Smart cities: the role of Internet of Things and machine learning in realizing a data-centric smart environment

Published in

(2023)

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TL;DR

An overview of smart cities’ various applications and the challenges associated with implementing IoT and machine learning in urban environments are presented and the findings suggest these technologies have the potential to transform urban environments and enable the creation of more livable, sustainable, and efficient cities.

Abstract

This paper explores the concept of smart cities and the role of the Internet of Things (IoT) and machine learning (ML) in realizing a data-centric smart environment. Smart cities leverage technology and data to improve the quality of life for citizens and enhance the efficiency of urban services. IoT and machine learning have emerged as key technologies for enabling smart city solutions that rely on large-scale data collection, analysis, and decision-making. This paper presents an overview of smart cities’ various applications and discusses the challenges associated with implementing IoT and machine learning in urban environments. The paper also compares different case studies of successful smart city implementations utilizing IoT and machine learning technologies. The findings suggest that these technologies have the potential to transform urban environments and enable the creation of more livable, sustainable, and efficient cities. However, significant challenges remain regarding data privacy, security, and ethical considerations, which must be addressed to realize the full potential of smart cities.

Authors

Amin Ullah

1 papers

Syed Myhammad Anwar

1 papers

Jianqiang Li

1 papers

References65 items

Smart City: Recent Advances in Intelligent Street Lighting Systems Based on IoT

The Role of ML, AI and 5G Technology in Smart Energy and Smart Building Management

Hybrid‐driven‐based fuzzy secure filtering for nonlinear parabolic partial differential equation systems with cyber attacks

Proposing a hybrid metaheuristic optimization algorithm and machine learning model for energy use forecast in non-residential buildings

A Review on 5G Technology for Smart Energy Management and Smart Buildings in Singapore

Smart cities: the role of Internet of Things and machine learning in realizing a data-centric smart environment

Published in

(2023)

External Links:

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TL;DR

Abstract

Authors

Amin Ullah

1 papers

Syed Myhammad Anwar

1 papers

Jianqiang Li

1 papers

References65 items

Smart City: Recent Advances in Intelligent Street Lighting Systems Based on IoT

The Role of ML, AI and 5G Technology in Smart Energy and Smart Building Management

Hybrid‐driven‐based fuzzy secure filtering for nonlinear parabolic partial differential equation systems with cyber attacks

Proposing a hybrid metaheuristic optimization algorithm and machine learning model for energy use forecast in non-residential buildings

A Review on 5G Technology for Smart Energy Management and Smart Buildings in Singapore

Lubna Nadeem

1 papers

Tariq Mahmood

1 papers

Amjad Rehman

1 papers

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TL;DR

Abstract

Authors

References65 items

Smart City: Recent Advances in Intelligent Street Lighting Systems Based on IoT

The Role of ML, AI and 5G Technology in Smart Energy and Smart Building Management

Hybrid‐driven‐based fuzzy secure filtering for nonlinear parabolic partial differential equation systems with cyber attacks

Proposing a hybrid metaheuristic optimization algorithm and machine learning model for energy use forecast in non-residential buildings

A Review on 5G Technology for Smart Energy Management and Smart Buildings in Singapore

TL;DR

Abstract

Authors

References65 items

Smart City: Recent Advances in Intelligent Street Lighting Systems Based on IoT

The Role of ML, AI and 5G Technology in Smart Energy and Smart Building Management

Hybrid‐driven‐based fuzzy secure filtering for nonlinear parabolic partial differential equation systems with cyber attacks

Proposing a hybrid metaheuristic optimization algorithm and machine learning model for energy use forecast in non-residential buildings

A Review on 5G Technology for Smart Energy Management and Smart Buildings in Singapore

Smart city and cyber-security; technologies used, leading challenges and future recommendations

An intelligent fault detection approach based on reinforcement learning system in wireless sensor network

Drone Deep Reinforcement Learning: A Review

COVID-19 cases prediction by using hybrid machine learning and beetle antennae search approach

Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions

Applications of Artificial Intelligence and Machine learning in smart cities

Smart city big data analytics: An advanced review

Manufacturing process data analysis pipelines: a requirements analysis and survey

High-performance medicine: the convergence of human and artificial intelligence

The practical implementation of artificial intelligence technologies in medicine

Artificial intelligence and deep learning in ophthalmology

Applying Deep Learning to Individual and Community Health Monitoring Data: A Survey

Design, Implementation and Practical Evaluation of an IoT Home Automation System for Fog Computing Applications Based on MQTT and ZigBee-WiFi Sensor Nodes

Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration

A fuzzy inference- fuzzy analytic hierarchy process-based clinical decision support system for diagnosis of heart diseases

Mobile and pervasive computing technologies and the future of Alzheimer’s clinical trials

Smart technology in the home: time for more clarity

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

Neural network models for supporting drug and multidrug resistant tuberculosis screening diagnosis

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A deep convolutional neural network model to classify heartbeats

Pre-trained convolutional neural networks as feature extractors for tuberculosis detection

Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks.

Medical image retrieval using deep convolutional neural network

Fog Computing for Sustainable Smart Cities

Dermatologist-level classification of skin cancer with deep neural networks

Knowledge Mining Approach For Healthy Monitoring From Pregnancy Data With Big Volumes

Smart street lighting system: A platform for innovative smart city applications and a new frontier for cyber-security

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Non-invasive hypoglycemia monitoring system using extreme learning machine for Type 1 diabetes.

Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

Securing Metering Infrastructure of Smart Grid: A Machine Learning and Localization Based Key Management Approach

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CAViaR

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Big Data Analytics Embedded Smart City Architecture for Performance Enhancement through Real-Time Data Processing and Decision-Making

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