Search
1939 articles for “AI” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
-
OBD-II Big Data–Driven ML and AI-Based Virtual Sensing for Fuel Economy, Component Health, and Carbon Intelligence
Abstract: The rapid growth of connected vehicles has led to the large-scale availability of high-frequency On-Board Diagnostics II (OBD-II) data; however, much of this data remains underutilised, as existing studies and commercial systems typically address fuel economy, maintenance, or emissions in isolation or rely on additional physical sensors. Such fragmented and sensor-dependent approaches limit scalability and increase system cost, particularly in high-volume and resource-constrained vehicle markets. To address this gap, this …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 39–50 Read article
-
AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
-
Unveiling Bihar's Atmospheric Crisis: A Synoptic Review of PM 2.5 Dynamics, Source Attribution, and Airshed Vulnerabilities in the Eastern Indo-Gangetic Plain (Bihar)
Abstract: Bihar, situated in the pollution-trapping Indo-Gangetic Plain (IGP), faces a severe air pollution crisis characterized by annual PM2.5 concentrations of 80–100 μg m-3 exceeding WHO guidelines (5 μg m-3) and Indian NAAQS (40 μg m-3) by 4–6-fold. This review synthesizes data from CPCB/BSPCB monitoring, MODIS satellite retrievals, and peer-reviewed studies (2000–2025) to assess ambient air quality, sources, health impacts, policies, and research gaps in the state. PM2.5 and PM10 dominate, …
Published in International Journal of Pollution: Prevention & Control · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
-
Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big Data Analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support informed decision – making and superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of Big Data Analytics (BDA) within …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
-
Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
-
Leveraging AI and Machine Learning for Early Prediction and Prevention of Non- Communicable Diseases in Resource-Limited Settings
Abstract: Populations in these regions face persistent structural barriers, such as underdeveloped healthcare infrastructure, shortages of trained health professionals, and fragmented or incomplete health information systems. These limitations delay timely diagnosis, restrict access to preventive care, and compromise effective disease management. In recent years, rapid progress in artificial intelligence (AI) and machine learning (ML) has opened promising avenues to mitigate these challenges. Practical applications already emerging include mobile health platforms for …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–15 Read article
-
Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
-
The Rise of AI in E-Commerce: Transforming Shopping Experiences
Abstract: The field of e-commerce is transforming due to the integration of artificial intelligence, offering businesses fresh possibilities to enhance customer experiences, streamline operations, and foster expansion. This article explores the transformative impact of artificial intelligence (AI) on various aspects of e-commerce, including personalized shopping experiences, intelligent chatbots and virtual assistants, predictive analytics for inventory management, dynamic pricing strategies, visual search and image recognition, fraud detection, and security measures, augmented reality …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 22–26 Read article
-
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
-
AI-Powered License Plate Recognition
Abstract: With the number of cars multiplying daily, safety precautions are judged required. Automatic number plate recognition uses image processing and machine learning techniques to recognize vehicle numbers. By utilizing the vehicle number plate, the approach recommended seeks to establish a capable automated approved auto identification system. We describe an automated vehicle number detection system based on image processing and Raspberry Pi that reads license plates. In this setting, a Raspberry …
Published in Trends in Machine design · Vol. 11, Issue 1, 2024 · pp. 20–29 Read article
-
AI-Based Criminal Identification System A Breakthrough Approach
Abstract: Identifying and locating a perpetrator is a time-consuming and difficult process. The perpetrators are growing more skilled, leaving no biological evidence or fingerprint impressions at the crime scene. Using cutting-edge face recognition technology is a quick and easy solution. Through the use of linear programming, this research presents an innovative approach to classifying all face tracks collectively. In addition to the following, it incorporates: a novel method for extracting more …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 1–14 Read article
-
Quantitative Structure-activity Relationship in Computer-aided Drug Design: A Review
Abstract: Quantitative Structure-Activity Relationship stands at the forefront of Computer-Aided Drug Design, providing a systematic framework for understanding the relationship between the chemical structure of molecules and their biological activity. The present review delves into the multifaceted realm of quantitative structure-activity relationship methodologies within the landscape of drug discovery. Through an exploration of diverse quantitative structure-activity relationship models, molecular descriptors, validation techniques, and recent advancements, the present article aims to elucidate …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 55–63 Read article
