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171 articles for “detection and intervention”
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Self-Navigating Rover for Real Time Mapping and Disaster Management
Abstract: This paper presents the development of an autonomous rover designed for mapping and object detection in challenging terrains. The rover integrates a 6-wheel rocker-bogie mechanism for enhanced mobility and stability, making it suitable for rugged and uneven environments. Key components include an Arduino Uno for control operations, a Camera module for real-time visual data capture and object detection, and a LiDAR for precise distance measurement and spatial mapping. The system …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 23–33 Read article
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Veterinary Immunology in Zoonotic Disease Control
Abstract: Zoonotic diseases, which are transmissible between animals and humans, pose a significant threat to global public health, food security, and economic stability. Veterinary immunology plays a pivotal role in understanding host–pathogen interactions, developing preventive strategies, and mitigating the impact of these diseases. Animals serve as reservoirs for a variety of pathogens, including viruses, bacteria, and fungi, which can persist asymptomatically or cause clinical disease. Understanding the immune mechanisms in both …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 3, 2025 · pp. 36–43 Read article
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Epilert: Epilepsy Tracker and Detector
Abstract: Epilepsy, affecting over 50 million individuals worldwide, necessitates innovative solutions for effective monitoring and intervention. Current systems face challenges such as inaccuracy, limited accessibility, and discomfort, leaving patients and caregivers vulnerable. Epilert, a wearable device, addresses these gaps by employing advanced sensors and machine-learning algorithms for real-time epilepsy detection and monitoring. The device integrates electromyography (EMG) and motion sensors to capture and analyze physiological and movement data. Preprocessing techniques ensure …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Collaborative Care for Diabetic Retinopathy: Integrating Artificial Intelligence and Clinical Pharmacy Services - A Comprehensive Review
Abstract: Background: Diabetic retinopathy (DR) remains the leading cause of blindness among working-age adults globally, affecting approximately 103 million people worldwide. The integration of artificial intelligence (AI) technologies with clinical pharmacy services presents unprecedented opportunities to enhance screening, diagnosis, and management of DR through collaborative care models. Objective: This comprehensive review examines the current landscape of collaborative care approaches for diabetic retinopathy management, focusing on the integration of AI-powered diagnostic tools …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 118–128 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
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Heart Attack Prediction Using Machine Learning
Abstract: Heart attacks have become a prevalent and serious condition in recent years due to a variety of causes. Numerous variables, including age, sex, fat, and others, can be used to predict it. In the current study, it was found that a data set with 13 parameters and 302 distinct data values, collected from a Kaggle dataset to assess patient condition, was covered. This article delves into the application of machine …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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IoT-Based Public Toilet Monitoring System
Abstract: Public restroom maintenance is critical to urban hygiene and requires good resource management to secure hygiene, sustainability, and costs. This project presents the design and implementation of a real-time monitoring system for public restrooms, including IoT-based sensors, to measure key environmental factors, such as ammonia concentration, ambient light, and water level. The system can continuously monitor ammonia concentrations to detect poor air quality, opening an intervention window to remedy the …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 15–25 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Embedded System for Rain Sensing Car Wiper
Abstract: The automatic rain wiper system aims to detect rainfall and activate windshield wipers automatically, eliminating the need for manual intervention by the driver. For over a century, the driver has been the one operating the windshield wiper. The wiper should be turned on when the driver feels that driving the vehicle is difficult and that better vision is necessary. On the other hand, since the driver must concentrate solely on …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 1, 2024 Read article
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Advances in Nanotechnology-based Biosensors: Enhancing Sensitivity and Specificity in Biomedical Diagnostics
Abstract: This study provides an in-depth exploration of the rapidly evolving field of nanotechnology-based biosensors, emphasizing their significant impact on biomedical diagnostics. The integration of cutting-edge nanomaterials, including nanoparticles, nanowires, and quantum dots, has catapulted biosensing technology to new heights, yielding unprecedented gains in sensitivity and specificity, and revolutionizing the detection of biomolecules. The study highlights various types of nanobiosensors, including optical, electrochemical, and magnetic, each offering unique advantages for detecting …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 2, 2024 · pp. 26–32 Read article
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Digital Health Interventions in Cardiovascular Pharmacology: A Review
Abstract: Cardiovascular diseases (CVDs) represent a formidable global health challenge, demanding innovative strategies for timely detection, effective management, and continuous monitoring. This study delves into the transformative potential of digital health interventions (DHIs), such as telemedicine and remote monitoring, in reshaping cardiovascular care paradigms. DHIs offer unparalleled accessibility, convenience, and personalized attention, thereby promising to revolutionize traditional approaches to cardiovascular health management. One of the foremost advantages of DHIs lies in …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 14, Issue 2, 2024 · pp. 1–5 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Cardiac Structural and Functional Changes in Anaemia: A 2D Echocardiographic Study in an Indian Population
Abstract: Anemia is a widespread global health concern, particularly prevalent in developing countries, like India, where it contributes significantly to cardiovascular morbidity. This study aimed to evaluate cardiac structural and functional changes in anaemic patients using 2D echocardiography and to assess correlations between haemoglobin levels and echocardiographic parameters. A cross-sectional observational study was conducted on 125 anaemic patients (defined as haemoglobin <13 g/dL in males and <12 g/dL in females) at …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 2, 2026 · pp. 39–44 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 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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Drones in Precision Livestock Farming: Advancing Health, Welfare, and Resilience in Dairy Production Systems
Abstract: The integration of drone technology in precision livestock farming represents a transformative advancement in modern dairy production systems. Drones offer innovative solutions for monitoring, managing, and optimizing livestock health, welfare, and productivity while addressing challenges related to environmental sustainability and resource efficiency. This study explores the diverse applications of drones in dairy farming, including health monitoring, disease detection, reproductive assessment, and real-time herd tracking. By leveraging thermal imaging and advanced …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 16–25 Read article