Australian Tree ID

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Industry
Education
Platforms
Android, iOS
What we did?
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    Development
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    Deployment
What is Australian Tree ID about?
Australian Tree ID is a comprehensive, helpful app to identify species of trees, conifers & palms using images & detailed descriptions. The Australian Tree ID allows you to identify more than 235 species using a simple identification key using traits such as leaf shape and colour, flower shape and fruit type. It is difficult to identify a tree easily just by taking a glance at it. The app allows you to identify species using a simple identification key features such as the leaf shape, flower shape, fruit form and bark texture. Each tree has a full description covering its origin, specification and landscape notes for preferred growing preference. It describes in detail native and exotic trees of NSW, ACT, VIC, TAS and SA, found growing commonly within our urban streets, parks and gardens. It is the perfect app for all Arborists, Gardeners, Landscape Architects, Biologists and nature lovers.
Challenges
The tree identification engine should be fast and smart.
The client wanted an app which can be used by kids for learning purposes. App was likely to work both offline and online. The app was subject to be very easy to use considering kids.
The functionality of the app revolves primarily around pictures of the trees.Also, the images needed to be high-quality and free from any type of pixelation. Even the slightest variation can lead to the tree not being clearly identified.
Besides that, it was important for the images to load on all Android and iOS devices, including those running on older versions.
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Solutions
Our development team losslessly compressed the images using Python programming that was uploaded to Amazon S3 (Amazon Simple Storage Service) and then synchronized to Cloudfront CDN, which intensified image delivery and other bulky content used in the application.
It was important for the client to run some features of the app with limited orno internet connection.
The team worked on a cohesive architecture based on feasibility analysis and priority, allowing users to access data and images that they browse or loaded earlier & cache, even without an internet connection.
This feature allows users to study their history of app usage and to continue their cycle of recognition without interruption.
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