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414 articles for “real- time analysis”
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Real-Time Analysis of E-Waste Monitoring Using Data Visualization in Power BI
Abstract: The exponential growth of electronic waste (e-waste) in India poses significant environmental and public health challenges, necessitating robust monitoring, management, and disposal strategies. This project, Real-time analysis of e-waste generated across different countries in the world and also survey report of India, seeks to provide a comprehensive assessment of e-waste production patterns, utilizing real-time data to capture dynamic shifts in waste generation and collection. By leveraging Power BI for advanced …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 1–7 Read article
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Artificial Intelligence for Real-time Water Management
Abstract: Effective water management is vital for sustainable development, requiring the strategic allocation and utilization of water resources to satisfy the diverse demands of agriculture, industry, and households. Traditional methods are increasingly inadequate due to escalating challenges from climate change and population growth, which amplify water scarcity and distribution issues. To overcome these challenges, we need innovative solutions. Artificial intelligence offers significant potential in revolutionizing realtime water management through advanced techniques …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–20 Read article
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Tank Water Quality Analysis Using Machine Learning
Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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Mood Mate: A Solid-State Edge-AI System for Real-Time Facial Emotion Recognition
Abstract: Recent progress in solid-state electronics and embedded vision systems has enabled real-time emotion-aware applications at the edge. This paper presents MoodMate, a solid-state edge-AI framework for real-time facial emotion recognition using camera-based sensing and embedded processing. The proposed system integrates a solid-state image sensor with an AI- driven emotion classification pipeline optimized for low-latency and resource-constrained environments. Intelligent, emotion-aware apps can now be deployed right at the network edge thanks …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 24–30 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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AI Voice Detection Tool
Abstract: In today’s digital era, distinguishing between AI-generated and human voices is more important than ever. This project introduces an AI-based voice detection system designed to accurately identify synthetic voices, ensuring security and authenticity across various applications like cybersecurity, media verification, and fraud prevention.Our system works by analyzing incoming audio samples and comparing them against a diverse database of both AI-generated and real human voices. Using advanced machine learning and signal …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
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An Analytical Study on Cybersecurity Threats and AI-Driven Mitigation Strategies in Next-Generation Smart Grids
Abstract: The increasing adoption of next-generation smart grids has introduced significant cybersecurity challenges due to their reliance on interconnected digital infrastructures and IoT-based control mechanisms. This study aims to analyze cybersecurity threats in smart grids and explore AI-driven mitigation strategies to enhance grid security and resilience. The research examines common cyber threats such as malware attacks, denial-of-service (DoS), data breaches, and insider threats while evaluating the effectiveness of AI-based solutions, including …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 16–25 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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AI-Powered IoT System for Early Detection and Monitoring of Livestock Health
Abstract: Protection of food production exists through livestock farming operations that advance economic global power. Continuous challenges to agricultural industry practices result in harmed animal health and enable disease spread as well as environmental threats to their welfare. Implementing current innovative solutions right away is necessary to solve these problems. The AI and IoT-based smart livestock health monitoring system functions as the fundamental development approach across this industry. The present integrated …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 1, 2025 · pp. 1–8 Read article
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Enhancing Farm Efficiency with IoT-Driven Real-Time Monitoring and Analysis
Abstract: This project proposes an Internet of Things (IoT) solution for enhancing agricultural practices by leveraging real-time data monitoring and analysis. The system utilizes NodeMCU, DHT11, pH sensor, soil moisture sensor, and an LCD display for data collection and visualization. NodeMCU facilitates internet connectivity, enabling the transmission of data to the ThingSpeak platform. Temperature and humidity are measured by the DHT11 sensor, and soil acidity is tracked by the pH sensor. …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 14, Issue 2, 2024 · pp. 9–15 Read article
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Real-time Water Quality Analysis Using Fuzzy Logic
Abstract: Nowadays the availability of safe drinking water is very difficult. In our project we are analysing water quality using different parameters like pH, turbidity, temperature and TDS for determining its safety level by monitoring the data from the readings. Moreover, we have a monitoring system for the data and also a webpage where all the data from these system is displayed. The sensors are connected to an Arduino Nano microcontroller …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 2, 2026 · pp. 01–11 Read article
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A Real-time Visualization Framework to Enhance Prompt Accuracy and Result Outcomes Based on the Number of Tokens
Abstract: In the rapidly evolving domain of artificial intelligence (AI), the efficacy of user-generated prompts has emerged as a critical factor influencing the quality of model-generated responses. Current methodologies for prompt evaluation predominantly rely on post-hoc analysis, which often leads to iterative prompting and increased computational overhead. Furthermore, the challenge of “prompt hallucinations,” where AI models produce irrelevant or nonsensical responses, persists as a significant impediment to effective AI utilization. The …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 45–53 Read article
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Wearable Devices Incorporating Nanostructured Biosensors: Enabling Real-Time Monitoring and User-Friendly Interfaces
Abstract: Wearable devices incorporating nanostructured biosensors have emerged as a revolutionary technology, enabling real-time monitoring of various physiological parameters and biomarkers. These devices leverage the unique properties of nanostructured materials, such as high surface-to-volume ratio, enhanced sensitivity, and improved electrical and optical characteristics, to achieve exceptional performance in terms of sensitivity, selectivity, and response time. This chapter explores the recent advancements in wearable devices with nanostructured biosensors, highlighting their applications in …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 1, 2024 · pp. 13–21 Read article
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Development of Web-enabled Smart Hospital Management System: Patient Data Visualization and Real-time Decision Making
Abstract: As everyone is aware, fewer people had access to healthcare services, which prevented many people from receiving the care they needed. The idea that, by WHO criteria, there should be one physician for every 1,000 patients is nearly unbelievable. Yet, India’s current ratio is a staggering 1:1445. This disparity highlights a serious gap in healthcare resources that cannot be ignored. Authors remember speaking with a friend who works in a …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
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SMART HOSPITAL MANAGEMENT SYSTEM:USING CLOUD, IOT & WEB DEVELOPMENT
Abstract: The Smart Hospital Management System (SHMS) leverages cloud computing, Internet of Things (IoT) technologies, and web development to address the inefficiencies in healthcare management, particularly in the context of the COVID-19 pandemic. With India’s doctor-to-patient ratio below WHO standards, there is a need for innovative solutions to enhance patient care and hospital resource management. This system integrates SpO2, temperature, and ECG sensors with the Raspberry Pi, enabling continuous and real-time …
Published in Journal of Telecommunication, Switching Systems and Networks Read article
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Real-time DDoS Attack Prediction in SDN Environments Using Machine Learning
Abstract: The ever-growing reliance on sdn-based services necessitates robust security measures against Distributed Denial-of-Service (DDoS) attacks that threaten service availability. This project investigates the development of a real-time prediction system for DDoS attacks in sdn environments, leveraging the power of machine learning. The proposed system employs a Decision Tree classification algorithm implemented in Python. To ensure accurate attack identification, the system meticulously addresses data preprocessing challenges inherent in network traffic datasets. …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 16–27 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