Authors :
Shrikant S. Gurav; Snehal A. Patil; Shubhangi L. Patil; Priti P. Desai; Prajakta B. Badkar
Volume/Issue :
Volume 7 - 2022, Issue 6 - June
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3yw3OQ2
DOI :
https://doi.org/10.5281/zenodo.6808989
Abstract :
In this Digitized world farmers can do day-today operations using online means such as buy and sell of
saplings. The Modern world can connect back to the
motherland using PlantIP app which helps farmers to
digitize themself and form a community. To identify and
detect plant diseases, which are a major factor in the loss
of crop yield in agriculture and crop production, we
employ a powerful ML library provided by Google. The
project uses live weather forecast for a week with updated
GPS tracks using satellite data from Openweathermap.
Parts of the distributed run-time system for the plant
disease detector are arranged to execute on user-side
mobile devices and cloud-side centralized servers. The
CNN deep learning model and the Intermediate
Representation (IR) model that operate on mobile devices
are both described in Layer 1 of the system. The user
interface is depicted in Layer 2 and created as an
Android app to make it easy for system users (shown in
Layer 3) to engage with the system.
Keywords :
Image processing, image acquisition, classification, segmentation.
In this Digitized world farmers can do day-today operations using online means such as buy and sell of
saplings. The Modern world can connect back to the
motherland using PlantIP app which helps farmers to
digitize themself and form a community. To identify and
detect plant diseases, which are a major factor in the loss
of crop yield in agriculture and crop production, we
employ a powerful ML library provided by Google. The
project uses live weather forecast for a week with updated
GPS tracks using satellite data from Openweathermap.
Parts of the distributed run-time system for the plant
disease detector are arranged to execute on user-side
mobile devices and cloud-side centralized servers. The
CNN deep learning model and the Intermediate
Representation (IR) model that operate on mobile devices
are both described in Layer 1 of the system. The user
interface is depicted in Layer 2 and created as an
Android app to make it easy for system users (shown in
Layer 3) to engage with the system.
Keywords :
Image processing, image acquisition, classification, segmentation.
