Features
1. Recommendations on what to plant based on a user's environment
2. Reminders when a user needs to water their plant
3. A social platform where users can see what others are growing and message them to trade produce
Hardware
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Micro controller
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Soil moisture sensor
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Soil temperature sensor
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Air temperature and humidity sensor
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Photo resistor to track sunlight strength
Our hardware consists of 2 boards: the Arduino MKR 1000 and the ELEGOO Uno. We decided to use two boards because we could run all of our sensors off of the Uno and connect to the IoT with the MKR 1000. The WeGarden has 4 sensors that collect 5 different values: air temperature, soil temperature, humidity, soil moisture, and sunlight. These 5 values will be collected in the cloud and utilized in the software to create our app. Currently, these sensors are powered by a USB cable connected to a computer but we plan to power it with a solar cell and battery in the future.
Software
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Arduino IDE
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AWS
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Adafruit.io
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HTML, CSS, JavaScript, and Python
All of our data is stored in Adafruit.io which we were able to access with APIs from both our Arduinos and our web app. In order to make the data useful to our users we send it to an AWS Lambda function through a custom API to receive recommendation information. Furthermore, on the frontend of our web app we utilized JavaScript to give users their own individual dashboard and a social page where they can see what others are growing.
System Flow Chart
Specifications
In order to keep users’ plants healthy, our device uses four sensors to collect five points of data. The soil moisture sensor allows the WeGarden app to notify users when their plants need to be watered. The temperature and humidity sensors provide environmental data and are housed within a DHT sensor. Our environmental data is retrieved using Adafruit’s API. We display this data on an individual dashboard on our web app for each user. We use Adafruit’s feed to track individual user’s plants, so the user can track the plants that they are growing. Another important feature of our web app is our proprietary recommendation algorithm. This takes sunlight strength, soil temperature, and germination period into account to generate the perfect plant for you. ​
Costs
Prototype Costs
Manufacturing Costs
