Research

Agricultural Sciences

Title :

An IoT-based pesticide detection in leafy vegetables using deep learning

Area of research :

Agricultural Sciences

Focus area :

Internet of Things (IoT)

Principal Investigator :

Ms. Anju Augustin, Indian Institute of Information Technology, Kottayam, Kerala (686635)

Timeline Start Year :

2024

Timeline End Year :

2028

Contact info :

Details

Executive Summary :

A balanced diet is crucial for human health, but many fruits and vegetables contain harmful pesticides and insecticides, leading to serious illnesses. A recent report from the University of Agriculture found that 48.48 of fruits, 48.80 of vegetables, and 85.71 of spices contain pesticides, with leafy vegetables like coriander leaves, mint leaves, and curry leaves containing extreme poison. Existing methods rely on expensive laboratory tests, but a system using IoT and deep learning is proposed to detect pesticides in leafy vegetables in real-time and efficiently. The system uses a nanoLambda sensor to generate spectral output, which is then analyzed using a deep learning model. The system uses a transfer learning model to avoid overfitting issues. This IoT-based approach offers better efficiency without large spectrometry laboratory machines, making it suitable for government authorities, consumers, and the general public.

Total Budget (INR):

25,35,840

Organizations involved