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AI驱动的物联网:集成人工智能与物联网以增强安全、效率和智能应用综述
AI-Powered IoT: A Survey on Integrating Artificial Intelligence With IoT for Enhanced Security, Efficiency, and Smart Applications
| 作者 | Vivek Menon U · Vinoth Babu Kumaravelu · Vinoth Kumar C · Rammohan A · Sunil Chinnadurai · Rajeshkumar Venkatesan |
| 期刊 | IEEE Access |
| 出版日期 | 2025年1月 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 SiC器件 工商业光伏 机器学习 深度学习 |
| 相关度评分 | ★★★★ 4.0 / 5.0 |
| 关键词 | 物联网 人工智能物联网 安全 架构 应用 |
语言:
中文摘要
物联网IoT和人工智能AI驱动的IoT是近年来激增至新高度的重要范式。IoT是智能技术,其中我们周围无处不在的物理对象或事物联网并连接到互联网以提供新服务和增强效率。IoT主要目标是在通用基础设施下连接世界所有物理对象或事物,允许人类控制它们并获得及时频繁的状态更新。这些连接到IoT的事物或设备生成、收集和处理海量二进制数据。来自这些设备的海量数据由AI算法和技术分析和学习,帮助为用户提供更好服务。因此AI驱动的IoT或人工物联网AIoT是融合AI与IoT的混合技术,能够轻松高效简化复杂繁重任务。IoT中各种机器学习ML和深度学习DL算法对确保IoT网络改善的安全性和保密性是必要的。本文还综述构成IoT和AIoT骨干的各种架构。此外阐明用于保护IoT的无数最先进ML和DL方法,包括检测异常/入侵、身份验证和访问控制、攻击检测和缓解、防止分布式拒绝服务DDoS攻击、IoT恶意软件分析。综述AIoT在优化网络效率、保护IoT基础设施和应对关键挑战中的作用。探索区块链、6G-AIoT、联邦学习和超维计算等前沿技术,表明它们在医疗保健、自主系统和工业自动化等领域推进IoT和AIoT驱动应用的潜力。
English Abstract
The Internet of Things (IoT) and artificial intelligence (AI) enabled IoT is a significant paradigm that has been proliferating to new heights in recent years. IoT is a smart technology in which the physical objects or the things that are ubiquitously around us are networked and linked to the internet to deliver new services and enhance efficiency. The primary objective of the IoT is to connect all the physical objects or the things of the world under a common infrastructure, allowing humans to control them and get timely, frequent updates on their status. These things or devices connected to IoT generate, gather and process a massive volume of binary data. This massive volume of data generated from these devices is analyzed and learned by AI algorithms and techniques that aid in providing users with better services. Thus, AI-enabled IoT or artificial IoT (AIoT) is a hybrid technology that merges AI with IoT and is capable of simplifying complicated and strenuous tasks with ease and efficiency. The various machine learning (ML) and deep learning (DL) algorithms in IoT are necessary to ensure the IoT network’s improved security and confidentiality. Furthermore, this paper also surveys the various architectures that form the backbone of IoT and AIoT. Moreover, the myriad state-of-the-art ML and DL-based approaches for securing IoT, including detecting anomalies/intrusions, authentication and access control, attack detection and mitigation, preventing distributed denial of service (DDoS) attacks, and analyzing malware in IoT, are also enlightened. In addition, this work also reviews the role of AIoT in optimizing network efficiency, securing IoT infrastructures, and addressing key challenges. Furthermore, it explores cutting-edge technologies like blockchain, 6G-enabled AIoT, federated learning (FL), and hyperdimensional (HD) computing, indicating their potential in advancing IoT and AIoT-driven applications within sectors like healthcare, autonomous systems, and industrial automation. Therefore, based on the plethora of prevailing significant works, the objective of this manuscript is to provide a comprehensive survey that expounds on AIoT in terms of security, architecture, applications, emerging technologies, and challenges.
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SunView 深度解读
该AIoT综述对阳光电源iSolarCloud平台和智能设备发展有全面指导价值。阳光云平台连接海量光伏储能设备,AIoT技术可提升平台智能化水平和设备管理效率。机器学习和深度学习安全方法可应用于阳光平台的入侵检测和异常识别。联邦学习技术可实现阳光分布式设备的隐私保护协同训练。区块链技术对阳光能源交易和数据可信共享有价值。6G通信技术对阳光未来设备连接升级有前瞻性参考。该综述为阳光构建更安全高效的AIoT平台提供全面技术路线,支撑智慧能源管理和工业自动化业务拓展。