Researchers at IIT-Hyderabad are working on developing smartphone based sensors to detect adulteration in milk
Open an application in your smart phone and may be detecting on change of color or pH value of the milk your mobile phone will be able to tell you whether your milk is safe to consume or not! Whether it is milked from a cow or manufactured in a factory! Yes, IIT Hyderabad researchers are working on developing a smartphone based system that will be able to catch adulteration in your milk. The detector system measures acidity in milk using an indicator paper that changes color according to acidity. They have also developed algorithms that can be incorporated on to a smartphone to accurately detect the color change.
Working on Easy-To-Use & Low Cost device
IIT Professor Shiv Govind Singh, heading the research team, said, "While techniques such as chromatography and spectroscopy can be used to detect adulteration, such techniques generally require expensive set up and are not amenable to miniaturization into low-cost easy-to-use devices. Hence, they do not appeal to the vast majority of milk consumers in the developing world."
"We need to develop simple devices that the consumer can use to detect milk contamination. It should be possible to make milk adulteration detection fail safe by monitoring all of these parameters at the same time, without the need for expensive equipment," he said.
Detection will work using smart phone camera
In the process of development of this equipment the research team first developed a sensor-chip based method for measuring pH level, an indicator of the acidity. They used a process called "electrospinning" to produce paper-like material made of nano sized nylon fiber, loaded with a combination of three dyes. The paper is "halochromic" which changes color in response to changes in acidity.The researchers have developed a prototype smart phone-based algorithm, in which, the colors of the sensor strips after dipping in milk are captured using the phone camera, and the data is transformed into pH range.
"The team will extend the research to study the effects of mobile phone cameras and lighting on detection efficiency."
"We have used three machine-learning algorithms and compared their detection efficiencies in classifying the color of the indicator strips. On testing with milk spiked with various combinations of contaminants, we found near-perfect classification with accuracy of 99.71 per cent," Mr Singh said.
"The team will extend the research to study the effects of mobile phone cameras and lighting on detection efficiency.
"In the long run, we hope to develop sensors for other physical properties such as conductivity and refractive index and integrate it with the pH detection unit to obtain comprehensive milk quality check systems that can be easily deployed by the consumer using mobile phones and other hand-held devices," he said.