Real-Time Systems Projects for ME, MTech, Masters, MS abroad, and PhD students. These Real-Time Systems ieee projects are implemented with future work and extension for final year students with research paper writing and publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Real-Time Systems Projects
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A Framework for Cognitive, Decentralized Container Orchestration
This project introduces CODECO, a system that helps decide the best infrastructure for running modern Internet applications on a mix of cloud and edge devices. It uses smart, decentralized methods to handle challenges like weak connections or device failures. CODECO aims to meet user goals like energy efficiency or reliability. The framework is open-source and can be used and tested by researchers. -
A Hyper-Heuristic Approach for Quality of Experience Aware Service Placement Scheme in 5G Mobile Edge Computing
This project focuses on improving 5G mobile edge computing. It aims to place computing services closer to users so they get faster responses. The system predicts user movement and moves services ahead of time to improve user experience. It uses smart algorithms to balance speed, cost, and efficiency in large networks. -
Reliability-Driven End–End–Edge Collaboration for Energy Minimization in Large-Scale Cyber-Physical Systems
This project focuses on making large-scale cyber-physical systems, like smart factories or connected devices, more energy-efficient and reliable. It studies how devices and edge computers can work together to handle tasks without wasting energy. The researchers created a method to group tasks, control them efficiently, and offload work smartly. Their approach reduced energy use by over 50% compared to other methods. -
A Review on Optimization-Based Automatic Text Summarization Approach
This project studies how computers can automatically create short and meaningful summaries from long texts. It focuses on optimization-based methods that make summaries more accurate and useful. The paper compares these methods with machine learning and deep learning techniques. It also suggests ways to improve automatic summarization for real-time applications in the future. -
Deep Learning Based Multi Pose Human Face Matching System
This project develops a real-time system that can recognize human faces even when they are turned or viewed from different angles. It uses a deep learning model called YOLO-V5 to detect and match faces quickly and accurately. The system learns different face positions and improves recognition speed and reliability. It helps identify and track people more effectively in live video streams.
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