Planttagg, Inc.

Shawn Gentry

Andrew E Levi

George R Schultz

Bradley W Bauer

A system and method is disclosed for plant maintenance, identification and viability scoring. An application is located on consumer devices connected to the server. Images may be submitted to the server to identify a plant type through convolutional neural network image recognition. The invention uses another artificial neural network to predict a plant's viability score or optionally, arrives at a correlation value based on a fast abbreviation set of the plant profile and third party data. The server compares plant related input and local climactic data to determine the plant's viability score. Another aspect of the invention generates and displays an augmented reality display of a plant in the user's yard.

System and method for horticulture viability prediction and display

A system and method is disclosed for plant maintenance, identification and viability scoring. An application is located on consumer devices connected to the server. The application, operating on a smart phone, utilizes onboard GPS, user input, and camera subsystems to customize plant care tips specific to a yard location and plant type. Images may be submitted to the server to identify a plant type through convolutional neural network image recognition. The invention uses another artificial neural network to predict a plant's viability score. The server receives input, such as plant type, soil type, yard location, and amount of sunlight, and the server retrieves local climactic data and plant type optimal values to return the plant's viability score for the selected location. Another aspect of the invention generates and displays an augmented reality display of a plant in the user's yard.

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Dallas, TX, United States of America

Shawn Gentry