Search
971 articles for “Pre-detection”
-
AI and Sensor Systems Revolutionizing Intoxication and Smoking Pre- Detection
Abstract: In an increasingly interconnected and safety-conscious world, the pervasive issues of intoxication and uncontrolled smoking continue to pose significant threats to public health, safety, and productivity. From impaired driving incidents to workplace accidents, and from chronic health conditions linked to smoking to the risk of fires, the societal and economic costs are staggering. However, a new frontier in preventative technology is emerging: sophisticated AI and sensor-based systems designed for the …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 3, 2025 · pp. 14–25 Read article
-
Sensor and AI based Pre-Detection Systems Transfiguring Intoxication & Smoking
Abstract: The ubiquitous problems of drunkenness and uncontrolled smoking continue to pose substantial hazards to public health, safety, and productivity in a world that is becoming more linked and protective of its personal safety. The costs to society and the economy are substantial, and they range from automobile accidents caused by impaired driving to accidents that occur in the workplace, and from chronic health disorders that are connected to smoking to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 37–50 Read article
-
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
-
Cyberattack Detection and Prevention Using Empowering AI Tools
Abstract: With more organizations entering the digital transformation sphere, the opportunities and risks in cyberspace have increased and gone up in levels of sophistication and occurrence. Many of these developments are attributed to the limits of existing cyber security solutions where addressing new threats requires advanced detection technologies and techniques. Cyber threats gained a new meaning and dimension with artificial intelligence (AI) coming into play in ways that supplement security systems …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
-
Advanced AI based Energy Monitoring and Demand Prediction with Theft Detection
Abstract: This paper presents a study on an AI-based energy management system, which is designed for real-time monitoring of energy consumption for theft detection and energy demand prediction. Our energy management system has voltage and current sensors for energy consumption measurement and provides real- time data on voltage (V), current (mA), and energy units. We have implemented Machine Learning algorithm SVM to improve the process of theft detection by identifying anomalies …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 Read article
-
DVT in Athletes: A Physiotherapist’s Approach to Prevention, Early Detection, and Rehabilitation
Abstract: Deep vein thrombosis (DVT) is a serious medical condition where blood clots develop in the deep veins, most often in the lower limbs. While it is traditionally associated with immobility, athletes are also at risk due to factors like prolonged travel, injuries, dehydration, and genetic predispositions. This paper explores the role of physiotherapists in preventing, detecting, and rehabilitating DVT in athletes. Preventive strategies include promoting hydration, active recovery, circulatory exercises, …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 1, 2025 · pp. 11–16 Read article
-
Transfer Learning Based High-Precision Multi-Class Object Detection for Real-Time UAV Autonomous Landing via YOLOv8l in Unstructured Scenarios
Abstract: A significant challenge for autonomous drone landings in unstructured environments is that of reliably detecting and identifying objects in real-time to ensure safety and accuracy of the landing area. This paper presents a well-founded method for solving this problem using the YOLOv8l object detection framework to detect landing zones, obstacles and people in the relevant vicinity of the landing area. The dataset used for the training of the model contained …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
-
Fingerprint Liveliness Detection in Biometric Authentication: A Survey
Abstract: In the world of cyberspace, presentation attacks (PA) on biometric systems have grown to be a major worry. The review of the literature suggests that these systems are more susceptible to spoofing or presentation attacks (PAs), which frequently cause the authentication or identification system to completely fail. To combat against presentation attacks (PAs), the presentation attack detection (PAD) or anti spoofing methods have been developed to validate the liveness of …
Published in Journal Of Network security Read article
-
Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
-
Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
-
Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
-
AI-Powered ECG Prediction System for Detecting Cardiovascular Disease
Abstract: The proposed AI-powered CardioSmart Analyzer, an electrocardiogram (ECG) prediction system, presents an innovative and scientifically rigorous approach to the real-time automated analysis of ECG signals for diagnosing various heart conditions. This research focused on building a predictive model to identify cardiovascular diseases (CVD) using ECG data. A dataset comprising 2,840 12-lead ECG recordings was gathered from medical facilities in Gazipur, Bangladesh, over the period from June to August 2024. The …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 51–85 Read article
-
Enhancing Wildlife Tourism Management Using Deep Learning and Particle Swarm Optimization (PSO) for Animal Detection in Wildlife Sanctuaries
Abstract: Wildlife tourism is one of the most thriving sectors, faced with huge challenges in terms of safeguarding protected areas. As demand for wildlife experiences accelerates, it becomes necessary to find efficient measures that are friendly to conservation. The use of these advanced techniques in this field such as YOLO and PSO algorithm presents a new dimension on managing wildlife tourism. To harness the abilities of these techniques, this research centers …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 41–50 Read article
-
Phishing Attack, Its Detections and Prevention Techniques
Abstract: The relentless surge of cyber threats represents a pressing challenge to global security and individual privacy. Among these, phishing attacks remain a particularly pernicious form of cybercrime. This study provides a comprehensive review of phishing attacks, their evolution, methodologies, impacts, and countermeasures. The methods of perpetrating phishing attacks have grown in sophistication, extending beyond the common email phishing to include spear phishing, whaling, clone phishing, vishing, smishing, and search engine …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 13–25 Read article
-
Fire Detection And Prevention in Electric Vehicles (Ev)
Abstract: This abstract presents a novel approach to fire prevention and detection in electric vehicles (EVs), highlighting the challenges posed by their high-voltage battery systems. The proposed system integrates advanced fire detection technology, such as infrared sensors and thermal imaging, with automatic gas release mechanisms triggered upon fire detection to manage the temperature of the electric engine and suppress fires effectively. The chosen gas serves a dual purpose of reducing oxygen …
Published in Journal of Automobile Engineering and Applications · Vol. 11, Issue 1, 2024 · pp. 26–31 Read article
-
Computer Lab Automation System
Abstract: This is an overview of an innovative computer lab system designed to enhance energy efficiency by automatically controlling lights and fans based on human presence detection. The system employs a combination of sensors, software, and smart controls to optimize energy consumption in computer labs, a sustainable and eco-friendly environment. The proposed computer lab system integrates motion sensors strategically placed throughout the lab, a real-time monitoring of human presence. When the …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 8–19 Read article
-
Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 Read article
-
Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
-
Ransomware Detection and Prevention Using Honeypot
Abstract: The significance of network security and explores the details of ransomware attacks, highlighting the crucial parameters essential to fortifying defences against this pernicious cyber threat. Network security involves safeguarding computer networks against unauthorized access, data breaches, and cyberattacks. Ransomware attack, a specific type of cyberattack, entail malicious software encrypting a computer system, making them unavailable to use in return attacker asks for ransom in form of cryptocurrency like Bitcoin or …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 1, 2024 · pp. 8–13 Read article
-
A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article