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159 articles for “data-driven decision making”
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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IoT-Enabled Sustainable Development: Architectures, Applications, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) has developed into a powerful technology that can help tackle key global sustainability issues by enabling real-time monitoring, supporting data-based decisions, and facilitating smart automation. By interconnecting physical devices, sensors, and communication networks, IoT enables continuous data collection and analysis that supports efficient resource utilization across multiple sectors such as energy, agriculture, water management, transportation, and urban infrastructure. Through smart sensing and automated control systems, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
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Transforming Digital Health Card Healthcare in India: An Integrated IT Solution
Abstract: India's healthcare sector faces critical challenges, including fragmented medical records, limited access to quality care in rural areas, and inefficiencies in patient engagement and insurance processes. This study proposes an innovative IT-driven healthcare model integrating a digital health card, web application, and NFC-enabled mobile platform. The system aims to streamline medical record management, enable telemedicine consultations, and provide seamless prescription and insurance integration. Advanced digital capabilities ranging from AI-driven recommendations …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 11–15 Read article
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Farmer’s Eye: A Sustainable Crop-Field Monitoring System
Abstract: This paper outlines the creation and implementation of an Internet of Things (IoT)-driven smart agriculture monitoring system. It aims to tackle major issues in agriculture, such as inefficient irrigation, excessive resource use, and a lack of real-time data. The system focuses on the Arduino Uno, which connects to a variety of sensors: soil moisture for measuring substrate conditions, DHT11 for monitoring ambient temperature and humidity, MQ135 for checking air quality, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 19–27 Read article
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Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Smart Agriculture: IoT-Based Automation and Monitoring for Enhanced Farming Efficiency
Abstract: This paper presents the development of an innovative agriculture automation and monitoring system designed to improve farming efficiency through the integration of low-cost sensors and microcontrollers. The system utilizes components such as PIR motion sensors, soil moisture sensors, DHT11 humidity sensors, and a relay motor pump for precise automation of irrigation and environmental monitoring. NodeMCU (ESP8266) acts as the primary controller, facilitating real-time data gathering and decision-making. Results show significant …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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Automation and Robotics for Quality Control in Manufacturing: A Review of Technologies and Applications
Abstract: Automation and robotics technologies have rapidly evolved, transforming modern manufacturing processes by improving productivity, quality, and operational efficiency. This review examines key advancements such as cloud robotics, machine vision, Industry 4.0 robotics, Building Information Modeling (BIM) combined with Computer Numerical Control (CNC), joystick-controlled automation, and intelligent manufacturing systems. These technologies utilize artificial intelligence (AI), machine learning (ML), digital twins, collaborative robots, programmable logic controllers (PLCs), and cyber-physical systems (CPS) to …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 36–48 Read article
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Artificial Intelligence for Improved Healthcare: A Case Study and Applications
Abstract: Artificial intelligence (AI) in healthcare ushers in a revolutionary period of innovation, but it also brings with it significant ethical dilemmas. This paper explores the complex relationship between AI and healthcare, emphasizing both its useful applications and the moral conundrums that arise. Ethical issues span a wide range, including patient privacy, transparency, accountability, and the unintentional reinforcement of biases in AI algorithms. Privacy concerns take center stage as healthcare providers …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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Industry 6.0: Building a Sustainable Future
Abstract: The next stage of industrialization, known as Industry 6.0, is centered on developing intelligent, fully integrated manufacturing systems that require little human involvement. India is in a perfect position to become a major player in the sector 6.0 ecosystem, thanks to its robust technological infrastructure, fast expanding economy, and large talent pool. It blends big data, cloud computing energy, human-robot interaction, artificial intelligence, and quantum computing. The main aim of …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 25–32 Read article
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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Optimizing Mango Harvest Timing in the Nasik Region (Maharashtra, India) by CNNs (Residual Network 101)
Abstract: The determination of optimal harvest timing is one of the most critical decisions in mango production, directly affecting postharvest quality, market value, transportation resilience, and export readiness. In regions such as Nashik, Maharashtra—one of India’s major fruit- producing belts—the climatic variability, cultivar differences, monsoon patterns, and market- driven pressures make accurate harvest timing essential. Traditional maturity assessment relies on subjective visual inspection, specific gravity, or destructive testing, each of which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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A Polymer-Based Recommender System for Precision Agriculture: Enhancing Crop Yield Analysis Using IoT Technology
Abstract: This study introduces an innovative recommender system that employs polymer-based sensors combined with advanced data analytics to deliver personalized recommendations for crop management optimization. The use of polymer-based materials in sensor design allows for the creation of durable, cost-effective, and efficient sensors, well-suited for the challenging conditions typical in agricultural environments. These sensors are designed to withstand variations in numerous factors like temperature of the surrounding, humidity level, and at …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 86–95 Read article
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Harnessing IoT and Sensor Technologies for Smart Agriculture: A Path Towards Viksit Bharat
Abstract: The integration of Internet of Things (IoT) and sensor technologies is redefining the landscape of Indian agriculture, serving as a catalyst for achieving the ambitious vision of Viksit Bharat (Developed India). Indian agriculture faces significant challenges such as resource scarcity, climate variability, and fragmented supply chains, which hinder productivity and sustainability. IoT-based solutions offer innovative approaches to address these critical issues by enabling smart irrigation systems, real-time field monitoring, precision …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 2, 2025 · pp. 38–45 Read article
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FutureGen – Predicting Genetic Health
Abstract: FutureGen is an intelligent web-based system developed to help couples assess the risk of genetic disorders in their future child through data-driven analysis. The system brings together modern web technologies and machine learning to offer accurate and accessible predictions. The frontend, built with React, provides an intuitive interface for user interaction, while a Flask-based backend API handles model inference and manages communication with the Supabase database, which securely stores user …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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Real-Time Supply Chain Monitoring with Blockchain: A Decentralized Approach
Abstract: This study presents the development and implementation of a Blockchain-Enhanced Shipment Management and Tracking System (SMTS) to address key challenges in the logistics and shipping industry, such as inefficiencies, lack of transparency, security concerns, and high operational costs. Utilizing blockchain technology, particularly Hyperledger Fabric, the SMTS creates a decentralized, immutable ledger that enhances real-time shipment tracking, ensures data integrity, and improves security by reducing fraud and unauthorized tampering. Smart contracts …
Published in Trends in Electrical Engineering · Vol. 14, Issue 3, 2024 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article