Artificial Intelligence-Based Semantic Internet of Things in a User-Centric Smart City

Area of Science:

• Computer Science
• Artificial Intelligence
• Internet of Things

Background:

• Smart cities (SC) rely on technologies to meet citizen demands.
• Internet of Things (IoT) is crucial for SC connectivity but faces challenges with heterogeneous devices and data analysis.
• Interoperability issues arise from diverse manufacturers and product standards in IoT devices.

Purpose of the Study:

• To propose a novel artificial intelligence-based semantic IoT (AI-SIoT) hybrid service architecture.
• To integrate heterogeneous IoT devices for enhanced intelligent services in smart cities.
• To address challenges in data analysis and service provision for smart city applications.

Main Methods:

• Development of an AI-SIoT hybrid service architecture.
• Leveraging semantic and artificial intelligence (AI) technologies for device integration.
• Implementing efficient data analysis and decision-making capabilities for service provisioning.

Main Results:

• The proposed AI-SIoT architecture enables flexible connections among heterogeneous IoT devices.
• AI technology facilitates efficient data analysis and accurate decision-making for smart city services.
• Demonstration of practical use cases highlighting the architecture's applicability.

Conclusions:

• The AI-SIoT architecture effectively integrates diverse IoT devices for smart city applications.
• Semantic and AI technologies are key enablers for intelligent and flexible smart city services.
• Discussion of opportunities and challenges for implementing AI-SIoT in future smart cities.