Honey Adulteration Detection through Hyperspectral Imaging and Machine Learning

Objectives

Main objective of the project are: (1) To automate the process of honey identification. (2) To automate the process of detecting adulteration in honey. (3) Integration of multiple ML models onto one front-end web interface.

Socio-Economic Benefit

The purity and authenticity of honey are paramount for ensuring consumer trust and maintaining the integrity of the honey industry. SDG3: GoodHealth and WellBeing

Methodologies

Through the use of python libraries such as sklearn for machine learning model, and a Flask API, we were able to form a fully automated and integrated system that is both a honey type and quality detector.

Outcome

A fully automated and integrated honey identification and adulteration system that can predict quality of honey and its associated honey type in real-time through the use of hyperspectral features.

Project Team Members

PROJECT GALLERY

Honey Adulteration Detection through Hyperspectral Imaging and Machine Learning

28 May, 2024 03:00 am

Honey Adulteration Detection through Hyperspectral Imaging and Machine Learning

28 May, 2024 03:00 am

Honey Adulteration Detection through Hyperspectral Imaging and Machine Learning

28 May, 2024 03:00 am

Honey Adulteration Detection through Hyperspectral Imaging and Machine Learning

28 May, 2024 03:00 am

Honey Adulteration Detection through Hyperspectral Imaging and Machine Learning

28 May, 2024 03:00 am