This track focuses on the latest advancements in bioprocess engineering for water and waste management. It aims to explore novel biotechnological approaches that enhance efficiency and sustainability in treatment processes.

This session will delve into the application of predictive modeling techniques in optimizing water treatment processes. Participants will discuss methodologies that leverage machine learning to forecast system performance and improve decision-making.

This track highlights the integration of supervised and unsupervised learning techniques in waste engineering. It will cover case studies that demonstrate the effectiveness of these methods in resource recovery and waste management.

This session will address the challenges and solutions related to anomaly detection in environmental monitoring systems. Attendees will explore advanced algorithms that enhance the reliability of monitoring data in biotechnological applications.

This track will focus on innovative feature extraction methods used to assess water quality. Discussions will include the role of these techniques in improving the accuracy of predictive models and monitoring systems.

This session aims to explore the role of automation in streamlining workflows within waste management systems. Participants will share insights on how automation can enhance operational efficiency and reduce human error.

This track will examine the impact of Industrial Internet of Things (IoT) technologies on water management practices. It will highlight case studies showcasing the integration of IoT for real-time monitoring and data-driven decision-making.

This session will focus on innovative strategies for resource recovery in biotechnological applications. Discussions will include methods that enhance the sustainability and economic viability of waste-to-resource processes.

This track will explore the application of deep learning techniques in optimizing bioprocesses for water and waste engineering. Participants will discuss how these advanced methodologies can lead to significant improvements in operational performance.

This session will investigate the use of digital twin technologies for simulating and optimizing water systems. Attendees will explore how digital twins can enhance system monitoring and predictive maintenance efforts.

This track will focus on the role of simulation and analytics in enhancing waste engineering practices. Participants will discuss various analytical frameworks that support effective decision-making and process improvements.