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

About project

Fresh Scanner - a platform for automating of quality control and categorization of fruits and vegetables with reports.

Facts

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

Customer

-

Our customer is a top manager of one of the largest Russian retailers. He wanted us to create a solution with the following characteristics:

darts image

Goal

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

Challenge

  • Laboratory for digitizing the results of the product examination.
  • Databases with the results of examinations conducted in accordance with the standards of the United Nations Economic Commission for Europe (UNECE) and the Organization for Economic Cooperation and Development (OECD).
  • Artificial intelligence based on trained neural network algorithms for assessing the quality of fresh fruits and vegetables.
  • Software for managing the implementation of the full cycle business process including analysis of products, shipment, and statistics.

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

Artifical intelligence
1
Convolutional neural networks, ResNET
RetinaNET

Platforms

Web applications
Desktop applications
Mobile applications
Server applications

Team