Innovative ways in which information technology can contribute to the understanding, management, and preservation of our environment. As the world faces escalating environmental challenges, the integration of informatics has become crucial for developing sustainable solutions.

• Sub-Track 1

  AI & ML in Environmental Monitoring and Sustainability

  This sub-track focuses on the application of artificial intelligence (AI) and machine learning (ML) techniques to address environmental challenges and promote sustainability. Participants are encouraged to explore innovative ways to leverage AI and ML technologies for monitoring environmental parameters, analyzing ecological data, predicting environmental trends, and developing sustainable solutions. Topics of interest include but are not limited to:

- Remote sensing and image analysis for environmental monitoring

- Data fusion and integration for environmental data analysis

- AI and ML for climate change modeling and prediction

- Natural language processing (NLP) for analyzing environmental policies and reports

- Optimization techniques for sustainable resource management

- AI and ML for biodiversity conservation and habitat protection

- Smart sensors and IoT devices for environmental data collection

- Blockchain and AI for enhancing transparency and accountability in environmental initiatives

- Case studies and real-world applications of AI and ML in environmental sustainability

- Citizen Science Integration

- AI-Driven Data Analysis

- Crowdsourced Data Annotation and Validation

- Ethical Considerations in Collaborative Monitoring

- Innovations in Data Visualization

• Sub-Track 2

  Informatics for Industry 5.0.

  Intersection of environmental informatics and the emerging paradigm of Industry 5.0. This sub-track explores how advanced information technologies can be applied to achieve sustainable and environmentally friendly practices within the industrial context.

- Smart Manufacturing and Sustainable Practices

- Environmental Monitoring in Industrial Settings

- Digital Twins for Environmental Impact Assessment

- Energy Efficiency and Green Computing

- Circular Economy and Supply Chain Sustainability

- Data-Driven Environmental Compliance

- Sustainable Innovation and Technological Adoption

- Environmental Informatics for Waste Management

- Life Cycle Assessment and Environmental Foot

• Sub-Track 3

  Business Intelligence for Green Decision-Making.

  Explores the integration of business intelligence (BI) tools and techniques to support environmentally conscious decision-making within organizations.

- Sustainable Business Intelligence Strategies

- Environmental Key Performance Indicators (KPIs) and Dashboards

- Decision Support Systems for Sustainable Investments

- Corporate Social Responsibility (CSR) Analytics

- Green Analytics for Compliance Management

- Supply Chain Transparency and Green Procurement

- Carbon Accounting and Emission Tracking

- Predictive Analytics for Environmental Impact Assessment

- Data-driven Sustainability Reporting