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334 articles for “Detection”
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Efficient Fault Detection in Power Transmission: A Review of Three-Phase Line Fault Detection with Hybrid Energy using MATLAB
Abstract: In urban regions, the density of power demand has significantly increased recently. Large-scale subterranean power cable installations are beginning to take the place of overhead transmission lines everywhere in the world because of environmental concerns in highly populated areas. The present project's primary objective is to use MATLAB to create a simulation model that includes 3ph symmetrical and unsymmetrical defects. Some have proven to be effective in detecting errors while …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 42–47 Read article
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Natural Language Processing-Based Plagiarism Detector
Abstract: Plagiarism is the act of taking another's work and claiming it as his/her own without giving the credit. Plagiarism is a grave concern in many fields like education, literature, business, etc. The project aims for text and image plagiarism detection employed by a web application containing four modules. Text plagiarism is detected when the input is either text or PDF. For PDF, the text extraction is done from the PDF …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 27–35 Read article
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Comprehensive Comparative Analysis of Intrusion Detection Systems: Evaluating Signature Based, Anomaly Based, and Hybrid Approaches
Abstract: In the fast-changing world of cybersecurity, Intrusion Detection Systems (IDS) play a vital role in protecting digital resources. This study offers an in-depth comparative analysis to evaluate the efficiency and performance of different IDS solutions. It examines a variety of both commercial and opensource platforms, encompassing signature based, anomaly based, and hybrid models, to assess their effectiveness in identifying and responding to a wide range of cyber threats. Methodologies for …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 39–44 Read article
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AI-Powered Fire Detection System for Accurate and Timely Emergency Response
Abstract: AI-based fire detection system leverages deep learning and Open CV. Issues with conventional fire detection techniques include false alarms and expense. The proposed system uses deep learning for real-time fire detection in videos, enhancing accuracy and adaptability. OpenCV aids in crowd counting, improving situational awareness during emergencies. This innovation promises to revolutionize fire safety by offering timely and precise detection, potentially saving lives and property. Additionally, by counting crowds, the …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 30–36 Read article
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Real-time Mask Detector (Monitoring COVID-19)
Abstract: This study presents the development and implementation of a real-time mask detection system designed to monitor and enforce mask-wearing policies during the COVID-19 pandemic. Utilizing a convolutional neural network (CNN) and a dataset consisting of annotated images, our system can accurately detect the presence or absence of masks on individuals in various environments. The proposed system achieves high accuracy and can be deployed in public spaces to help mitigate the …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 42–49 Read article
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Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning
Abstract: This study focuses on the crucial problem of non-adherence to traffic regulations, particularly with the compulsory use of helmets by motorcyclists. Motorcycle accidents have a greater mortality rate compared to other types of accidents, indicating a need for a more effective enforcement strategy. Current procedures depend on traditional techniques where traffic officers manually observe traffic rule infractions through patrols and monitoring CCTVs, requiring substantial labor and time resources. The inherent …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 9–18 Read article
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Intrusion Eye Detector
Abstract: Uncertainty about security risks and illegal access are becoming more prevalent in a variety of settings, such as private homes, business buildings, and critical government buildings. Conventional security systems, which may not offer real-time warnings or prompt reactions, frequently rely on passive monitoring, including CCTV cameras and motion sensors. Artificial intelligence (AI) and computer vision-based intelligent systems are becoming more and more popular as a means of improving security and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 28–32 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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Fire Detection System
Abstract: Fire detection systems are engineered to identify the presence of fire or smoke and notify individuals of possible hazards. These systems employ a range of sensors, such as smoke detectors, heat detectors, flame detectors, and advanced algorithms, to recognize indications of fire inception or spread. When a fire is detected, alarms are activated, facilitating swift responses to minimize dangers and forestall fire incidents.
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 2, 2023 · pp. 29–38 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article
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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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Enhancing Road Safety: A System for Vehicular Accident Detection, Prevention, and Rescue Alerts
Abstract: The Vehicular Accident Detection, Prevention, and Rescue Alert System is a comprehensive solution aimed at bolstering road safety by integrating multiple advanced technologies. It merges drowsiness detection, alcohol level monitoring, and instant emergency alerts to mitigate accidents and expedite rescue efforts. Modern computer vision and machine learning techniques are used by the Drowsiness Detection Alarm to track driver conduct and spot drowsiness indicators. Upon detecting drowsiness, an immediate alarm is …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 7–11 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 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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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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IoT-Enabled Multi-Sensor Accident Detection and Automatic Rescue Alert System
Abstract: Road accidents and vehicle instability caused by skidding, engine overheating, and improper braking behavior remain major concerns in modern transportation systems. This project presents an intelligent vehicle safety and accident detection system that integrates multiple sensors and control logic to enhance driving safety and reduce accident severity. A vibration sensor is employed to detect collision or impact events and accurately identify vehicle accidents. An accelerometer sensor is used for real-time …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 1, 2026 · pp. 9–19 Read article
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Multi-Sensor System for Underwater Pothole Detection to Enhance Road Safety During Monsoon Seasons
Abstract: Monsoon seasons across India and similar tropical regions severely compromise road safety by causing water accumulation that conceals dangerous potholes beneath stagnant pools, leading to frequent vehicle damage, tire punctures, and fatal accidents. Traditional detection methods relying on smartphone accelerometers, ultrasonic sensors, or machine vision fail under flooded conditions due to acoustic signal reflection at water surfaces and optical distortions from glare and turbidity. This research proposes an innovative multi-sensor …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article