Kongunadu College of Engineering and Technology(Autonomous)

Inside an electric vehicle’s battery pack, thousands of battery cells work side by side to deliver power. But keeping an eye on every single cell's temperature and charge level creates a massive headache for automakers: a tangled mess of copper wires. These wiring harnesses add dead weight, complicate factory assembly and introduce physical failure points inside a tightly sealed, high voltage battery case. Engineers tried solving this using standard wireless communication like Bluetooth or Wi-Fi, but they hit an unexpected snag. Inside a sealed metal battery pack, normal radio waves bounce off the metallic walls like a loud echo in an empty room, causing heavy signal clutter and dropped data. Enter Near Field Electric (NFE) wireless sensing, a clever hardware fix that ditches bouncing radio waves for localized electric fields. Wired Harnesses vs. Modular Wireless Battery Design The Big Trouble with Standard Wi-Fi and Bluetooth Inside a Battery Standard wireless signals are built to...

  Abstract: The human heart is a complex muscular pump whose life-sustaining rhythmic contractions are governed by a sophisticated, self-contained electrical network. This paper explores the cardiac conduction system, the intricate internal wiring responsible for generating and transmitting the electrical impulses that trigger every heartbeat. We examine the initiation of the cardiac cycle at the sinoatrial (SA) node, the heart's natural pacemaker, and trace the sequential pathway of the electrical signal through the atrioventricular (AV) node, the Bundle of His, and the Purkinje fibers. Furthermore, the discussion highlights how this hidden system precisely coordinates atrial and ventricular contractions to optimize blood flow. Finally, we review common clinical arrhythmias resulting from electrical malfunctions and look into modern biomedical advancements, such as artificial pacemakers and ablation therapies, designed to restore the heart's natural rhythm. Introduction: The B...

Introduction Artificial Intelligence (AI) Agents are intelligent software systems capable of perceiving their environment, reasoning about tasks, making decisions, and performing actions autonomously. Modern AI agents combine large language models, memory, planning, and external tools to solve complex real-world problems. They are transforming healthcare, finance, education, cybersecurity, software engineering, manufacturing, and customer support by improving productivity and reducing manual effort. Architecture User -> AI Agent (LLM) -> Memory/Planning/Decision -> External Tools/APIs -> Response Working The user submits a request. The AI agent interprets the request, retrieves relevant knowledge, plans the required steps, chooses suitable actions, invokes external tools or databases when necessary, verifies the results, and returns an accurate response. Continuous learning and feedback help improve future performance. Applications AI agents are used in virtual assistants, ...

Construction Materials That Can Heal Themselves August 2026 Introduction Concrete is one of the most widely used construction materials because of its strength and durability. However, cracks can develop over time due to loading, temperature changes, shrinkage, and environmental conditions. Small cracks may gradually allow water and harmful chemicals to enter the structure, reducing its service life. Living concrete is an innovative material designed to address this problem naturally. It uses biological processes, such as bacteria or other living components, to repair cracks automatically. This technology has the potential to create stronger, longer-lasting, and more sustainable structures. Living concrete showing self-healing cracks and biological activity Evolution of Self-Healing Construction Materials Traditional concrete repair requires regular inspection, maintenance, and additional repair materials. Researchers first developed chemical-based self-healing systems to reduce these ...

  Description: Much of the software used today depends on open-source projects. These projects make source code available under licences that allow people to use, study, modify and share it according to the licence terms. Open source has become an important part of software development and also provides valuable learning opportunities for students. One of the most interesting aspects of open source is collaboration. A project may have contributors from different countries and backgrounds. People can report problems, improve documentation, suggest features and submit code. The work is coordinated through version-control systems and project guidelines. For students, this creates a chance to learn from real software. Classroom programs are useful for understanding concepts, but large open-source projects show how code is organised in practice. Students can examine documentation, issue discussions, testing procedures and contribution workflows. Figure 1: Illustrative view related...

  ABSTRACT:          In the history of agriculture, many projects have been introduced.   All of them aimed to improve our lives, the lives of farmers, or agriculture in general. Some of these projects succeeded, while others did not. In my paper, I will discuss one such project that failed-Golden rice. Golden Rice is a genetically modified type of rice designed to help prevent vision problems in young children. However, for various reasons, it did not succeed. Despite the promise of Golden Rice, it faced challenges in production, distribution, and public acceptance. These included issues with regulatory approvals, public opinion, and concerns about genetically modified organisms. Though it was created to fight vitamin A deficiency, the journey of Golden Rice was complicated. It is an interesting example of how science and society interact. INTRODUCTION:        Golden Rice is a genetically modified ric...

Introduction Unexpected equipment failure is one of the major causes of production loss in industries. Traditional maintenance methods either repair machines after failure or service them at fixed intervals. AI-Based Predictive Maintenance offers a smarter solution by predicting equipment problems before breakdown occurs. It combines Artificial Intelligence, Machine Learning, Industrial IoT, sensors, and condition monitoring to continuously assess machine health and support timely maintenance decisions. How Does It Work? Sensors installed on industrial machines collect real-time operating data such as: • Vibration • Temperature • Pressure • Motor current • Speed • Acoustic signals • Lubricant condition The collected data is processed using AI and machine-learning algorithms. These algorithms identify abnormal patterns and compare them with normal operating behaviour. When early signs of a fault are detected, the system alerts maintenance personnel before serious failure occurs. Typical...