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| Title | From Data To Decisions: Cloud, Iot, And Ai Integration |
|---|---|
| ID_Doc | 27178 |
| Authors | Prerna; Sharma S. |
| Year | 2024 |
| Published | Integration of Cloud Computing and IoT: Trends, Case Studies and Applications |
| DOI | http://dx.doi.org/10.1201/9781032656694-26 |
| Abstract | The convergence of cloud computing, the Internet of Things (IoT), and artificial intelligence (AI) has ushered in a transformative era of technological innovation with profound implications for various industries. This book chapter, titled “From Data to Decisions: Cloud, IoT, and AI Integration,” explores the synergies, challenges, and opportunities presented by the fusion of these three powerful domains. In recent years, the proliferation of IoT devices has generated unprecedented data, laying the foundation for a data-driven world. However, the true value of this data can only be unlocked through advanced analytics, and this is where AI and cloud computing enter the scene. This chapter elucidates how cloud computing serves as a catalyst, providing the scalable infrastructure to process, store, and analyze the massive influx of IoT data. Integrating cloud computing with IoT begins with establishing a robust, scalable, and secure infrastructure that enables the seamless transfer of data between devices and the cloud. The authors delve into the intricacies of cloud IoT integration, emphasizing the importance of real-time data processing, data governance, and security measures to protect sensitive information. AI plays a pivotal role in deriving actionable insights from IoT data. The chapter expounds upon the various AI techniques that can be applied to analyze IoT data, including machine learning, deep learning, and natural language processing. One of the central themes explored in this chapter is the significance of edge computing in the cloud-IoT-AI ecosystem. Edge computing allows for data processing and analysis at the network’s edge, reducing latency and ensuring real-time decision-making. The authors discuss how edge devices with AI capabilities revolutionize industries such as healthcare, manufacturing, and transportation by enabling local data processing and decision-making. The discussion also addresses the challenges and ethical considerations inherent in this convergence. Privacy, data security, and the responsible use of AI are critical concerns that demand careful consideration. The authors offer insights into best practices for addressing these challenges, ensuring compliance with data regulations, and maintaining transparency in AI decision-making. Furthermore, the chapter explores the potential societal impact of cloud-IoT-AI integration. From smart cities that optimize resource usage to precision agriculture that enhances food production, this technology convergence has the potential to address some of the world’s most pressing challenges. The chapter emphasizes the importance of interdisciplinary collaboration between cloud computing experts, IoT practitioners, and AI researchers. The synergies created by combining these domains offer an unparalleled opportunity to drive innovation and reshape industries. © 2025 selection and editorial matter, Prabh Deep Singh and Mohit Angurala; individual chapters, the contributors. |
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