| Title | Intelligent Edge Computing for Real-Time Internet of Things Applications: A Secure and Adaptive Framework |
| Research Area | Internet of Things |
| Abstract | The Internet of Things (IoT) has become an important foundation for modern intelligent systems by connecting sensors, embedded devices, machines, vehicles, industrial equipment, and consumer ap-pliances through communication networks. The continuous growth of IoT devices has also resulted in enormous volumes of data that require rapid processing. Traditional cloud-centric architectures frequently transmit IoT data to remote data centers for analysis, which can introduce network la-tency, bandwidth consumption, privacy concerns, and dependency on centralized infrastructure. Edge computing addresses these limitations by moving computation and analytics closer to the de-vices that generate data. The combination of edge computing and artificial intelligence creates an emerging paradigm in which intelligent decisions can be made near the data source rather than rely-ing exclusively on centralized cloud services. Recent research identifies low latency, resource effi-ciency, and localized processing as important motivations for Edge AI, while also highlighting chal-lenges involving constrained hardware, security, privacy, and model deployment. (DOI) |
| Keywords | Internet of Things, Edge Computing, Edge AI, Artificial Intelligence, Machine Learn-ing, Real-Time Processing, IoT Security, Federated Learning, Resource Management, Anomaly De-tection |
| Paper Status | Published |
| Volume | 2 |
| Issue | 3 |
| Published On | 15/06/2026 |
| Published File |
IJSRTD_4883.pdf
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