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
| Registration# | Name |
|---|---|
| CU-1782-2020 | Anna Amjad |
| CU-1176-2020 | Hazrat Usman |
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
