Kongunadu College of Engineering and Technology(Autonomous)

Description: This article delves into how data analytics is transforming decision making in healthcare, shedding light on how data driven strategies are reshaping the way care is delivered and managed. By leveraging data from electronic health records, wearable devices, and other sources, healthcare professionals can identify trends, predict patient needs, and make informed decisions. As healthcare systems continue to embrace digital transformation, there’s been a massive surge in the amount of data being generated from electronic health records (EHRs) and diagnostic imaging to genomic data and real time updates from wearable devices. But collecting data is just the beginning; the real impact comes from how that data is analyzed and turned into actionable insights. In an era of unprecedented data generation, the healthcare industry is undergoing a profound transformation. The use of data analytics has shifted healthcare from intuition driven to evidence based decisions, supporting clin...

    1. Introduction to Artificial Intelligence Artificial Intelligence (AI) is the branch of computer science that enables machines to simulate human intelligence. Unlike traditional programs that follow explicit instructions, AI systems are capable of learning from data, reasoning logically, solving complex problems, and making decisions independently . AI has evolved significantly over the past few decades, moving from theoretical concepts to practical applications that affect our daily routines. From simple tasks like filtering emails to complex processes like autonomous driving, AI is reshaping industries and lifestyles.The key characteristic of AI is its ability to mimic cognitive functions of the human brain. Through techniques such as machine learning, deep learning, and natural language processing, AI systems can analyze vast amounts of data, recognize patterns, and continuously improve their performance. As technology advances, AI continues to integrate into every...

 ABSTRACT: The growing demand for sustainable and biodegradable alternatives to conventional wood based paper has led to the exploration of agricultural residues and natural fibers for pulp production. This project focuses on the development of paper pulp using a sisal fiber, banana fiber and rice straw three abundant and renewable bio resources. This study involves the extraction of fiber through suitable pulping techniques such as chemical or mechanical processes, followed by blending in various proportions to form pulp sheets. The prepared paper samples are evaluated for their physical properties including strength, texture and durability. INTRODUCTION: Paper production traditionally relies heavily on wood as the primary raw material. However, overexploitation of forests has led to deforestation, loss of biodiversity and environmental imbalance. To address these issues, researchers and industries are exploring alternative sources of cellulose fibers such as sisal, banana fibers ...

  Introduction: The Power of Biomedical Data      Healthcare today produces enormous amounts of data every second. From heartbeats recorded on an ECG machine to the millions of MRI scans performed every year, this data holds critical insights into human health. On their own, these signals and images are just raw information. But through the field of Biomedical Signal and Image Processing, engineers and medical professionals are able to transform this information into life-saving knowledge. By combining engineering principles, computer science, and medicine, this field supports early diagnosis, more effective treatments, and the advancement of personalized healthcare. Understanding Biomedical Signals      Biomedical signals are continuous recordings of the body’s physiological activities, and they play a crucial role in monitoring patient health. The electrical activity of the heart is measured through an electrocardiogram (ECG), while brain activity is...

ABSTRACT: The emergence of Artificial Intelligence (AI) in agriculture is a turning point in world farming, ushering in data-driven, automated, and hugely flexible solutions to long-standing problems. AI technologies from machine learning algorithms and neural networks to robots and computer vision are helping farmers to track crops in real-time, identify pests and diseases early, optimize irrigation and fertilization, and enhance harvesting precision. These technologies are not just improving yield and resource use efficiency but also equipping farms to react more efficiently to environmental stresses, changing market needs, and worker focus. The application of predictive analytics and AI-driven decision support tools is revolutionizing conventional farming into an intelligent and responsive business. Moreover, AI makes sustainable methods easier to integrate by reducing chemical inputs, cutting water waste, and making more climatically resilient crop planning possible. Despite challe...