Date of Publication :7th December 2025

Abstract: Electronic devices are machines designed to process information and perform tasks through electrical signals. Portable electronic devices, such as smartphones, tablets and laptops, are compact and battery- powered, making them easy to carry and use anywhere. AI assistance refers to intelligent systems that help users by providing automation, decision support, and personalized interaction. Agentic AI extends traditional AI by giving systems the ability to reason, make decisions, and act proactively in user- centric environments. This literature survey reviews the foundations of electronic devices, portable devices, AI assistance, and agentic AI in the context of intelligent recommendation. It focuses on data preprocessing, NLP, AI models, and recommendation systems relevant to portable device assistants. The survey highlights preprocessing methods for structured/unstructured data, NLP- based intent detection, AI model performance, and hybrid recommendation techniques. In conclusion, the literature review shows that combining preprocessing, NLP, agentic AI models, and recommendation logic enhances accuracy, personalization, and user satisfaction in portable AI assistants.

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