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508 articles for “real-time detection”
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Smart Weather Monitoring System Using ESP32 and IoT
Abstract: The increasing unpredictability of climate conditions necessitates an efficient and real-time weather monitoring system. The following paper describes an IoT weather monitoring system using the ESP32 microcontroller, connected to various environmental sensors to gather and process atmospheric information. The system uses a DHT11 sensor to measure temperature and humidity, an MQ135 gas sensor for measuring air quality, and a PM2.5 sensor to measure the level of particulate matter. The ESP32 …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 2, 2025 · pp. 25–36 Read article
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Advanced Digital Twin and AI Integration for Real-Time Optimization in Polymer Production
Abstract: The integration of Internet of Things (IoT) with Artificial Intelligence (AI) technologies opens up considerable avenues for reshaping polymer manufacturing by improving operational effectiveness, securing exceptional product standards, and advancing sustainability in the environment. This academic manuscript delineates an advanced framework that integrates IoT and AI with synergistic technologies, including blockchain, edge computing, and digital twin methodologies, to revolutionize polymer manufacturing processes. The proposed architecture utilizes IoT sensors for the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 81–89 Read article
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Simulation and Experimental Analysis of Abuse Testing for Prediction of Life Cycle for Lithium Ion Battery Cell and Pack Level
Abstract: Lithium-ion batteries play a crucial role in contemporary technology, serving as the power source for everything from consumer gadgets to electric vehicles. However, their safety and longevity are significant influenced by the reperformance under extreme conditions, commonly referred to as ab use testing .This paper explores the simulation and analysis of ab use testing and life cycle prediction for lithium-ion batteries at both the cell and pack levels. Abuse testing …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 2, 2024 · pp. 1–24 Read article
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Modern Chemistry & Chemical Technology in Sensor Formation
Abstract: The field of sensor formation stands at the vibrant intersection of modern chemistry and chemical technology, driven by an insatiable demand for precise, rapid, and sensitive detection across myriad applications. This paper explores the foundational and transformative role these disciplines play in engineering next-generation sensing platforms. Modern chemistry, through its atomic-level precision in synthesizing novel responsive materials – ranging from advanced polymers and supramolecular architectures to cutting-edge nanomaterials like graphene, …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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Database-Driven Energy Management in Electric Vehicles
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Smart Bionic Hand: Combining Hardware and AI For Adaptive Prosthetic Functionality
Abstract: This research paper presents the development and integration of a bionic arm that leverages both hardware components and artificial intelligence (AI) models for enhanced functionality and user interaction. The hardware design includes key components such as servo motors, an Arduino UNO microcontroller, electromyography (EMG) sensors, and a lithium-ion battery. The EMG sensors detect muscle signals, which serve as inputs for controlling the arm's movements, while the servo motors are responsible …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 1–7 Read article
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Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling
Abstract: This project is the development of an Automated Guided Vehicle (AGV) system that has been developed to handle materials in the high-accuracy, reliability, and efficiency in industrial settings. The AGV is a combination of a blend of advanced technologies including sensor fusion, real-time path planning, and AI-based navigation to allow smooth and intelligent operation with minimal human intervention. The vehicle is able to efficiently identify, and evade obstacles by using …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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NutriHeart with Chatbot
Abstract: Heart disease stands as one of the world's principal reasons for human deaths since it causes major preventable fatalities each year. Healthcare institutions currently explore machine learning (ML) integration for establishing new approaches toward predicting, and acting ahead of healthcare developments. NutriHeart presents an AI-based platform that accomplishes cardiovascular risk detection early and extends heart wellness by delivering customized nutritional and lifestyle recommendations. Using Support Vector Machines (SVM) along with …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 22–34 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Artificial Intelligence in Diagnostics: Advancements, Challenges, and Future Prospects
Abstract: AI is changing (and will change) healthcare as we know it, and diagnostics might be the specialty that feels the most discomfort. Artificial intelligence-based analytical systems are facilitating the detection, diagnosis, and treatment of a variety of diseases, with better accuracy, speed, and results. Now, this abstract investigates the role of AI in diagnostics, scouring its elements, landmark techniques, transformative impact and future overview. This article explains AI and discusses …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 8–17 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Live Integrated Facial Observation (L.I.F.O.)
Abstract: A human face is the most influential part of humans that can uniquely identify a person. Using all the facial characteristics as biometric, the LIFO system can be applicable in many different ways. Like in everyday life, the most mandatory task in any organization is attendance marking. Earlier, people used to mark their presence using paperwork but now along with the advancement of technology, this system has also changed and …
Published in Journal of Advancements in Robotics Read article
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Blockchain-Enabled Secure Wireless Communication IoT Networks
Abstract: Cloud-native environments with their distributed environments and transient workloads raise the intrinsic problem of traditional intrusion detection and response systems to unprecedented levels. Modern cloud platforms have rapid elasticity, microservice orientation, and dynamic scaling, which usually exceed the range of centralized security services, contributing to the problem of slower threat detection and a poor ability to contain the threat. The proliferation of the Internet of Things (IoT) gadgets across different …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 10–14 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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A Comprehensive Survey on IoT-Enabled and Hand Gesture Controlled Robotic Arm Using Blynk IoT and OpenCV
Abstract: This venture presents an IoT-enabled and hand gesture-managed robot arm that operates in three distinct modes: automated control, IoT-based control via the Blynk app, and gesture-based control using OpenCV. The gadget integrates a NodeMCU microcontroller for wireless verbal exchange and management, with MQTT protocol enabling real-time messaging among the devices. In automated mode, the robotic arm plays predefined tasks autonomously. In IoT mode, users can remotely manage the arm using …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 35–40 Read article
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ExploroBot: A Versatile Robotic Explorer
Abstract: ExploroBot: A versatile robotic explorer is a cutting-edge robotic platform designed for exploration and surveillance applications. Equipped with six battery-operated motors for mobility and an Arduino UNO microcontroller as its brain, the rover integrates ultrasonic sensors and two ESP32 CAM modules for obstacle avoidance and live footage streaming. With precise control mechanisms and advanced sensor technologies, ExploroBot: A versatile robotic explorer offers a versatile solution for navigating complex environments while …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Everlasting Life Achieved Through Technology in AI
Abstract: The concept of immortality Life is a philosophical idea that states life is limitless and does not stop with death, it exists infinitely. In our Sanskrit scriptures and Santana dharma teach us that there is a life of beginning and an end, which are referred to as birth and death but our souls do not perish, instead, they switch bodies. In this scenario, our memories have evaporated to protect our …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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Human Skin Abnormality Detection with Process Similarity Criteria Fit Machine Learning Method
Abstract: This method presents a machine learning method that satisfies the defined conditions for healthy waterside beach activities. The boundary conditions of the normal and abnormal radiation spaces were formulated. The objectives of using a Regression Polynomial with Process Similarity Criteria Fit for skin temperature prediction are justified by the analysis of the existing analytical and machine learning approaches. An algorithm for skin temperature prediction using the theories of similarity criteria …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 17–24 Read article