Emerging Trends in AI-Powered IoT: Innovations, Key Challenges, and Future Directions

This survey provides a comprehensive overview of recent emerging technologies in artificial intelligence (AI) applied to the Internet of Things (IoT), highlighting their significance and applications across various domains. Our study covers key advancements, including Concept Drift, Transformers, TinyML, Explainable AI (XAI), and Federated Learning (FL). Concept Drift addresses changes in data patterns to maintain the accuracy of machine learning models in dynamic environments. Transformers revolutionize Natural language processing (NLP) by efficiently capturing long-range dependencies. TinyML enables smart IoT applications on low-power devices, while XAI promotes transparency in AI decisions. FL facilitates decentralized model training while preserving data privacy. Our discussion also covers challenges, limitations, and future research directions to improve AI and IoT integration.