Integration of AI, IoT, and Edge Computing: Architectural Frameworks, Enabling Technologies, and Intelligent System Integration

The rapid expansion of the Internet of Things (IoT) has led to unprecedented growth in data generated from heterogeneous and resource-constrained environments across domains such as smart healthcare, transportation, agriculture, and industrial automation. Traditional cloud-centric computing models face significant challenges in handling latency-sensitive and data-intensive applications due to bandwidth limitations, network congestion, privacy risks, and delayed response times. To address these limitations, the integration of Artificial Intelligence (AI), IoT, and edge computing has emerged as a transformative paradigm for enabling intelligent, scalable, and low-latency systems. By processing data closer to its source, edge computing reduces latency, improves reliability, enhances privacy, and supports real-time decision-making.