Autonomous Systems in Smart Cities
Submission deadline: 2024-06-30
Section Collection Editors

Section Collection Information

Dear Colleagues,


Automated smart city applications encompass various technologies and innovations designed to improve the quality of life, sustainability, efficiency, and services within urban environments. Smart applications for environmental sustainability is a concept that refers to the development and implementation of advanced technological solutions that integrate environmental sustainability principles. The aim is to leverage technology to reduce environmental impact and improve resource efficiency while advancing innovation and economic growth. Smart cities require self-adaptive and fault-tolerant systems to continuously increase the quality, productivity, compliance, and sustainability of smart services.

 

Smart computing is an important multi-disciplinary area where advanced computational methods and technologies are combined with engineering approaches to create systems, applications and new services that meet the needs of society. These applications, often interconnected, rely on sensor-based data collection, analysis, and the integration of various technologies including the Internet of Things (IoT), Deep Learning (DL), privacy and security, communication networks, Cyber-Physical Systems (CPS), edge computing, Artificial Intelligence (AI), cognitive computing, neuromorphic computing and software systems. Smart city applications can be found in different domains such as transportation, city management, connected communities, finances, healthcare, entertainment, disaster management and social media.

 

This platform aims to explore novel, cutting-edge, and creative research in emerging trends and innovative solutions to green and smart cities. We look forward to receiving your contributions to research articles and reviews in this area of study.

 

Prof. Dulani Medeniya

Section Editor

Keywords

Intelligence Systems; Edge Computing; Resource-Constrained Devices; Energy Efficiency; Low Cost; Night Vision; Artificial Intelligence; Deep Learning, Internet of Things

Published Paper