Open Access

ARTICLE

Human Intelligent-Things Interaction Application Using 6G and Deep Edge Learning

Ftoon H. Kedwan^*, Mohammed Abdur Rahman

College of Computer and Cyber Sciences, University of Prince Mugrin, Medina, 42241, Saudi Arabia

* Corresponding Author: Ftoon H. Kedwan. Email:

Journal on Internet of Things 2024, 6, 43-73. https://doi.org/10.32604/jiot.2024.052325

Received 30 March 2024; Accepted 12 August 2024; Issue published 10 September 2024

Abstract

Impressive advancements and novel techniques have been witnessed in AI-based Human Intelligent-Things Interaction (HITI) systems. Several technological breakthroughs have contributed to HITI, such as Internet of Things (IoT), deep and edge learning for deducing intelligence, and 6G for ultra-fast and ultralow-latency communication between cyber-physical HITI systems. However, human-AI teaming presents several challenges that are yet to be addressed, despite the many advancements that have been made towards human-AI teaming. Allowing human stakeholders to understand AI’s decision-making process is a novel challenge. Artificial Intelligence (AI) needs to adopt diversified human understandable features, such as ethics, non-biases, trustworthiness, explainability, safety guarantee, data privacy, system security, and auditability. While adopting these features, high system performance should be maintained, and transparent processing involved in the ‘human intelligent-things teaming’ should be conveyed. To this end, we introduce the fusion of four key technologies, namely an ensemble of deep learning, 6G, IoT, and corresponding security/privacy techniques to support HITI. This paper presents a framework that integrates the aforementioned four key technologies to support AI-based Human Intelligent-Things Interaction. Additionally, this paper demonstrates two security applications as proof of the concept, namely intelligent smart city surveillance and handling emergency services. The paper proposes to fuse four key technologies (deep learning, 6G, IoT, and security and privacy techniques) to support Human Intelligent-Things interaction, applying the proposed framework to two security applications (surveillance and emergency handling). In this research paper, we will present a comprehensive review of the existing techniques of fusing security and privacy within future HITI applications. Moreover, we will showcase two security applications as proof of concept that use the fusion of the four key technologies to offer next-generation HITI services, namely intelligent smart city surveillance and handling emergency services. This proposed research outcome is envisioned to democratize the use of AI within smart city surveillance applications.

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Keywords

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