Development of an automated, power-efficient & field-worthy warning system for arresting water wastages using IoT and machine learning

Pakistan is facing an impending water crisis linked both with its quantity and quality. So having crossed water stress line in 1990 and water scarcity line in 2005, Pakistan Council of Research in water resources has marked 2025 as the year in which Pakistan may run out of its fresh water resou

Project Title

Development of an automated, power-efficient & field-worthy warning system for arresting water wastages using IoT and machine learning

Project Area of Specialization

Internet of Things

Project Summary

Pakistan is facing an impending water crisis linked both with its quantity and quality. So having crossed water stress line in 1990 and water scarcity line in 2005, Pakistan Council of Research in water resources has marked 2025 as the year in which Pakistan may run out of its fresh water resources. This grim situation entails the use of smart solutions to monitor and advertise water consumption trends for consumer awareness and enhance its utilization efficiency through automated management and control systems.
So with the same motivation, at College of Aeronautical Engineering (CAE), an IoT driven water management system is being developed through automated means to sense and collect critical information regarding the (consumption) of water distribution. This system will be plug and play that can be used by any individual with zero technical background. The analytics performed over collected data were utilized
to trigger real-time alerts to all concerned through IoT controllers. These alerts can help to adopt suitable remedial measures proactively by isolating water leakages. Algorithms will also be developed for anomaly detection to arrest excessive water consumption and water leakages and pin pointing sources of abnormalities in real time.

Project Objectives

1. Accumulation data of water consumption over cloud

2. Performing statistical analysis and application of machine learning algorithms.

3. Making a automated, cost efficient & field worthy, plug and play product that can be installed anywhere.

4. It would make the consumption profiles and learn from them. If any anomaly is detected in the pattern, it would timely stop  the flow and generate alerts.

5. It would also helps to develop a system based on "Pay per usage of water" 

6. It would also be able to distribute accurate amount of water at distribution points for better management of resource

Project Implementation Method

1. Installation of Flow sensors at main distribution points inside a building. 

2. Using NodeMCU or suitable gateway, sending data to cloud.

3. Aggregating data over cloud and applying statistical analysis over that aggregated data.

4. Automate the system that would be able to manage the resource autonomously.

5. Application of Recurrent Neural Network for forcasting the demands.

6. By the use of gateways and solenoid valves, remotely stop or pass accurate amount of water, in short efficient use of water would be possible

Benefits of the Project

Pakistan is now a severely water-stressed country. But while everyone is vocally concerned about the scarcity of water and obsessed with constructing large dams, we continue to squander the resource we already have.  With a projected population of 263 million in the year 2050, Pakistan needs to put serious thought into how it will provide adequate water for agriculture, industry, and human consumption in the face of rapidly dwindling reserves.

Meanwhile, the water reaching the end user has also decreased due to further losses along the way. Our water management practices are highly inefficient. With the help of this project, we can identify how much water is utilized at which place, timely manage the anomalies and stop remotely if there is any leakage or wastage of water.

This project in short will going to prove a cost effective solution in forthcoming drought 

Technical Details of Final Deliverable

1.Design and Implementation of an IoT enabled sensor network for monitoring of water consumption parameters at suitable distribution points inside CAE building.

2.Aggregating collected data over extended period on local/cloud server.

3.Creating consumption profile by applying statistical learning over the collected data.

4.Establishing consumption trends based on the collected data.

5.Developing algorithms for anomaly detection to arrest excessive water consumption and water leakages and pin pointing sources of abnormalities in real time.

6. Implementation of machine learning algorithm for forcasting and managing usage of water.

7. Make a field worthy plug and play product that can be installed anywhere.

Final Deliverable of the Project

HW/SW integrated system

Type of Industry

IT , Agriculture , Food , Finance , Others , Health

Technologies

Internet of Things (IoT), Cloud Infrastructure, Shared Economy

Sustainable Development Goals

Good Health and Well-Being for People, Clean Water and Sanitation, Decent Work and Economic Growth, Responsible Consumption and Production, Life on Land

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com