Mobile App for Herbarium Data Segmentation
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Solution Overview
Problem
Herbarium data and digital live plant images are not effectively organized or accessible, lacking a dedicated platform for professionals and enthusiasts to share and utilize these resources, and there is no streamlined process for image uploading, licensing, sharing, or purchasing.
Innovation Solution
A mobile app that stores herbarium and live plant image data in the cloud, allowing users to download region-specific data, upload images, set licenses, and monetize them, utilizing machine learning for image identification and autocompletion of taxonomic details, with features for filtering, searching, and payment processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If herbarium data is made available through online portals, then data accessibility is improved, but user convenience and ease of access on mobile devices deteriorates
Solution Approach 1:
The patent segments herbarium data by geographic regions and allows users to download only the specific regional data they need to their mobile devices. This segmentation approach makes the large herbarium dataset manageable and accessible on mobile devices with limited storage, while maintaining ease of access through the mobile application interface.
2Quantity of substance
If a comprehensive herbarium database is created, then data completeness is improved, but device storage requirements and data download time worsens
Solution Approach 1:
The patent divides the comprehensive herbarium database into region-specific segments. Users can selectively download only the data for the regions they are interested in, rather than downloading the entire global database. This significantly reduces download time and storage requirements while maintaining data completeness for the user's specific needs.
3Quantity of substance
If digital live plant images are collected from various sources, then image diversity is improved, but organization and classification quality deteriorates
Solution Approach 1:
The patent incorporates machine learning algorithms that automatically analyze uploaded plant images and provide feedback for classification and organization. The system learns from user corrections and refinements, continuously improving its classification accuracy while handling diverse images from multiple sources. This feedback mechanism maintains high classification quality despite the diversity of input images.
4Productivity
If a platform for sharing and monetizing plant images is created, then user engagement and contribution increases, but system complexity and licensing management worsens
Solution Approach 1:
The patent implements a self-service licensing system where users can automatically set licensing terms for their uploaded images and selectively choose which images are available for download. The system automatically manages licensing agreements and payment processing between users, eliminating the need for complex manual licensing management while enabling monetization of plant images.
Data Source
AI summary
The invention uses mobile app technology to make herbarium information available on devices with easy-to-use interfaces. With the mobile app, the herbarium information is more easily accessible. This portion of the invention was disclosed in Provisional Application No. 63/404,960, filed on Sep. 9, 2022. This invention further supports the functionality to add new herbarium and/or live plant images. A user can use machine learning technology to identify the plant in the image or add taxonomic information with the aid of autocompletion feature. The invention allows a user to specify licenses for images. The images can be displayed to other users for information sharing, purchase and download. There is also a functionality to show only herbarium or live plant images in the app. This portion of the invention was not disclosed in Provisional Application No. 63/404,960 and built upon the foundation established by Provisional Application No. 63/404,960.