Abstract
Detecting formalin can be difficult and time- consuming without exact chemical knowledge. The presence of naturally occurring formalin in food products can additionally make it more difficult to distinguish between formalin that has been purposefully added. The method for dynamic and precise food and formalin identification described in this work is machine learning-based. Preserving food practises that put public nutrition in jeopardy include the unethical use of formalin. It was decided what kind of food to provide based on conductive characteristics. With the use of a VOC HCHO gas sensor and a Renesas, the gadget has the ability of detecting formalin concentrations of 1 to 50 ppm. Polynomial regression has been used in a number of investigations to simulate the application of formalin.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Innovative Research in Information Security
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
