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971 articles for “Pre-detection”
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Real Time Alcohol Detection with Accident Prevention System Using Arduino
Abstract: The aim of our research work is to present a project designed to make human driving safer and to significantly reduce road accidents caused by drunk driving. This project integrates an MQ3 alcohol sensor with an Arduino-based system using the ATmega328 processor, which offers enhanced functionality compared to conventional microcontrollers. The MQ3 sensor is capable of detecting alcohol content in a person’s breath and has a sensitivity range of approximately …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 19–26 Read article
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Nanotechnology-Enhanced Wearable Biosensors for Liver Disease Detection: Integration with AI for Predictive Analytics
Abstract: The worldwide health burden of liver diseases is substantial, and effective treatment and management depend heavily on early detection. This study investigates the integration of nanotechnology-enhanced wearable biosensors with artificial intelligence (AI) techniques for predictive analytics in liver disease detection. The construction of extremely selective and sensitive biosensors that can identify a variety of biomarkers linked to liver illnesses has been made possible via nanotechnology. These nanotechnology-based biosensors can be …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 1, 2024 · pp. 22–36 Read article
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Room Light Controller with Bidirectional Visitor Counter
Abstract: With the speed at which technology is developing today, automation is essential for increasing productivity, preserving energy, and enhancing consumer ease. The concept and implementation of an automatic room light controller with a bidirectional visitor counter are presented in this study. By detecting the presence and quantity of people in a room, the device is designed to automatically adjust the lighting, cutting down on wasteful electricity use. Pairs of Infrared …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 33–37 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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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: Growing healthy and productive crops is crucial in the global battle for food security. To minimize crop losses and apply timely control measures, early and precise diagnosis of plant diseases is essential. Conventional illness detection techniques are subjective, labor-intensive, and complicated; they frequently rely on eye inspection. The TensorFlow and OpenCV libraries are used in this study to explore the use of Convolutional Neural Networks (CNNs) for plant disease discovery. …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 31–38 Read article
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IoT-Based Industrial Safety Management Systems
Abstract: The integration of the Internet of Things (IoT) in industrial safety management has transformed workplace safety by enabling real-time monitoring, predictive analytics, and automated hazard mitigation. IoT-Based Industrial Safety Management Systems utilize interconnected sensors, wearable devices, and intelligent analytics platforms to proactively detect and respond to potential risks in high-risk environments such as manufacturing, oil and gas, and construction. These systems continuously monitor critical safety parameters, including temperature, pressure, gas …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 18–22 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Detectiverse: Advancing Supply Chain Efficiency with AI-Enhanced Screw Counting
Abstract: Accurate screw counting is essential in the manufacturing sector to ensure efficient inventory management and maintain quality control standards. The current manual counting method is prone to errors and lacks the ability to identify the source of missing screws. To address this challenge, we propose implementing an automated screw counting system at Indo Metal Tech in Ambattur, Chennai. This system would utilize advanced image processing and machine learning algorithms to …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 21–26 Read article
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A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Implementation of Anticipating Rainfall Using Machine Learning
Abstract: Rainfall forecasting is crucial for many aspects of our national economy and should help prevent major seasonal droughts. Since agriculture is a beloved profession in many states, some Asian countries are economically hooked to decline. Previous precipitation info is beneficial. Farmers are cancerous in managing their crops, resulting in economic progress for the country. downfall prediction is hard for earth science scientists because of unordering time and unordered quantity of …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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Classification of Fruits Based on Quality Using Artificial Intelligence
Abstract: The visual inspection method for fruit grading is prone to judgment distortion among different individuals. There is a demand for an automated fruit classification machine to replace labor-intensive processes with an intelligent system for fruit quality classification. This study proposes a practical real-time fruit quality classification system that classifies the fruit’s appearance in order to decrease human effort costs in the fruit industry. For the sorting and classification of fruits, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 23–30 Read article
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Sensor Guard: Thermal Sensor System for Lion Detection and Collision Prevention
Abstract: This paper presents a novel system that utilizes thermal imaging and CCTV cameras integrated with sensors to detect heat sources, specifically focusing on the detection of lions near railway tracks to prevent collisions. The system employs infrared thermal imaging to identify heat signatures of animals, particularly lions, that may create risk to his/her life. By combining thermal sensors and machine learning algorithms, the system is capable of accurately the heat …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 21–28 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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A Security Investigation Survey of Ransomware Detection and Avoidance Strategies for IoT Networks
Abstract: The internet of things (IoT) refers to the interconnection of a large number of distinct physical objects, which in turn makes possible a variety of services and applications. Because the IoT sector is developing at such a rapid rate, ensuring its safety ought to be a high concern. At this time, ransomware attacks constitute the biggest danger to IoT posed by cyberattacks. Ransomware is software that blocks access to or …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 14–23 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
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Enhancing Credit Card Fraud Detection Using Device Fingerprinting and Behavioral Biometrics
Abstract: Credit card fraud is a growing global concern, with financial losses projected to reach $ 43.47 billion by 2028. Credit card fraud poses a major challenge in the financial industry, resulting in substantial financial losses and security risks. This research introduces a Machine Learning-based Credit Card Fraud Detection System designed to improve the accuracy of fraud identification. Due to the imbalanced nature of fraud datasets, SMOTE (Synthetic Minority Over-sampling Technique) …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 40–50 Read article
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Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
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Effectiveness of Public Health Campaigns in Reducing Oral Cancer Incidence in Urban Maharashtra
Abstract: Introduction: Oral cancer is a major public health problem in urban Maharashtra which can be attributed to high consumption of tobacco, late presentation, and poor awareness. To tackle these issues, public health campaigns have been established to encourage early diagnosis, lifestyle modification, and availability of health resources. This study assesses the impact of these campaigns on the reduction of oral cancer incidence and awareness level in the population. Methods: This …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Enhancing Road Safety: A Smart Alcohol and Vehicle Accident Detection System with GPS and GSM Integration
Abstract: This work introduces a cutting-edge system designed to bolster road safety through the integration of advanced technology. The "Enhancing Road Safety" project focuses on the development and implementation of a smart alcohol and vehicle accident detection system, enriched by the integration of GPS and GSM functionalities. The system incorporates a range of sensors, including the MQ3 gas sensor for alcohol detection, GPS module for precise location tracking, and various other …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 28–45 Read article