Ricerca CERCA

Real-Time Detection of Plant Parasites and Diseases in Smart Agriculture

azienda Thesis in external company    


Reference persons LUCIANO LAVAGNO

External reference persons Marcello babbi, Reply Torino

Research Groups Microelectronics


Description In smart agriculture, early detection and control of plant parasites and diseases are crucial for maintaining
high crop yields and minimizing economic losses. This thesis proposes the development of a cutting-edge AIbased
system for the real-time detection of plant parasites and diseases in smart agriculture. The system will
use computer vision and machine learning techniques to analyze images of plants captured by sensors and
identify patterns. The system will be designed to run on edge devices, allowing for real-time processing of
images and immediate feedback to farmers. The use of state-of-the-art AI technologies, such as deep
learning and transfer learning, will enable the system to learn and adapt to new patterns of parasites and
diseases over time, leading to more accurate and reliable detections.

Required skills Python programming, some knowledge of Machine Learning, image processing

Notes The student will be involved in:
❑ State-of-the-art literature review
❑ SW requirements definition for edge deployment
❑ Data pre-processing and feature engineering
❑ Developing and implementing a deep learning-based model for image analysis
❑ HW computational requirements trade-off

Deadline 11/10/2024      PROPONI LA TUA CANDIDATURA