Background
Water borne disease is a greater cause of death in developing countries than malaria, aids, war, and famine put together yet the problem receives little attention. The problem we seek to address is that of how to treat water in places where there is no spare money. We suggest the solution is zero-cost water analysis. Put simply we want to empower people with information about the condition of their drinking water.
Whiteside (whom inspired so much of this business plan) developed the idea of zero-cost systems. Zero-cost refers to the goal of devising systems where the cost of operating the system is as close to nothing as possible. Typical cost reduction involves looking at an existing solutions and trying to reduce the associated costs. In the zero-cost model, the problem is examined in reverse. One begins with the system’s goal and asks "what is the cheapest possible stuff that you could make… [the] system out of?”
In the medical field Whiteside developed a urine testing device made of paper that is roughly the size of a fingernail. Whiteside calls this a “microfluidic device” but is simply a small piece of paper, with indicators, a wax coating and colour printing. His microfluidic testing device does most of what a $30 test in Australia will do. The significant point of difference for Whiteside’s device is the test costs less than fifty cents. Once the microfluidic testing device has been used it is photographed using a camera phone and can be sent via the existing mobile phone network to an expert who interprets the results. This simple and low cost system can be used to diagnose diseases in real time.
In the field of water treatment we propose to develop a similar solution for zero-cost water analysis. We have a three key things working in our favour towards realising this objective.
First, we have the benefit of Whiteside’s research and development on urine and blood tests for medical purposes, as well as his considerable thought in relation to how such a system would work. This includes journal articles.
Second, for less than five cents it is already possible for a person to buy a test strip that will test the pH, alkalinity and chlorine content in water. This means water testing technology already has a very low cost base, suggesting it will be feasible to create a microfluidic testing system cheaply by combining existing testing technologies.
Third, we are working with water (c.f. blood or urine). This makes experimentation low cost and easy to conduct. Our preliminary research has shown water testing does not change according to location. We will still do a onsite test.
Fourth, we have a fantastic team. This is expanded on below in the Governance and Management section.
Whiteside (whom inspired so much of this business plan) developed the idea of zero-cost systems. Zero-cost refers to the goal of devising systems where the cost of operating the system is as close to nothing as possible. Typical cost reduction involves looking at an existing solutions and trying to reduce the associated costs. In the zero-cost model, the problem is examined in reverse. One begins with the system’s goal and asks "what is the cheapest possible stuff that you could make… [the] system out of?”
In the medical field Whiteside developed a urine testing device made of paper that is roughly the size of a fingernail. Whiteside calls this a “microfluidic device” but is simply a small piece of paper, with indicators, a wax coating and colour printing. His microfluidic testing device does most of what a $30 test in Australia will do. The significant point of difference for Whiteside’s device is the test costs less than fifty cents. Once the microfluidic testing device has been used it is photographed using a camera phone and can be sent via the existing mobile phone network to an expert who interprets the results. This simple and low cost system can be used to diagnose diseases in real time.
In the field of water treatment we propose to develop a similar solution for zero-cost water analysis. We have a three key things working in our favour towards realising this objective.
First, we have the benefit of Whiteside’s research and development on urine and blood tests for medical purposes, as well as his considerable thought in relation to how such a system would work. This includes journal articles.
Second, for less than five cents it is already possible for a person to buy a test strip that will test the pH, alkalinity and chlorine content in water. This means water testing technology already has a very low cost base, suggesting it will be feasible to create a microfluidic testing system cheaply by combining existing testing technologies.
Third, we are working with water (c.f. blood or urine). This makes experimentation low cost and easy to conduct. Our preliminary research has shown water testing does not change according to location. We will still do a onsite test.
Fourth, we have a fantastic team. This is expanded on below in the Governance and Management section.
The Solution
A working solution for a water testing system involves four main components:
Due to the fact that we are largely assembling existing technologies in novel ways we expect to have the system running within five months. On even our most pessimistic assumptions anticipate a working system to be up running within twelve months. Once this is established we would like to establish a statistical backend that records levels, such as pH, and looks for trends.
- A microfluidic testing device: that is a piece of paper specially designed for testing the water
- A portable capture device: in this case, it is simply a mobile phone with a built in camera
- A method of analysing the results (from the microfluidic testing device): To keep running costs low and scalability high we will develop an internet based software program to do this.
- A system to ensure testing is performed: the Business Model section discusses this.
Due to the fact that we are largely assembling existing technologies in novel ways we expect to have the system running within five months. On even our most pessimistic assumptions anticipate a working system to be up running within twelve months. Once this is established we would like to establish a statistical backend that records levels, such as pH, and looks for trends.
