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1987 articles for “Lap Splice Detection” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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IoT Based Electricity Theft Detection System
Abstract: The proliferation of smart grids and advanced metering infrastructure has paved the way for innovative solutions to tackle the longstanding issue of electricity theft. This study presents an IoT-based electricity theft detection system that leverages real-time data analytics and machine learning algorithms to identify potential theft cases. The proposed system utilizes smart meters to collect electricity consumption data, which is then transmitted to a central server for analysis. The system …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 18–22 Read article
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Fraud Detection in Government Procurement Using Machine Learning
Abstract: Fraud represents a significant challenge in the realm of procurement, with estimates indicating that between 12 and 30% of global procurement budgets are lost to fraudulent activities (OECD, 2023). The pervasive nature of procurement fraud, which may encompass a range of deceptive practices such as bid rigging, invoice fraud, and procurement kickbacks, not only undermines the integrity of financial operations but also results in substantial losses for organizations. These losses …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 19–34 Read article
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Fire Detection and Alert System Using IoT
Abstract: The Fire Detection and Alert System Using IoT is a new solution aimed at improving fire safety in multi- floor buildings. Fires can be very dangerous, especially in crowded areas or tall buildings. When a fire breaks out, evacuating can be hard and slow. This project uses IoT technology to create a fire detection system that works fast and is easy to expand. Each floor of the building is equipped …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 15–23 Read article
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Hybrid DL-ML Approach for Android Malware Detection
Abstract: The widespread growth of Android malware has become a significant mobile security threat during the past few years thus requiring the development of strong detection solutions. The primary tool applied in this research for Android malware detection consists of app permissions. The main indicator in the dataset for identifying malicious and benign applications functions through displaying application permission information. The evaluation of particular permission relationships with malware behavior leads to …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 18–25 Read article
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Accident Avoidance and Crash Detection Using GSM and GPS
Abstract: The Accident Avoidance and Crash Detection system is designed to enhance vehicle safety by utilizing real-time accident detection, speed tracking, and automated crash prevention mechanisms integrated with GSM and GPS technologies. The system incorporates an accelerometer to identify abrupt changes in acceleration, indicating a potential collision. Upon detecting an accident, the system automatically transmits an alert message with the vehicle's GPS location to a designated mobile number using GSM technology, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 3, 2025 · pp. 01–12 Read article
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Choosing the Right Machine: A Comparative Analysis of Desktops and Laptops
Abstract: This study provides a comparative analysis of desktop and laptop computers, focusing on factors such as performance, portability, cost, and user requirements. Desktops are highlighted as the preferred option for resource-intensive tasks like gaming, video editing, and handling large-scale data because of their powerful processors, efficient cooling mechanisms, and expandability. These systems are well suited for users who prioritize high performance and the ability to upgrade components over time. On …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 41–49 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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Machine Learning for Soil Moisture Detection: Introduction, Approaches and Challenges
Abstract: The demand for agricultural is increasing day by day as the population of the world is increasing. So, it becomes necessary for us to increase the production of agricultural products. Traditional ways of agriculture cannot meet such requirements. Nowadays, machine learning based technologies are being used to develop models for agriculture. Machine learning-based applications are very fast and produce high-quality results. It includes recurrent neural networks (RNN), convolution neural networks …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 88–96 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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Random Forrest Based Man-in-the-Middle Attack Detection in Advanced Metering Infrastructure
Abstract: Advanced metering infrastructure (AMI) plays a central role in the operation of modern smart grid (SG) systems by enabling continuous, two-way communication between utility providers and consumers. Through this communication, AMI supports real-time monitoring, dynamic pricing, and efficient energy management. However, the same connectivity that makes AMI effective also increases its exposure to cyber threats. One of the most critical threats is the man-in-the-middle (MITM) attack, in which an attacker …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 1–8 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
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Earthquake Detection and Monitoring System
Abstract: Earthquakes continue to be one of the major natural hazards affecting human life and infrastructure. The development of affordable monitoring systems is essential for increasing preparedness and reducing the impact of such disasters. This work presents an Earthquake Detection and Monitoring System based on a vibration sensor and Arduino controller. The system continuously observes ground movements and evaluates the detected vibration levels against a predefined threshold. Whenever unusual vibrations are …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Real-Time Deepfake Detection in Video Conferencing Systems
Abstract: Deepfake technology presents non-exemplary threats to video conferencing platforms, enabling advanced fraud, impression and misinformation campaigns worth billions annually. Current detection methods either exhibit latencies exceeding 100ms or rely on server-side cloud processing, raising privacy concerns. This paper presents DeepConfGuard, a lightweight hybrid architecture combining MobileNetV2 for spatial feature extraction, a bidirectional LSTM with attention for temporal modelling, and EfficientNetV2 for refinement. It reaches 94.8% accuracy with 85 ms end‑to‑end …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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GHS Label Detection Using Color Segmentation
Abstract: AbstractThis research presented the Globally Harmonized System (GHS) label detection by color segmentation approach. The researcher adapts this approach for identify boundary of each color pixels in Different environment image set. Experimental result shown the detection model have high accuracy. However, the mainly cause of error processing is asymmetrical GHS label in sample image that.Keywords: Color Segmentation, Image Processing, GHS Label Detection, Computer VisionCite this ArticleSansanee Hiranchan. GHS Label Detection …
Published in Current Trends in Signal Processing · Vol. 10, Issue 2, 2020 · pp. 26–32 Read article
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Deploying Optimal Number of Sensors and Damage Detection in Structural Health Monitoring Using SEM-GA Method
Abstract: Detecting damages is the most important criterion in any engineering creation—be it a machine or a building. Among the engineering creation, civil engineering structures need a continuous monitoring to check their operations, performance and the health status of the structures. Damage detection cannot be done manually every time. Automated systems have to be developed in order to monitor the health of the structure periodically. Hence, structural health monitoring (SHM) aims …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 28–35 Read article