Journal Home
Login
Register
Open Access Journal
Submit a Paper
Propose a Special lssue
Open Access
ARTICLE
INTELLIGENT DATA PROCESSING ECOSYSTEMS: INTEGRATING IOT, CLOUD, AND EDGE COMPUTING WITH ARTIFICIAL INTELLIGENCE FOR NEXT-GENERATION SMART SYSTEMS
Issue Vol. 1 No. 01 (2024): Volume 01 Issue 01 --- Section Articles --- Published Date: 2024-12-28
Abstract
The convergence of Internet of Things (IoT), cloud computing, edge computing, and artificial intelligence (AI) technologies has created unprecedented opportunities for intelligent data processing and automated decision-making across various domains. This comprehensive review examines the synergistic integration of these technologies, analyzing their architectural frameworks, implementation challenges, and real-world applications. The proliferation of IoT devices, expected to reach billions of connections globally [3], necessitates sophisticated data processing paradigms that can handle massive volumes of heterogeneous data while ensuring real-time responsiveness and energy efficiency. This study investigates how cloud and edge computing infrastructures serve as foundational platforms for deploying AI algorithms, enabling intelligent data analytics from sensor networks to actionable insights. Through systematic analysis of current literature and emerging trends, we identify key challenges including security vulnerabilities, resource constraints, scalability issues, and ethical considerations in AI deployment. The findings reveal that federated learning, model compression techniques, and distributed computing architectures are critical enablers for successful IoT-AI integration. Furthermore, the research highlights the importance of standardized protocols, robust security frameworks, and energy-efficient algorithms in creating sustainable intelligent ecosystems. This work contributes to understanding the technological landscape of integrated IoT-AI systems and provides insights for future research directions in autonomous computing environments.
Keywords
References
[1] Atzori, L.; Iera, A.; Morabito, G. The Internet of Things: A survey. Comput. Netw. 2010, 54, 2787–2805. [CrossRef]
[2] Ersöz, B.; Oyucu, S.; Aksöz, A.; Sağıroğlu, Ş.; Biçer, E. Interpreting CNN-RNN Hybrid Model-Based Ensemble Learning with Explainable Artificial Intelligence to Predict the Performance of Li-Ion Batteries in Drone Flights. Appl. Sci. 2024, 14, 10816. [CrossRef]
[3] Vailshery, L.S. Number of IoT Connections Worldwide 2022–2033. 2024. Available online: https://www.statista.com/statistics/1183457/iot-connected-devices-worldwide/ (accessed on 2 December 2024).
[4] Lombardi, M.; Pascale, F.; Santaniello, D. Internet of Things: A General Overview between Architectures, Protocols and Applications. Information 2021, 12, 87. [CrossRef]
[5] Ali, O.; Ishak, M.K.; Bhatti, M.K.L.; Khan, I.; Kim, K.I. A Comprehensive Review of Internet of Things: Technology Stack, Middlewares, and Fog/Edge Computing Interface. Sensors 2022, 22, 995. [CrossRef] [PubMed]
pdf
