[Paper Review] Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems

Maryam Nikpour, Parisa Behvand Yousefi+6 more|arXiv (Cornell University)|Jun 8, 2023

Air Quality Monitoring and Forecasting8 citations

TL;DR

The paper reviews IoT-based frameworks for smart city energy management and analyzes how intelligent analytics and machine learning can reduce energy use and environmental impact in smart buildings, while enabling third-party applications within the IoT platform.

ABSTRACT

This study confronts the growing challenges of energy consumption and the depletion of energy resources, particularly in the context of smart buildings. As the demand for energy increases alongside the necessity for efficient building maintenance, it becomes imperative to explore innovative energy management solutions. We present a comprehensive review of Internet of Things (IoT)-based frameworks aimed at smart city energy management, highlighting the pivotal role of IoT devices in addressing these issues due to their compactness, sensing, measurement, and computing capabilities. Our review methodology encompasses a thorough analysis of existing literature on IoT architectures and frameworks for intelligent energy management applications. We focus on systems that not only collect and store data but also support intelligent analysis for monitoring, controlling, and enhancing system efficiency. Additionally, we examine the potential for these frameworks to serve as platforms for the development of third-party applications, thereby extending their utility and adaptability. The findings from our review indicate that IoT-based frameworks offer significant potential to reduce energy consumption and environmental impact in smart buildings. Through the adoption of intelligent mechanisms and solutions, these frameworks facilitate effective energy management, leading to improved system efficiency and sustainability. Considering these findings, we recommend further exploration and adoption of IoT-based wireless sensing systems in smart buildings as a strategic approach to energy management. Our review underscores the importance of incorporating intelligent analysis and enabling the development of third-party applications within the IoT framework to efficiently meet the evolving energy demands and maintenance challenges

Motivation & Objective

• Assess IoT-based frameworks for smart city energy management.
• Identify how intelligent analysis and ML methods enhance monitoring, control, and efficiency.
• Evaluate the potential of IoT platforms to support third-party applications.
• Recommend adoption of IoT wireless sensing and intelligent analytics for sustainable energy management.

Proposed method

• Literature review of IoT architectures and frameworks for intelligent energy management.
• Analysis of frameworks that collect, store, and support intelligent analysis for monitoring and control.
• Evaluation of frameworks as platforms for third-party application development.
• Synthesis of findings on energy reduction and environmental impact.

Experimental results

Research questions

• RQ1 What IoT-based frameworks exist for intelligent energy management in smart buildings and cities?
• RQ2 How do intelligent analysis and ML methods within these frameworks improve energy efficiency and sustainability?
• RQ3 Can IoT platforms support third-party applications to extend functionality and adaptability?
• RQ4 What are the strategic recommendations for adopting IoT-based wireless sensing in smart buildings?
• RQ5 What is the potential impact of these frameworks on energy consumption and environmental footprint?

Key findings

• IoT-based frameworks show significant potential to reduce energy consumption and environmental impact in smart buildings.
• Intelligent mechanisms within IoT frameworks enable improved system efficiency and sustainability.
• IoT frameworks can serve as platforms for developing third-party applications, increasing utility and adaptability.
• Adoption of IoT-based wireless sensing systems is strategically advantageous for energy management in smart buildings.