The conventional apple farming process requires bringing apples into a facility after harvesting for grading and sorting, increasing time and decreasing freshness. The Eve MQP aims to make automation more accessible and efficient by bringing the apple grading and sorting process onto the orchard site. By leveraging machine learning, cameras, and sensors, Eve optimizes apple production by decreasing the time and cost while improving inspection accuracy. The system efficiently classifies apples based on color and surface defects, and sorts them accordingly. Through collaborative efforts, the team designed, prototyped, and refined the Eve Inspection and Sorting System within an academic year. By automating inspection/sorting and bringing them further up the process, Eve promises heightened productivity and waste reduction, thereby setting new standards for agricultural automation.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Rinaldi, Timothy
• Krzywicki, Lexi
• El Mansouri, Soumaya

Subject

• Innovation
• Industry
• Sustainability
• Food
• Environment

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042524-150853
• 121783

Parola chiave

• Inspection
• Harvesting
• Agriculture
• Robotics
• Fruit
• Automation

Advisor

• Wodin-Schwartz, Sarah Jane
• Calli, Berk
• Doroz, Yarkin

Year

• 2024

UN Sustainable Development Goals

• 2 - Zero Hunger
• 9 - Industry, Innovation and Infrastructure
• 11 - Sustainable Cities and Communities
• 12 - Responsible Consumption and Production
• 15 - Life On Land

Date created

• 2024-04-25

Resource type

• Major Qualifying Project

Major

• Robotics Engineering

Source

• E-project-042524-150853

Rights statement

• In Copyright