Background

Clean Water AI – Automated water quality analysis

Background

The idea behind Clean Water AI was to provide cities with an inexpensive, easy-to-install and easy-to-maintain means of automatically monitoring their existing water networks.

Most cities in developed countries purify their water by injecting chlorine into their water systems. This process is expensive to run and maintain, and most cities in developing countries cannot afford to have a chlorine-based water purification system. Furthermore, the traditional method of monitoring a water system, even in developed countries, involves using an analysis strip that indicates chemical and biological contaminants in water. These strips have to be analysed by maintenance staff. It is a costly and relatively slow process as the individuals have to travel to the different water supplies to carry out testing. Deployed on a large scale with lots of devices, Clean Water AI can be used to monitor water supply systems in near real time, identifying contaminants in minutes. The monitoring system can also be run remotely by a small number of people.

First of all, the IoT device collects a water sample and lets any potential bacteria grow. It then analyses the water quality for dangerous bacteria and harmful particles. The result is then stored in cloud storage and can be visualised, for example, on a dashboard. A dedicated dashboard still needs to be developed. Alternatively, end users can use an existing dashboard and connect this to the cloud storage.

The solution was developed after the CEO of Clean Water AI visited countries and cities where water supplies were of a poor quality. He decided he wanted to find a way to improve the situation. His analysis of countries capable of implementing the solution revealed that China was a good candidate as the water supply and purification systems used in the country’s cities were often poor. At the same time, China has the money and means to implement smart city solutions quite easily. He obtained a letter of intent from the City of Hangzhou. Due to the coronavirus situation, however, plans to further implement the project have come to a halt. The concept involved determining the quality of water in drinking fountains in places such as schools and hospitals. This would have been done by checking the quality of water coming from existing water filters and would have enabled public utility companies to use Clean Water AI as a tool for assessing the effectiveness of these filters.

Clean Water AI is a proof of concept and the software works. As an AI-based solution, it provides the added value of being an automated, near real-time monitoring facility which can be easily installed and maintained by cities. It is a primary classification tool that lets a water inspector decide whether they need to go to the specific node in their water supply system and look for the cause of contamination (for instance, a broken toilet that is leaking into the surrounding water pipes).

Clean Water AI is an independent start-up comprising two people who developed the project from idea to implementation in half a year with €170,000 of implementation costs. The esti-