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Course Description

This 5-day program provides an in-depth overview of artificial intelligence applications in water infrastructure maintenance, including predictive maintenance, smart monitoring, and operational optimization. Participants will explore sensor technologies, IoT integration, machine learning algorithms, data collection and management, and AI-based decision-making tools. The course also examines fault detection, leak prediction, asset performance modeling, and water network optimization. Participants will understand how AI and data-driven approaches can improve efficiency, reduce costs, enhance reliability, and support sustainable water management practices.

Course Objectives

Upon completion of this course, participants will be able to:

  • Understand the principles of AI and machine learning relevant to water infrastructure.
  • Implement data collection, IoT integration, and sensor technologies for monitoring.
  • Apply predictive maintenance and fault detection techniques.
  • Use AI models for optimizing water distribution, pumping, and treatment operations.
  • Analyze performance metrics to improve operational efficiency and sustainability.
  • Integrate AI tools into water asset management and decision-making workflows.

Who Should Attend?

This course is designed for water utility engineers, maintenance managers, GIS specialists, data analysts, municipal infrastructure planners, and technical professionals responsible for operational efficiency, asset management, or smart water systems.

Course Agenda

Registration

Welcome & Introduction

Pre-Test

Day 1: Introduction to AI and Water Infrastructure

  • Overview of AI, machine learning, and predictive analytics
  • Introduction to water infrastructure systems: pipelines, treatment plants, pumping stations
  • Challenges in maintenance and monitoring
  • Opportunities for AI-driven solutions

Day 2: Data Collection, Sensors, and IoT Integration

  • Sensor technologies for water monitoring (flow, pressure, quality)
  • IoT and SCADA integration
  • Data management and preprocessing for AI models
  • Data quality, cleaning, and storage
Day 3: Machine Learning and Predictive Maintenance
  • Fundamentals of predictive modeling for infrastructure assets
  • Fault detection and anomaly identification
  • Predictive maintenance strategies for water networks
  • Evaluating model performance and reliability
Day 4: AI for Water Network Optimization

  • Optimizing pump operations and energy usage
  • Leak detection and water loss minimization
  • Simulation and modeling of water distribution networks
  • Decision-support systems for maintenance and operations
Day 5: Applications, Case Studies, and Future Trends

  • Real-world case studies of AI in water infrastructure
  • Integrating AI into strategic asset management
  • Emerging trends: smart water networks, digital twins, and sustainable water management
  • Program review, key takeaways, and action planning

Post Test

End of the Course

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.