-
AI-Powered Face Detection and Recognition Using Machine Learning
Abstract: These days, one of the biggest computer vision technologies is facial recognition. Face identification in computer vision, lighting position, and facial expression is always an extremely challenging issue. In real-time video pictures captured by a video camera, face recognition tracks specific objects. Put simply, it is a system tool that uses a still picture or video frame to automatically identify a person. In this research paper we use different different …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–12 Read article
-
Leveraging IoT and AI for Real-Time Monitoring and Optimization of Polymer Production Processes
Abstract: Integrating the Internet of Things (IoT) and Artificial Intelligence (AI) technology provides a transformational potential for the polymer manufacturing business, allowing for real-time monitoring and better control of production processes. This paper explores the synergistic application of IoT and AI to achieve greater efficiency, sustainability, and quality control in polymer manufacturing. IoT sensors and devices may capture massive volumes of data from different phases of the manufacturing process, delivering real-time …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1–16 Read article
-
Exploring the Evolution of Mobile Phone Detectors: From Basic Sensors to AI-Enhanced Solutions
Abstract: This work talks about the creation and plan of a portable phone locator that can discover approaching and active signals from versatile phones. This little, pocket-sized gadget can sense when a portable phone is dynamic from a separate of one and a half meters. Because of this, it can help anticipate the utilization of portable phones in places like exam corridors, private rooms, and petrol stations. It can moreover effectively …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 3, 2024 · pp. 17–23 Read article
-
Portable and User-friendly Air Watch System Based on IoT
Abstract: The internet of things (IoT) based air monitoring system is a novel approach to monitoring air quality in real time. With the increasing concerns over pollution and its impact on human health, our IoT-based air monitoring system offers a solution to gather and analyze air quality data efficiently. The system utilizes IoT devices like Node MCU and sensors like MQ135 and DTH11 to collect data such as temperature, air quality, …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 3, 2024 · pp. 19–27 Read article
-
The BambooBuddy: An AI-powered Chatbot for Enhancing Bamboo Yield in India
Abstract: Bamboo farming is essential for sustainable agriculture and environmental preservation. This project presents BambooBuddy, a chatbot developed to assist farmers and surveyors in managing bamboo-related inquiries. The system leverages a structured dataset stored in recommendations.csv to provide precise and relevant recommendations based on user queries. By utilizing the flask framework for web development and incorporating Cohere’s natural language processing capabilities, BambooBuddy facilitates seamless interaction and enhances user experience. The chatbot …
Published in Current Trends in Information Technology · Vol. 15, Issue 1, 2025 · pp. 12–18 Read article
-
Academia to Industry: The Impact of AI on Information Retrieval Technologies
Abstract: Artificial intelligence (AI) has significantly reshaped the field of information retrieval (IR), bridging theoretical advancements from academia with practical applications across various industries. This article explores the transformative impact of AI on IR technologies, highlighting key contributions from academic research and how they have been adapted for industry-scale implementations. Academic innovations, such as neural ranking models and semantic search techniques, have improved the accuracy and relevance of search results by …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
-
Automation in Waste Management: How AI and Robotics Transforming Waste Sorting and Recycling
Abstract: Waste management is a big issue in the modern world, and it gets worse as urbanisation and industry increase. Hazards to the environment and human health result from traditional waste management practices' inability to effectively classify, recycle, and dispose of garbage. Robotics and artificial intelligence (AI) provide creative ways to improve trash processing, sorting, and collection. This article examines the application of robotics and artificial intelligence (AI) to waste management, …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
-
Future Prospects of AI in Pharmaceutical Industry and its Limitation
Abstract: The pharmaceutical industry is facing significant challenges, including prolonged drug development timelines, high costs, and low success rates in clinical trials. Traditional methods often result in inefficiencies, with new drug development taking over a decade and billions of dollars, yet most candidates fail in clinical trials due to issues like inefficacy or safety concerns. Artificial Intelligence (AI) has become a groundbreaking technology with the potential to tackle these issues effectively. …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 6–13 Read article