Swapnil Sayan Saha and Sadman Siraj’s dual efforts bring successful results after a year
Two students of Dhaka University (DU) have made a breakthrough innovation in the formalin detection mechanism arena by developing a portable formalin detection device called Food Alytics.
This new local device costs only Tk1,000 each. It is capable of accurately determining the artificial formalin concentration in food items at all temperatures and humidity, and has been designed in such a fashion that it would accurately determine whether the formalin present in food items is harmful for the human body or not.
A year-long research project
Swapnil Sayan Saha, a fourth-year student of the Department of Electrical and Electronic Engineering (EEE), and third-year student Sadman Siraj, have deftly developed a cheaper formalin detection kit by working relentlessly on this research project for an entire year.
“The striking feature of the device is its ability to differentiate between artificial (harmful) and natural (harmless)formalin with accuracy using machine learning algorithms”, remarked the team leader of the project, Swapnil.
Addressing the 2014 report of Bangladesh Council for Scientific and Industrial Research, Swapnil told BSS:“The Z300 was not only found faulty, it was also very costly. But ours is the world’s first such device at a competitive price. Where Z300 costs over USD1100, our device will be available at only Tk1000.”
It should be noted that the Formaldehyde Metre Z-300, which is a kit used in the country for detecting formalin in food,has been found inappropriate for the detection test as per the aforementioned report.
The duo got their motivation from observing the rampant use of dangerous levels of formalin in food items which incited anxiety and concern amongst Bangladeshi citizens.
“Sporadic monitoring, amalgamated with the paucity of well-grounded and inexpensive testing devices, has created a need for citizens to address the issue themselves. We conducted a survey and decided to make a device for the market so that citizens themselves can use it to check for adulterated foods,” said Sadman.
The project has funded by the Institute of Electrical and Electronic Engineers (IEEE) and supervised by the authority of FAB Lab DU, a modern laboratory.
Contents of the device: The device measures 10 X 10 X 3.5 cm. The device contains a formaldehyde sensor, micro controller, Bluetooth module, rechargeable battery and charging circuit. The Android app associated with the device can be downloaded for free from the Google Play store.
The voltage output of the Grove Formaldehyde sensor changes exponentially with formalin concentration. This voltage is sent to the Android app via the Bluetooth module by the At Tiny-85 micro controller. The app applies machine learning algorithms on the data to determine the correct concentration and safety rating. Furthermore, the app is able to report to appropriate authorities as well. The device can provide accurate artificial formalin concentration levels within food items from a distance of 2-3 cm.
Recently, the duo showcased their project in the “Science for Mankind -Research Award 2018(Undergraduate)” in September and earned the champion’s prize.
Dr Khondkar Siddique-e-Rabbani, Honorary Professor at the Department of Biomedical Physics and Technology, as well as the chief coordinator of the event and one of the judges of the competition, remarked: “The innovation has great potential. We evaluated the two students’ application of the scientific method and data analysis, and selected their project for first prize jointly with another one. It may be used for the betterment of mankind.”
Swapnil and Siraj are now working on shaping the device, fixing its size and preparing covers to make it market-ready.
Commenting on the new device,Swapnil said: “Earlier, our system had been awarded by the IEEE Bangladesh Section Humanitarian Activities Committee, DUET and AUST. Furthermore, our project was selected as one of the top 10 projects in the world out of 419 projects in IEEE AIYEHUM 2017. The system is an example of how machine learning can be used to provide low-cost humanitarian solutions to common issues. We hope to market this product soon.”