Smart Garden ML Usecase - UMKCNSF/UMKC--HACKATHON GitHub Wiki
Smart Garden Using Machine Learning Algorithms
The aim of the development is to develop a mobile application for Smart Garden. The application has to be intelligent enough for taking the decision on their own according to the type of plant, the direction of the sun, current weather conditions and location of the plantation.
The scenario:
We have a small garden in Kansas City but we don’t know the best time to give water so by using android application we take a small video of the garden from such a location that it traces the rays of the sun and detects the current weather using any weather API, and location using Google maps. The application will be able to detect the type of plant let’s say tomato, you can use any image recognition or video annotation API available. According to the type of plant and direction of the sun, the application should raise a notification of watering the plant and it should also suggest how much water is required (Gallons or any familiar unit) and the application should have the on-screen stopwatch for start and stop water according to the size of the garden. The application should also be able to inform the Gardener using web admin panel about 10 days weather forecast and tell what he should do regarding watering the plants in such conditions breaking down in daily reports.
Dataset:
For considering data the developer has the flexibility to choose the public data sets available for training purpose.
Features & Technology:
Android / IOS ApplicationWeb Admin Panel (Language of Personal Choice) FCM (For Notifications) Email & SMS Alerts Weather API, Google Maps Machine Learning Algorithms
References
https://github.com/UMKCNSF/UMKC--HACKATHON/blob/master/Images/Smart%20Garden%20Use%20Cases.pptx