ArticleSensors (Basel, Switzerland)2025
Hierarchical Resources Management System for Internet of Things-Enabled Smart Cities.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Enhancing internet of things intrusion detection through high-performance boosting ensemble learning.Scientific reports · 2026Article
- A Blockchain-Enhanced Neural Network Framework for secure e-waste forecasting in smart cities.Frontiers in public health · 2026Article
- EnergiQ: A Prescriptive Large Language Model-Driven Intelligent Platform for Interpreting Appliance Energy Consumption Patterns.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The efficient management of IoT systems is fundamental to advancing smart cities while enabling the seamless integration of technologies that enhance urban sustainability and resilience. This paper introduces a Hierarchical Resource Management System (HRMS) tailored for IoT-enabled smart cities, emphasizing a decentralized architecture at the building level and scaling up to city-wide applications. At its core, the system integrates the Adaptive Resilient Node (ARN), designed to autonomously manage energy resources and ensure continuous operation through self-healing capabilities. This study outlines the HRMS architecture, operational workflows, and core functionalities, demonstrating how the hierarchical framework supports real-time decision-making, fault tolerance, and scalable resource allocation. The proposed system's lightweight inter-node communication enhances workload balancing and system responsiveness, addressing critical challenges in urban energy management. Experimental evaluations show that the system achieves up to a 50% improvement in energy efficiency and a 30% reduction in downtime across various urban environments, highlighting its transformative potential for sustainable and resilient urban growth.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.