Voice Picking App for French Warehouse Management Systems
Voice Picking App for French Warehouse Management Systems
Information
Region:
France
Industry:
Logistics and Transportation
Type:
Mobile
Engagement model:
Time and Materials
Duration:
3 months
Staff:
Android Senior / Team Lead Developer, Business Analyst, Senior Project Manager, Senior Quality Assurance Engineer, Middle Designer
Technologies used
C++
Kotlin
Jeypack
Vosk
Async
Hilt
GitLab
Confluence
Figma
Android Framework 2.1

Сlient

The client is the leading provider of cold warehouse logistics systems in France. The company reached out to Elinext to build an Android-based mobile app compatible with a device used for scanning parcels. The primary purpose of an app is to provide information about the location of parcels. The app receives data from the client’s warehouse management system and communicates it using speech recognition technology.

Challenge

Before reaching out to Elinext, the client had been using a third-party voice recognition solution integrated with their warehouse management system. Due to the high cost of a solution and poor performance, it became risky to continue using this solution in daily processes. The client came up with the idea to build its own Android-based application that would replace a third-party tool and be scalable enough to integrate with their WMS system.

From a technical standpoint, the client expected an app to have features that would:

  • Recognize voice messages of warehouse workers
  • Transform WMS’ text messages into speech
  • Train the app with language adjustments, such as dialects and pronunciation
  • Change the speed of an app speech
  • Change the port number of a WMS

Solution

The solution is a chat-based application used by warehouse workers to communicate with a warehouse system and pick up parcels.

The application enables warehouse workers to communicate with the WMS using voice commands. This feature enables warehouse operators to use both hands while collecting parcels, leading to a faster and more efficient gathering process.

The voice-picking app incorporates speech recognition and is trained in more than 20 languages, with a focus on French.

Each worker can contribute to the language library and train a model for speech recognition. This feature is for workers with different dialects who want to improve the way an app understands their voice commands.

Additionally, we developed a feature that speeds up speech messages of WMS from 1x to 2x, ensuring that every worker benefits from this app, regardless of their preferred working speed.

The application allows a worker to change the port of a WMS. Since warehouses have closed Wi-Fi network areas, workers need to change the port number in order to access the warehouse logistics system, which is now available using a mobile app.

Results

The client has already started using the app in their warehouses. The stable performance of the app and its chat-based structure have significantly expedited the process of parcel gathering.

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