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ICDSSC · Registering as Listener

International Conference on Data Science for Smart Cities and IoT

8 - 9 May 2027 Berlin, Germany Standard / Physical Participation
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$115
virtual · $175 in person
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Registration summary

ConferenceICDSSC
ModeStandard / Physical
ParticipationListener
Registration fee$175.00
Bank charges (5.8%)$10.15
Total payable$185.15
Includes all bank processing charges — the amount above is exactly what will be charged.

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• Conference Session Tracks •
SDGs
SDG-Aligned Research Themes

ICDSSC conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 4 - Quality Education SDG 9 - Industry, Innovation and Infrastructure SDG 11 - Sustainable Cities and Communities SDG 16 - Peace, Justice and Strong Institutions
01 Mathematical Foundations of Data Science +
This track focuses on the theoretical underpinnings of data science, emphasizing mathematical models and statistical methods. Participants will explore advanced topics such as probability theory, linear algebra, and optimization techniques relevant to data analysis.
02 Machine Learning Algorithms for Smart Cities +
This session will delve into the application of machine learning algorithms specifically designed for urban environments. Topics will include predictive modeling, classification techniques, and the integration of AI in city infrastructure management.
03 Big Data Analytics in Urban Systems +
This track examines the challenges and solutions associated with big data analytics in the context of urban systems. Participants will discuss data integration, processing techniques, and the role of analytics in enhancing city services.
04 IoT and Sensor Data Processing +
Focusing on the intersection of IoT and data science, this session will explore methods for processing and analyzing data generated by sensors in smart cities. Topics will include real-time data analytics, data fusion, and the implications for urban planning.
05 Cloud and Edge Computing for Data Science +
This track addresses the role of cloud and edge computing in facilitating data science applications for smart cities. Discussions will center on architecture, scalability, and the trade-offs between centralized and decentralized data processing.
06 Statistical Methods for Urban Infrastructure Analysis +
This session will highlight statistical techniques used to analyze and optimize urban infrastructure systems. Participants will engage with case studies that illustrate the application of statistical modeling in transportation, utilities, and public services.
07 Predictive Modeling in Smart City Applications +
This track will explore the development and implementation of predictive models tailored for smart city applications. Emphasis will be placed on forecasting urban trends, resource allocation, and decision-making processes.
08 Data Ethics and Governance in Smart Cities +
This session will address the ethical considerations and governance frameworks surrounding data use in smart cities. Discussions will focus on privacy, data ownership, and the implications of data-driven decision-making.
09 Urban Systems Optimization through Data Science +
This track will investigate optimization techniques applied to urban systems using data science methodologies. Participants will discuss algorithms and strategies for enhancing efficiency in transportation, energy use, and waste management.
10 Interdisciplinary Approaches to Data Science in Smart Cities +
This session will highlight the importance of interdisciplinary collaboration in advancing data science applications for smart cities. Participants will share insights from fields such as urban planning, environmental science, and public policy.
11 Emerging Trends in Data Science for IoT +
This track will explore the latest trends and innovations in data science as applied to IoT technologies. Discussions will include advancements in machine learning, data visualization, and the future of smart city ecosystems.