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IoT Applications for Intelligent Resource Management Systems

Author(s) Dr. Ethan Richardson
Country New Zealand
Abstract The Internet of Things (IoT) has emerged as an important technological foundation for intelligent resource management by enabling continuous sensing, communication, monitoring, and analysis of physical and operational resources. The integration of IoT sensors with artificial intelligence, machine learning, edge computing, cloud platforms, and data analytics allows organizations to monitor resource utilization and develop more responsive management strategies. This study examines IoT applications for intelligent resource management systems, focusing on real-time sensing, resource monitoring, data analytics, predictive management, automation, energy optimization, and intelligent allocation.
A qualitative descriptive and conceptual research design was adopted using secondary academic literature. The analysis indicates that IoT-enabled resource management can improve the utilization of energy, water, materials, equipment, agricultural resources, transportation assets, and organizational infrastructure. Continuous sensor data can identify consumption patterns, detect abnormal conditions, estimate future requirements, and support timely allocation decisions. Edge computing can provide rapid local processing, while cloud platforms enable large-scale data storage and analytical operations. Artificial intelligence can further support predictive demand estimation, anomaly detection, and automated resource optimization.
Despite these capabilities, challenges related to data quality, interoperability, cybersecurity, privacy, energy consumption, scalability, and system complexity remain significant. The study concludes that IoT applications can strengthen resource management by connecting physical resources with intelligent monitoring and decision-making mechanisms. Future research should emphasize adaptive resource allocation, AI-enabled optimization, energy-efficient IoT architectures, secure data management, edge intelligence, interoperability, and sustainable resource utilization.
Keywords Internet of Things, Resource Management, Intelligent Systems, IoT Applications, Resource Optimization, Artificial Intelligence, Machine Learning, Smart Systems, Edge Computing, Sustainable Management
Field Engineering
Published In Volume 5, Issue 6, November-December 2023
Published On 2023-12-10
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