Applications invited for Developing Camera-Based AI Algorithms to Monitor Water Quality at Water and Wastewater Utilities

About the Grant

The Water Research Foundation (WRF) is inviting research proposals under its Research Priority Program to develop and validate cost-effective, camera-based Artificial Intelligence (AI) systems for monitoring water quality and operational conditions at drinking water and wastewater utilities. The research will explore how camera technologies, computer vision, and AI can support practical applications such as harmful algal bloom detection, turbidity monitoring, spill and foam detection, sludge quality assessment, and treatment process monitoring. The project aims to develop a practical and scalable framework that enables water and wastewater utilities to adopt camera-based AI technologies for more efficient and continuous operational monitoring.

Objectives of the Grant

The proposed research will focus on the following key objectives:

• Identify priority applications: Select 3–5 high-value applications across drinking water and wastewater utilities where camera-based AI can provide significant operational benefits.
• Evaluate camera technologies: Assess different camera platforms, ranging from RGB cameras to multispectral and hyperspectral systems, and determine their minimum technical requirements.
• Develop AI algorithms: Create and test computer vision and AI algorithms for selected water-quality and operational monitoring applications.
• Validate performance: Evaluate algorithm performance across different sites, lighting conditions, weather conditions, and deployment configurations and compare results with conventional operational measurements.
• Assess scalability: Determine whether AI models developed using one camera type or at one utility can be transferred to other locations with minimal retraining.
• Develop implementation pathways: Provide practical recommendations for utilities on adopting and scaling camera-based AI monitoring systems.

Background

• Water and wastewater utilities face increasing challenges in continuously monitoring water quality and operational conditions across geographically dispersed infrastructure.
• Traditional sensor networks can require significant investment, maintenance, and workforce resources. Camera-based systems combined with computer vision and AI may offer a more cost-effective approach to monitoring certain water-quality and treatment conditions.
• Potential applications include early detection of harmful algal blooms, turbidity events, spills, and foam, as well as monitoring treatment processes and sludge characteristics.

Research Approach

The research is expected to involve:

• A review of existing literature, camera technologies, AI approaches, and relevant WRF projects.
• Multi-site field demonstrations across drinking water and wastewater utilities.
• Development and testing of computer vision and AI algorithms.
• Evaluation of performance under different environmental and operational conditions.
• Validation against conventional water-quality and operational measurements.
• Assessment of technology and model transferability across utilities.
• Development of a framework for implementation, scalability, and practical adoption.

Expected Deliverables

The selected research team is expected to provide:

• A comprehensive Research Report following WRF's Research Report Template.
• An open-access publication and/or webcast and conference presentation.
• A Utility Guidance Framework covering technology selection, costs, workforce requirements, and an implementation roadmap.
• Technology Deliverables, potentially including open-source data, shareable AI algorithms, a project website, and interactive tools.

Eligibility

This opportunity is particularly relevant to organizations and research teams with experience in:

• Artificial Intelligence and Machine Learning
• Computer Vision
• Water and Wastewater Management
• Environmental Engineering
• Water Quality Monitoring
• Data Science
• Camera and Sensor Technologies
• Research and Technology Development

For more information, please check the link: Developing Camera-Based AI Algorithms to Monitor Water Quality at Water and Wastewater Utilities

Tags Innovations and Technology Livelihood Recycling and Waste Management Sustainable Development Goals (SDGs) Water Research