Enhancing Usability and Control in Artificial Intelligence of Things Environments (AIoT) Through Semantic Web Control Models

Introduction

Enhancing usability and control in Artificial Intelligence of Things (AIoT) environments through Semantic Web Control Models represents a significant advancement in the field, offering a comprehensive framework for managing the complexity of interconnected devices and systems. Semantic Web Control Models leverage semantic technologies, such as ontologies and linked data, to enhance interoperability, discoverability, and understanding of web content within AIoT ecosystems. By providing a shared understanding of data semantics, these models enable more intelligent, context-aware interactions among diverse applications and devices. This overview explores how Semantic Web Control Models facilitate usability and control in AIoT environments by enabling personalized experiences, seamless integration, and efficient management of interconnected resources (Zhang & Tao, 2020). Through the integration of standardized ontologies and vocabularies, Semantic Web Control Models enable AIoT systems to interpret and contextualize information accurately, leading to more intuitive and effective user interfaces. Additionally, these models support the development of adaptive systems and intelligent assistants that can learn from user interactions and dynamically adjust their behavior to meet evolving user needs and preferences (Bibri et al., 2024). Moreover, Semantic Web Control Models enable the aggregation and fusion of data from disparate sources, facilitating seamless integration and interoperability among heterogeneous devices and systems. This unified view of data enhances decision-making, enables real-time monitoring and control, and fosters innovation in AIoT applications. Overall, Semantic Web Control Models offer a holistic approach to enhancing usability and control in AIoT environments, enabling organizations to realize the full potential of interconnected devices and systems in delivering personalized, context-aware experiences to users.

The Artificial Intelligence of Things (AIoT) is a combination of AI and the Internet of Things, offering transformative capabilities. However, as AIoT systems become more complex and interconnected, usability and control are crucial. The complexity of interconnected devices, sensors, and actuators can make it difficult for users to manage and control these systems effectively. The diversity of interfaces and interaction paradigms can also cause confusion and frustration. Therefore, simplifying the user experience and providing intuitive control mechanisms are essential for improving usability in AIoT environments (Tabuenca et al., 2024). User interface design is crucial for enhancing usability in AIoT environments. It should be intuitive, responsive, and accessible, facilitating user interactions. Human-centered design principles and user feedback can tailor interfaces to specific needs. Prioritizing usability empowers users to interact with complex systems. Accessibility and user experience issues are also essential for inclusivity and usability. Ensuring AIoT systems are accessible to diverse users can enhance engagement and satisfaction. Addressing accessibility and user experience considerations upfront can lead to more user-friendly and inclusive AIoT environments (Shi et al., 2021).

Semantic Web control models enhance usability and control in AIoT environments by leveraging semantic technologies like ontologies and linked data. They enable intelligent, context-aware interactions, seamless integration across devices, and simplified user control. These models capture and represent IoT data, resulting in more intuitive and personalized user experiences. They simplify management and management of AIoT environments. Enhancing usability and control in AIoT environments is crucial for maximizing the full potential of these technologies. By addressing device complexity, designing intuitive interfaces, and utilizing semantic Web control models, developers can create intelligent AIoT systems, leading to more accessible, inclusive, and satisfying user experiences (Tan et al., 2021). Artificial Intelligence of Things (AIoT) is a combination of Artificial Intelligence (AI) and the Internet of Things (IoT), enabling the integration of AI capabilities into IoT devices and systems. This synergy has the potential to revolutionize various industries by enabling smarter, more efficient, and responsive systems. The IoT, consisting of interconnected devices with sensors, actuators, and communication capabilities, forms the foundation of AIoT. By leveraging this data, AIoT systems can gain insights into real-world phenomena, make intelligent decisions, optimize processes, enhance services, and improve user experiences (Nahr et al., 2021).