AN IOT-ENABLED EMBEDDED SCHEDULING FRAMEWORK FOR AUTOMATIC TASK MANAGEMENT
DOI:
https://doi.org/10.64751/Abstract
With the growing reliance on embedded systems across industries, efficient task scheduling has become a critical requirement for optimizing performance, reducing energy consumption, and ensuring real-time responsiveness. Traditional task scheduling approaches in embedded systems are often limited by static methods, leading to resource underutilization and execution delays. This paper proposes an IoT-enabled embedded scheduling framework for automatic task management, which integrates real-time monitoring, adaptive scheduling algorithms, and intelligent resource allocation. The system leverages IoT connectivity for dynamic feedback and optimization, ensuring that tasks are executed with minimal latency and maximum efficiency. Experimental validation demonstrates that the framework significantly improves system throughput, reduces energy consumption, and enhances task predictability compared to conventional scheduling approaches. The proposed solution is highly scalable, making it suitable for applications in smart manufacturing, healthcare devices, home automation, and autonomous systems
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