Search
532 articles for “detection methods”
-
Autonomous Snake Detection and Catching System for Household Safety After Calamities
Abstract: Autonomous Snake Detection and Catching Robot for household Safety after Calamities is a robot to protect house premises from the intrusion of snakes which is a major issue specially after calamities. During floods many incidents of snake encounters and bites were reported in numerous residential areas. According to disaster management experts, the possibility of flood in Kerala still remains and it can cause major impacts in future. Conventional methods for …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 1–5 Read article
-
AccuPark: Intelligent Parking Using Wheel Detection
Abstract: Nowadays Due to rapid urbanization and the increasing number of vehicles in India, major traffic problems have emerged in cities. The lack of parking spots is one of the main causes. Even when parking spaces are available, they are often not properly managed. Additionally, improper and unorganized parking by individuals leads to inefficient use of available space, further worsening traffic congestion as people tend to park their vehicles anywhere. This …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
-
AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article
-
A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
-
AutoGen Bike: A Self-Sustaining Smart Electric Bike with Integrated AI Safety Systems
Abstract: This is the paper which gives the information about the self-sustaining electric bike. This also tells the idea about how energy is produced during its usage. The “Auto gen bike” is the most useful aspect that can change the future of the electric bikes. This also helps in the conservation of natural resources and nature. This also helps in the accidents happening to the two-wheel vehicle. This is achieved by …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 41–49 Read article
-
Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
-
AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
-
The Heart of Charani Poetry: An AI Interpretation of Emotional Resonance
Abstract: Poetry has long been a means of expressing emotions and ideas, yet understanding the emotional depth within poems can be challenging using traditional computer-based tools. This study explores the emotions embedded in Charani poems, an important genre in Indian literature, through the lens of their distinctive poetic style. The primary objective is to develop a novel method of analyzing emotions in Charani poetry, contributing to the broader field of emotion …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 34–39 Read article
-
Xypher Bot: Autonomous Surveying Robot
Abstract: Xypher Bot is a fully autonomous robot built to carry out tasks like height measurement, estimating distance, and detecting objects. It uses affordable and easily available components such as the MPU6050 sensor, ultrasonic sensors, and a laser pointer. By using simple trigonometry, the bot can measure object height with good accuracy. The top part of the bot, which is responsible for height measurement, has already been built and tested. The …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 49–62 Read article
-
Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
-
A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
-
Avian Echoes: Convolutional Neural Network for Bird Vocalization Detection
Abstract: Bird species identification is a complex task within ornithology that demands advanced technological solutions. This research presents an approach leveraging Convolutional Neural Networks (CNNs) for bird species recognition based on identification of bird sound, each employing unique datasets and methodologies. The objective involves a two-stage identification process, beginning with the construction of an ideal dataset. The crucial step involves converting 1D audio waveforms to 2D spectrograms, enhancing CNNs' ability to …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 26–37 Read article
-
A Study to Assess the Impact of Physical Health Problems and Coping Strategies Among Post-COVID-19 Patients in Selected Rural Areas
Abstract: Introduction: COVID-19, an infectious illness, stems from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and was initially detected in Wuhan, China, in December 2019. Its rapid transmission has triggered a global pandemic, affecting populations across the globe. Materials and method: A descriptive study design is used in the research. The research took place within a rural community setting. The population consists of post-COVID-19 patients living in rural community areas. …
Published in Journal of Nursing Science & Practice · Vol. 14, Issue 3, 2024 · pp. 11–16 Read article
-
Literature Review On Nanotechnology In Dentistry
Abstract: Nanotechnology is a relatively new field in dentistry that utilizes nanomaterials, nanorobots, and nanotechnology for diagnosing, treating, and preventing dental diseases. Nanotechnology has revolutionized various fields of dentistry, offering innovative solutions that enhance patient care, improve treatment outcomes, and contribute to the overall advancement of dental science. This cutting-edge technology has found applications in several areas, including restorative dentistry, dental implants, early cancer diagnosis, dental hypersensitivity, and pain management, among …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 · pp. 19–23 Read article
-
A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
-
Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
-
A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
-
Enhanced Diabetes Prediction: A Comparative Study of Machine Learning Models
Abstract: Excessively high blood glucose levels lead to diabetes, a condition that can be better managed with early detection, resulting in a longer life and improved health. Machine learning models are essential tools in diagnosing diabetes, especially when trained on appropriate and relevant datasets. In this study, a combination of ensemble methods and nine distinct machine learning algorithms were utilized to develop a predictive model for diabetes diagnosis based on a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
-
Unraveling Metagenomics: A Comprehensive Diagnostic Approach for COVID-19
Abstract: The COVID-19 pandemic has brought attention to the need for rapid, accurate, and scalable diagnostic techniques. Metagenomics, a powerful technique that enables the comprehensive analysis of genetic material from complex microbial communities, has emerged as a promising diagnostic approach for COVID-19. This article elucidates the principles of metagenomic sequencing, highlighting its ability to detect viral RNA directly from clinical samples without prior knowledge of the pathogen. Furthermore, we discuss the …
Published in International Journal of Tropical Medicines · Vol. 1, Issue 2, 2024 · pp. 19–28 Read article
-
Optical Image Sensing and Analysis of Iron Ore Pellets: A Machine Learning Approach
Abstract: The present work is aimed to improve quality control in steel production using SEM imaging and machine learning. High-resolution SEM images of iron ore pellets, primarily composed of hematite and magnetite, are analyzed to understand their microstructural features, which significantly impact pellet performance during reduction processes. Traditional microstructure analysis is manual, time- consuming, and prone to inconsistencies. This study proposes an automated approach using K-Means Clustering, Canny Edge Detection, DBSCAN, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 7–18 Read article