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Our Research Focus

Our work is driven by the urgent need to modernize the water sector through intelligent digital solutions. We address core challenges in wastewater, drinking water, and infrastructure management by developing innovative, real-time, and data-driven approaches.

 

Directions

1. Real-Time GHG Reduction in Wastewater Treatment

Moving beyond static operational models, we develop concepts for real-time monitoring and estimation of greenhouse gas emissions. This enables proactive adjustment of treatment conditions to minimize emissions while ensuring compliance with effluent standards.

2. Smart Surveillance and Removal of Emerging Contaminants

Current methods for monitoring and removing Contaminants of Emerging Concern (CECs) are costly and slow. We focus on real-time surveillance across the treatment train, optimizing existing units to maximize removal without expensive new infrastructure.

3. CFD & Digital Modeling for Utility Optimization

While digital tools are commonplace in other industries, the water sector lags in adoption. We apply Computational Fluid Dynamics (CFD) and advanced modeling to optimize processes—for example, improving sedimentation tank efficiency by minimizing hydraulic short-circuiting and dead zones rather than relying solely on chemical additives.

4. Data-Enhanced Green Infrastructure

Green infrastructure is often designed for stormwater volume management. By integrating digital monitoring and predictive analytics, we enable these systems to also target pollution loads, significantly improving their environmental performance.

5. Rapid Detection of Microbiological Water Quality

Conventional microbiological testing is too slow for operational decision-making. We investigate surrogate parameters, hybrid sensors, and rapid methods to enable near real-time detection of contamination—critical for both treatment plants and vulnerable distribution networks.

6. Real-Time Water Quality Transparency for Consumers

As public expectations rise, monthly water quality reports are no longer sufficient. We develop affordable systems using digital sensors and AI to provide consumers with real-time access to water quality data, building trust and engagement.

7. Predictive Lifespan Assessment of Water Infrastructure

Replacing infrastructure based on manufacturer estimates or failure events is inefficient and risky. We use sensor data, AI, and predictive analytics to estimate the remaining useful life of pipes and assets, optimizing rehabilitation timing and reducing costs.

8. Advanced Process Optimization Through Real-Time Insight

Many treatment processes—from coagulation and filtration to aeration—operate below their potential. By combining real-time monitoring with deep process expertise, we identify actionable adjustments to improve accuracy, efficiency, and cost-effectiveness.

9. Evolving Research Agenda

Our research priorities adapt continuously to sector needs, technological advances, and our team’s growing expertise. We remain agile, exploring emerging challenges and opportunities to deliver impactful innovation.

 
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Projects

This page summarizes SWIQ’s ongoing projects. Since SWIQ was just established, we also list some of the previous projects of the team members.

Publications

This page summarizes SWIQ’s research production., Since SWIQ was just established, we also list some of the previous projects of the team members.