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Machine learning




Web, QA, Embedded




JavaScript, HTML5, CSS

Project type

Machine Learning


Hummingbird is a drone-enabled data and imagery analytics information system for precision agriculture. This technology uses the most advanced machine learning and computer vision techniques, delivering actionable insights on crop health directly to the field. The system collects images and uploads to the Hummingbird cloud, before being processed with proprietary computer vision algorithms and machine learning techniques.

Business needs:

Extend the functionality of the UI for better user interactions.

Implement new functionality displaying additional records for maps.

Add new functionality for area selection and marks on maps.

Develop and test new functionality for layers on maps.

Finalize the admin part of the information system for recording flights and administering information, adding users, farms, fields etc.

Suggested solutions from Svitla:

Use the existing set of libraries to effectively solve front-end tasks.

Cover all functionality on the front-end with unit tests.

Intensively use continuous integration and unit tests on the front-end.

Use advanced functions of the leaflet library to display additional information on maps.


Programming languages: JavaScript, HTML, CSS

Unit tests: mocha, chai

Libraries: React.JS, Redux, leaflet

Tools: git, continuous integration, Scrutinizer, Trello


Value delivered

Improved user interface due to using modern technologies.
Better data analysis with extended functionality of information system with maps data.
Better user control and improved functionality of admin panel.
Fast front-end development based on closed cycle of continuous integration unit tests.

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