Fresh Scanner

Timeframe:
6-12 m
Complexity:
Price:
80k

About project

An artificial intelligence platform provides surveyors with automatic quality control and categorization for fruits and vegetables.

Facts

6 team members including 3 software developers
80k USD Budget
Revolutionary technology applied

Customer

-

Our customer is a former top manager of one of the largest Russian retailers, leads a world-class surveyor and logistics professionals. Spellsystems delivered a solution with the following specification:

Goal

darts image
  • Accuracy of 99%
  • Defects Detection
  • Product Quality Detection
  • Quality Category Detection
  • Databases conducted with the accordance with the UNECE and OECD standards

Challenge

  • The software automates the entire process of dataset and feature management, ANN training pipeline, and deployment.
  • Neural network algorithms assess the quality of fresh fruits and vegetables.
  • The software covers all the essential surveyors' business processes. including analysis of products, shipment, and statistics.
  • Databases of examination results are saturated. All the examinations meet the United Nations Economic Commission for Europe (UNECE) and the Organization for Economic Cooperation and Development (OECD) standards.

Results

1

A scanner for obtaining high-quality photographs has been developed

2

A unit of trade professionals has been formed to assess the quality of fruits and vegetables

3

Data collection for machine learning is ongoing

4

Developed software to assess the quality of fruits and vegetables

5

The automated process of forming reports has been developed

6

The virtual personal Cabinet of the expert-receiver has been developed

Technologies

Basic technologies
1
C#, Microsoft.NET
Python
Artifical intelligence
2
Convolutional neural networks, ResNET
RetinaNET

Platforms

Web applications
Desktop applications
Mobile applications
Embeded
Server applications

Screenshots