AI-Powered IoT: A Survey on Integrating Artificial Intelligence With IoT for Enhanced Security, Efficiency, and Smart Applications - Vivek Menon U; Vinoth Babu Kumaravelu; Vinoth Kumar C; Rammohan A; Sunil Chinnadurai; Rajeshkumar Venkatesan; Han Hai; Poongundran Selvaprabhu (IEEE Access)
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.