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ICMLSCI · Registering as Listener

International Conference on Machine Learning for Smart Cities and IoT

16th Mar – 17th Mar 2027 Mecca, Saudi Arabia Standard / Physical Participation

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ConferenceICMLSCI

ModeStandard / Physical

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Benefits of Registering as Listener

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Conference Session Tracks

SDG-Aligned Research Themes

International Conference on Machine Learning for Smart Cities and IoT conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 9 - Industry, Innovation and Infrastructure

SDG 11 - Sustainable Cities and Communities

This track focuses on the application of artificial intelligence in enhancing urban infrastructure. It will explore innovative AI solutions that improve the efficiency and sustainability of smart city systems.

This session will delve into advanced data science methodologies tailored for urban environments. Participants will discuss the role of data analytics in driving insights for smart city development.

This track highlights the integration of machine learning techniques within Internet of Things frameworks. It aims to showcase real-world applications that enhance IoT performance and functionality.

This session addresses the challenges and solutions related to real-time data monitoring in urban areas. It will cover technologies and methodologies that enable timely decision-making for city management.

This track explores the use of predictive analytics to maintain urban infrastructure effectively. Discussions will focus on methodologies that prevent failures and optimize resource allocation.

This session will examine the role of artificial intelligence in transforming urban transportation networks. It will cover innovations that enhance traffic management and improve user experiences.

This track focuses on strategies for optimizing energy consumption in urban settings through advanced analytics. Participants will discuss sustainable practices and technologies that contribute to energy efficiency.

This session will explore the deployment of edge computing solutions to enhance IoT applications in smart cities. It will highlight the benefits of processing data closer to the source for improved responsiveness.

This track addresses the complexities associated with managing and analyzing large datasets in urban contexts. Discussions will focus on innovative solutions to harness big data for effective city planning.

This session will explore advanced methodologies for detecting anomalies within IoT networks. Participants will discuss the implications of these techniques for maintaining system integrity and security.

This track focuses on the intersection of sustainability and technology in urban planning. It will explore how AI and data science can contribute to the development of resilient and sustainable urban systems.