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Assembling and programming a microcontroller that predicts the microbial quality of recycled water
The Sustainable Development Goals (SDGs) Target 6.2 calls for “access to adequate and equitable sanitation and hygiene for all” by 2030. Yet, substantial progress is needed to meet this goal: according to the WHO, 4.2 billion people did not have safely managed sanitation services and 3 billion lacked basic handwashing facilities in 2019.
One of the great challenges for the provision of adequate sanitation and hygiene services is to provide, process, and distribute sufficient quantities of safe water. On-site water reuse technologies can offer a flexible solution to improve access to such services in places with water scarcity or with insufficient water infrastructure.
Eawag has developed such a technology, the Water Wall, which recycles handwashing water in a closed loop, thus eliminating the need for a water and sewerage connection (more information on www.autarky.ch). The process by which the water is recycled takes several steps, thus ensuring that the water is safe for reuse. Field tests in Switzerland and South Africa have shown that the technology works well, but we have also observed that some system components can fail. This can lead to a water quality that is no longer safe for reuse.
For the implementation of water reuse technologies, such as the Water Wall, it is thus crucial that the microbial safety of the recycled water can be ensured at all times. This means that we need online monitoring and alarm systems that allow for direct intervention in case of treatment failures.
Keywords: WASH; Microcontroller; Programming
Based on experimental data gained during simulated disruptions of the Water Wall, we have developed machine-learning algorithms that predict the microbial quality of recycled water based on simple sensor measurements (for instance the oxidation-reduction potential or the free chlorine concentration). To develop the algorithms, we have collected sensor data and microbial indicators in the laboratory, and have then processed the data on a desktop PC. However, we have not yet implemented a system that directly reads in sensor data and issues an alarm if the water quality is not safe for reuse.
Based on experimental data gained during simulated disruptions of the Water Wall, we have developed machine-learning algorithms that predict the microbial quality of recycled water based on simple sensor measurements (for instance the oxidation-reduction potential or the free chlorine concentration). To develop the algorithms, we have collected sensor data and microbial indicators in the laboratory, and have then processed the data on a desktop PC. However, we have not yet implemented a system that directly reads in sensor data and issues an alarm if the water quality is not safe for reuse.
The goal of this MSc thesis is to assemble and program a microcontroller that reads in sensor data, predicts the microbial water quality of recycled water (based on the previously developed algorithms) and issues an alarm if the water is not safe.
The main tasks for this MSc thesis are:
- Define the main functionalities of the alarm system
- Select a suitable microcontroller (for instance an Arduino system) and hardware parts
- Write a program that reads in sensor data and predicts the microbial water quality (machine learning algorithms) issues some form of alarm (for instance a red light turning on, or an alarm SMS) if the water quality is not safe
- Test the microcontroller in the laboratory
These tasks only comprise the basic functionality of the microcontroller. Depending on your specific interests and skills, we could also think of additional features. Some ideas are:
- data storage on the microcontroller; remote access to the microcontroller
- data transfer from the microcontroller to a computer or smartphone
- data visualization on an app; sensor data treatment (for instance to detect outliers; physical set-up (for instance a custom-made water proof box)
-… and all ideas you might potentially have or develop during this MSc thesis!
In terms of project organisation, this research will be performed in the department of Process Engineering at Eawag (www.eawag.ch). Office space with computer and an existing experimental facility will be provided. Our sensor lab (https://www.eawag.ch/en/aboutus/working/researchenvironment/sensor-lab) is also here to support you.
Project period: 6 months, start date flexible
Language: English or German
The goal of this MSc thesis is to assemble and program a microcontroller that reads in sensor data, predicts the microbial water quality of recycled water (based on the previously developed algorithms) and issues an alarm if the water is not safe.
The main tasks for this MSc thesis are:
- Define the main functionalities of the alarm system
- Select a suitable microcontroller (for instance an Arduino system) and hardware parts
- Write a program that reads in sensor data and predicts the microbial water quality (machine learning algorithms) issues some form of alarm (for instance a red light turning on, or an alarm SMS) if the water quality is not safe
- Test the microcontroller in the laboratory
These tasks only comprise the basic functionality of the microcontroller. Depending on your specific interests and skills, we could also think of additional features. Some ideas are:
- data storage on the microcontroller; remote access to the microcontroller
- data transfer from the microcontroller to a computer or smartphone
- data visualization on an app; sensor data treatment (for instance to detect outliers; physical set-up (for instance a custom-made water proof box)
-… and all ideas you might potentially have or develop during this MSc thesis!
In terms of project organisation, this research will be performed in the department of Process Engineering at Eawag (www.eawag.ch). Office space with computer and an existing experimental facility will be provided. Our sensor lab (https://www.eawag.ch/en/aboutus/working/researchenvironment/sensor-lab) is also here to support you.
Project period: 6 months, start date flexible
Language: English or German
Prof. Elizabeth Tilley tilleye@ethz.ch
Eva Reynaert, eva.reynaert@eawag.ch
If you have any questions about the project or the requirements, or have ideas that you would like to discuss, please get in touch!
Prof. Elizabeth Tilley tilleye@ethz.ch
Eva Reynaert, eva.reynaert@eawag.ch
If you have any questions about the project or the requirements, or have ideas that you would like to discuss, please get in touch!
ETH for Development (ETH4D) aims to develop innovations that are directly relevant to improving the livelihoods of people in low-resource settings and to educate future leaders in sustainable development.