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The study highlights the potential of serverless computing as a sustainable backbone for next-generation IoT–ML systems, offering guidelines for building carbon-aware and cost-efficient inference pipelines for real-world applications.
There is a conclusion that although AI has become an inseparable part of linguistics today, there is a need to establish a balanced approach of using computational methods and knowledge of human linguists to be sustainable and ethical.
This study reviews pre-2018 developments and proposes an improved HAR framework incorporating advanced feature engineering, sensor fusion, and ensemble learning techniques, which shows strong potential in healthcare, fitness, and smart environments.
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