International Conference on Data Analytics for Sustainability and Engineering Technology (DASET)

About the Conference

The International Conference of Data Analytics for Sustainability and Engineering Technology (DASET) aims to bring together researchers, practitioners, and experts from academia and industry to discuss and exchange cutting-edge research and innovations in the fields of data analytics, sustainability, and engineering technology. The conference seeks to explore the applications of data analytics in promoting sustainability across various domains and leveraging engineering technology to address global challenges.

Technical Tracks and Topics:

Data Analytics for Sustainability

Environmental data analysis
Sustainable energy analytics
Climate change data modeling
Water resource management
Sustainable agriculture analytics

Engineering Technology for Sustainable Development

Renewable energy technologies
Sustainable infrastructure development
Green building technologies
Sustainable transportation systems
Waste management technologies

Big Data and Machine Learning Applications

Big data analytics for sustainability
Machine learning for environmental monitoring
Predictive analytics for sustainable practices
Data-driven decision-making for sustainability
Energy efficiency optimisation using data analytics

Smart Cities and IoT

IoT applications for environmental monitoring
Smart city infrastructure for sustainability
Data analytics for smart transportation systems
IoT-enabled energy management
Sustainable urban planning using data analytics

Big Data for Sustainability and Innovation

Sustainable Project management for construction
Smart Cities
Construction Innovation
Facilities Management
Impact of COVID-19 on the Construction Sector
CSR in the construction sector
Construction and Building Technologies.
Sustainability and Energy Saving Methods and Technologies.
Construction Management technologies.
Virtual Reality Technologies and Applications.
Big Data Analysis Architectures
Big Data Analysis for Business Model Innovation

Data Analytics in Marketing for Engineering Industries

Data-driven marketing strategies for engineering products
Customer segmentation and targeting in engineering industries
Predictive analytics for marketing campaign optimisation
Market trend analysis using data analytics
Decision models for pricing strategies in engineering sectors
Marketing performance measurement through data analytics

Human Resource Analytics in Engineering Projects

Predictive analytics for talent acquisition and retention in engineering firms
Employee performance evaluation using data-driven models
Workforce planning and optimisation through data analytics
Decision models for training and development programs in engineering organisations
Human resource analytics for diversity and inclusion initiatives
Employee engagement and satisfaction analysis using data-driven approaches

Sustainable Strategies in Green Engineering

Project risk assessment and management using decision models
Data analytics for project scheduling and resource allocation
Decision-making in engineering project portfolio management
Cost-benefit analysis and optimisation in engineering projects
Decision support systems for project management in engineering
Performance evaluation and project success prediction using data analytics

Ethical and Legal Considerations

Ethical considerations in data-driven decision-making processes in engineering
Legal implications of using data analytics in engineering decision making
Privacy and data protection issues in engineering data analytics
Bias and fairness in algorithmic decision-making in engineering
Compliance and regulatory challenges in using data analytics in engineering practices
Ethical frameworks for responsible AI and machine learning applications in engineering

Keynote Speakers

Dr. Antonio Luque

Associate Professor, University of Seville, Spain; Director, IEEE Region 8

aluque@ieee.org

Bio

Professor Vincenzo Piuri

University of Milan; IEEE Fellow; ACM Distinguished Scientist

vincenzo.piuri@unimi.it

Bio

Professor Ahmad Elragal

Luleå University of Technology, Sweden; ACU, Egypt

ahmed.elragal@guc.edu.eg

Bio

Submission Guidelines and Important Dates

Activity	Deadline
Full Paper Submission	1 November 2025
Notification of Acceptance	1 December 2025
Final Paper Submission	15 December 2025
Conference Dates	15 + 16 January 2026

All papers should be a maximum of five pages in IEEE format.
Papers must be submitted online.
Accepted submissions will be included in IEEE Xplore and indexed by Scopus.

Hosting Institution

This conference is proudly hosted by Al-Maktoum College of Higher Education, UK, in collaboration with international academic and professional partners.