International Conference on Spatiotemporal Data Analysis in Engineering

ICSD-AE

28th Apr – 29th Apr 2027 Izmir, Turkey

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Registration Summary

Conference ICSD-AE

Date 28th Apr – 29th Apr 2027

Location Izmir, Turkey

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

Calculated based on 5.8% of the registration fee

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Total Payable USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Advancements in Predictive Modeling Techniques +

This track focuses on the latest methodologies in predictive modeling within engineering contexts. Researchers are invited to present their findings on novel algorithms and frameworks that enhance predictive accuracy and efficiency.

SDG 9 SDG 12

02 Supervised and Unsupervised Learning Applications +

This session explores the application of supervised and unsupervised learning techniques in engineering data analysis. Contributions should highlight innovative approaches to feature extraction and model training in complex datasets.

SDG 4 SDG 9

03 Deep Learning Innovations for Engineering Data +

This track emphasizes the role of deep learning in processing and analyzing engineering data. Papers should discuss new architectures and techniques that address challenges in spatiotemporal data analysis.

SDG 9 SDG 11

04 Anomaly Detection in Engineering Systems +

This session is dedicated to methodologies for detecting anomalies in engineering systems using spatiotemporal data. Researchers are encouraged to present case studies and theoretical advancements that improve anomaly identification.

SDG 9 SDG 16

05 Time Series Analysis in Engineering Applications +

This track examines the techniques and challenges associated with time series analysis in various engineering domains. Submissions should focus on innovative methods for forecasting and trend analysis in time-dependent data.

SDG 9 SDG 13

06 Geospatial Analytics in Engineering +

This session highlights the integration of geospatial analytics in engineering projects. Papers should address the use of spatial data in decision-making processes and the implications for infrastructure and resource management.

SDG 11 SDG 13

07 Sensor Data Processing and Analysis +

This track focuses on the methodologies for processing and analyzing sensor data in engineering applications. Contributions should explore techniques for data cleaning, integration, and real-time analytics.

SDG 9 SDG 12

08 Predictive Maintenance Strategies Using Data Science +

This session is dedicated to the development of predictive maintenance strategies leveraging data science techniques. Researchers are invited to share insights on improving maintenance schedules and reducing downtime through data-driven approaches.

SDG 9 SDG 12

09 Industrial IoT and Data Fusion Techniques +

This track explores the intersection of industrial IoT and data fusion techniques in engineering. Papers should focus on the integration of diverse data sources to enhance operational efficiency and decision-making.

SDG 9 SDG 12

10 Model Evaluation and Performance Metrics +

This session addresses the critical aspects of model evaluation and the development of performance metrics in engineering applications. Contributions should discuss best practices and innovative approaches to assess model reliability and validity.

SDG 9 SDG 16

11 Simulation Analytics for Engineering Insights +

This track focuses on the role of simulation analytics in deriving insights from engineering data. Researchers are encouraged to present methodologies that enhance simulation accuracy and applicability in real-world scenarios.

SDG 9 SDG 12