments frequently come with serious adverse effects and limited efficacy against certain types of tumors. In the relentless pursuit of more targeted and effective therapies, nanorobotics has emerged as a promising frontier. This article explores the potential of nanorobots in revolutionizing cancer treatment, drawing …
Published in International Journal of Nanomaterials and Nanostructures · Vol. 11, Issue 1, 2025 · pp. 44–52 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Deep Learning for Smarter Farming: Innovations in Plant Disease Identification
Abstract: Agriculture is the backbone of global food security, yet plant diseases significantly impact crop yields and farmers' livelihoods. Traditional disease detection methods are often time-consuming and require expert intervention, making them less feasible for large-scale farming. Recent advancements in deep learning have revolutionized plant disease identification by offering automated, accurate, and efficient solutions. This article explores innovative deep learning techniques, including convolutional neural networks (CNNs) and transformer-based models, that enhance …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 27–32 Read article
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Green and Nanotechnology Approaches for the Determination of Tungsten (VI): A Modern Analytical Perspective
Abstract: The determination of tungsten (VI) has gained increasing importance due to its extensive industrial applications and growing environmental relevance. Tungsten is widely used in alloys, catalysts, electronics, and energy systems, leading to its release into environmental matrices such as water, soil, and biological systems. Accurate monitoring of tungsten at trace and ultra-trace levels is therefore essential for environmental assessment and industrial quality control. Conventional analytical techniques, including inductively coupled plasma …
Published in International Journal of Analytical and Applied Chemistry · Vol. 12, Issue 1, 2026 · pp. 26–35 Read article
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Landslide Monitoring, Detection and Warning System by Wireless Sensor Network (WSN)
Abstract: Wireless sensor network (WSN) is one of the most hopeful field and has uncountable applications in the real-time systems. Execution of WSN in real-time system for landslide detection and warning system is discussed in the present paper. Sliding of rocks and soil is called landslide. It is triggered mostly because of heavy rainfall or melting of snow and can cause loss of lives and property. Using real-time monitoring the landslide …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 3, Issue 2, 2017 · pp. 24–28 Read article
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DEVELOPING A DRIVER DROWSINESS DETECTION SYSTEM (DDDS)
Abstract: Driver drowsiness accounts for over 18% of all traffic accidents in India, making it a major contributing factor. This study proposes a real-time, edge-based Driver Drowsiness Detection System (DDDS) that detects early fatigue signs and alerts drivers prior to accidents. The system employs a multimodal, bimodule strategy. In order to track face traits such eye closure, blink rate, yawning, head position, and gaze direction, the first module uses computer vision. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 2, 2026 Read article
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SMART SURVEILLANCE: AI-DRIVEN DRIVER DROWSINESS DETECTION SYSTEM
Abstract: In this study, a real-time application for driver drowsiness detection based on machine learning and deep learning is developed. Accidents, including traffic accidents, are now a frequent cause of fatalities and injuries among people. One of the major contributing factors to traffic accidents and a significant threat to road safety is drowsy driving. As a result, there are more people dying and getting hurt every year. Serious traffic accidents have …
Published in International Journal of Computer Aided Manufacturing · Vol. 9, Issue 1, 2023 · pp. 29–35 Read article
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Using an Embedded System for Accurately Diagnosis of Bone Tumors and of Selection of the Best Treatment in Real Time
Abstract: An embedded system is the use of a combination of a programmable device and software to operate that device in order to perform a specific desired operation. The article presents a developed embedded system that combines an IR spectrophotometer and a programmable logic controller (PLC), controlledby a specially developed "Spectrum" program for accurately diagnosis of bone tumors and of selection of the optimal treatment for the detected disease in real …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 7, Issue 2, 2021 · pp. 27–32 Read article
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IoT-Powered Weather Monitoring and Irrigation Automation: Transforming Modern Farming Practices
Abstract: It is proposing an IoT-based weather monitoring system. This will monitor, in real-time, the critical environmental parameters aid for farming. Soil moisture, temperature, humidity, and rainfall will be measured parameters that help optimize agricultural practices and perfect the use of water. The IoT technology will, therefore, include a microcontroller such as NodeMCU that tracks soil moisture levels and automates irrigation. If the soil moisture falls below 50%, then the programming …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Classification of power quality disturbances using advanced deep learning algorithms for Accurate and efficient electrical signal analysis
Abstract: Power systems today have to deal with more and more power quality issues (PQDs) like voltage drops, rises, harmonics, and transients because more people are using renewable energy sources and electronic devices. These problems can hurt equipment, stop services, and lower the overall reliability of power. In real-time settings, traditional detection methods often don't work as quickly or accurately as they should. This paper looks at how deep learning models, …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 2, 2026 Read article
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SOBER “An Alcohol Detection and Car Engine Locking System”"
Abstract: Drinking Driving is a major issue of road accidents all over the world; 60 plus of the accidents are caused by it. The number of deaths due to crapulous driving is assumed to be larger than imagination. The model device aims to help the stoner from driving drunk and reduce the number of accidents and cases being due to drunk driving. . Alcohol impairs drivers’ cognitive and motor functions, reducing …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 11, Issue 2, 2025 · pp. 14–19 Read article
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Biosensors for Health: A Review on Monitoring Utilizing Multifunctional Hybrid Nanomaterials
Abstract: Biosensors play a pivotal role in health monitoring, offering real-time and accurate detection of various physiological parameters crucial for disease diagnosis, management, and prevention. This review delves into the burgeoning field of biosensors, focusing specifically on the utilization of multifunctional hybrid nanomaterials for enhanced monitoring capabilities. Nanomaterials, with their unique properties and functionalities, have revolutionized biosensor technology, enabling sensitive, selective, and versatile detection platforms. Hybrid nanomaterials, formed by integrating multiple …
Published in International journal of Nanobiotechnology · Vol. 9, Issue 2, 2023 · pp. 31–36 Read article
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Review and Analysis of Fault Detection in Self-Healing Hardware System
Abstract: Self-healing hardware systems represent a transformative advancement in fault tolerance, enabling devices to autonomously detect, diagnose, and recover from malfunctions to ensure continuous and reliable operation. This paper explores the critical role of fault detection techniques in self-healing systems, focusing on methods such as built-in self-test (BIST), redundancy, and machine learning-based approaches. These techniques facilitate proactive and real-time fault resolution, addressing the limitations of traditional reactive strategies. The study highlights …
Published in International Journal of Analog Integrated Circuits · Vol. 11, Issue 1, 2025 · pp. 11–15 Read article
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Anomaly Detection Network for Surveillance Video
Abstract: Anomaly Activity is the prediction of a suspicious activity from a picture or video. This project would include using neural networks to detect suspicious human activity from real-time CCTV video. Human Anomaly Activity is a central issue in computer vision that has been researched for over 15 years. It is significant due to the large number of applications that can benefit from Activity detection. Human pose estimation, for example, is …
Published in International Journal of Software Computing and Testing · Vol. 7, Issue 2, 2021 · pp. 13–20 Read article
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CyberSentinel: A Proposed Hybrid AI Framework for Real-Time Cyber Threat Intelligence
Abstract: Modern cyberattacks have grown far more sophisticated, frequent, and fast-moving than the signature-based intrusion detection systems many organizations still rely on. This paper proposes CyberSentinel, a hybrid artificial intelligence framework for real-time cyber threat intelligence (CTI) that combines three complementary techniques into a single detection pipeline: a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) module for network traffic anomaly detection, a Random Forest ensemble for structured log classification, and a transformer-based …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article