Hierarchical Resources Management System for Internet of Things-Enabled Smart Cities

Area of Science:

• Computer Science
• Urban Planning
• Electrical Engineering

Background:

• Efficient Internet of Things (IoT) system management is crucial for smart city development, sustainability, and resilience.
• Integrating diverse technologies in urban environments presents significant resource management challenges.

Purpose of the Study:

• To introduce a Hierarchical Resource Management System (HRMS) for IoT-enabled smart cities.
• To detail the Adaptive Resilient Node (ARN) for autonomous energy management and self-healing capabilities.
• To demonstrate the system's potential for enhancing urban sustainability and resilience.

Main Methods:

• Development of a decentralized HRMS architecture, scaling from building to city-wide applications.
• Integration of Adaptive Resilient Nodes (ARN) with self-healing functionalities.
• Implementation of lightweight inter-node communication for workload balancing and responsiveness.

Main Results:

• The HRMS supports real-time decision-making, fault tolerance, and scalable resource allocation.
• Experimental evaluations indicate up to a 50% improvement in energy efficiency.
• A 30% reduction in system downtime was observed across various urban settings.

Conclusions:

• The proposed HRMS offers a transformative approach to urban energy management in smart cities.
• The system's hierarchical and decentralized design enhances efficiency, resilience, and sustainability.
• HRMS demonstrates significant potential for advancing smart city infrastructure and operations.