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Submission

introduction
title
PVDoctor
short description
Improve the performance of solar modules there be leaving bigger profits to PV module owners using IOT , Web application, Neural Networks
Eligibility
Full Description
One of the major factors people consider before installing solar modules is the money they will save after they install.
So, we wanted to make sure PV module runs with maximum performance which eventually will encourage more people in US to install solar modules
Each PV module gives lot of metrics that when properly analyzed can give us the action plan to make sure it is running at its full potential. There is no current hardware module for small scale users like single family homes to collect this data and get meaningful insights.
We believe that with our idea it will be very easy to keep track of the PV module performance which eventually will encourage more people in US to install solar modules
There are Three parts for our project:

1) HardWare Part: We tap into the potential of low cost IoT devices which contains modules to track various parameters

2) Front End Part: User will have Web/Mobile App which will provide various insights using the data that is being pulled from sensors and also existing NREL and other 3rd party APIs. One example is to show how efficient the current PV module is compared to neighbor PV modules.

3) Back End Software Part: Insights to take action on are powered by neural network model using the data from our IoT sensor and other third party APIs.

Please refer to Additional Material for more details on each of these three parts.
Additional Materials
PVDoc_revised_new.docx
Ideation Video
References
Submissions may include up to 5 links to research literature that provides background and relevant patents. Such links can be to a website article, a Wikipedia page or for National Lab IP, https://www.labpartnering.org/lab-technologies. It is the Prize Administrator’s hope that the quality of literature referenced in the submissions will factor into voting results.

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