Winners Of Hackaday’s Data Loggin’ Contest: Bluetooth Gardening, Counting Cups, And Predicting Rainfall

The votes for Hackaday’s Data Loggin’ Contest have been received, saved to SD, pushed out to MQTT, and graphed. Now it’s time to announce the three projects that made the most sense out of life’s random data and earned themselves a $100 gift certificate for Tindie, the Internet’s foremost purveyor of fine hand-crafted artisanal electronics.

First up, and winner of the Data Wizard category, is this whole-garden soil moisture monitor by [Joseph Eoff]. You might not realize it from the picture at the top of the page, but lurking underneath the mulch of that lovely garden is more than 20 Bluetooth soil sensors arranged in a grid pattern. All of the data is sucked up by a series of solar powered ESP32 access points, and ultimately ends up on a Raspberry Pi by way of MQTT. Here, custom Python software generates a heatmap that indicates possible trouble spots in the garden. With its easy to understand visualization of what’s happening under the surface, this project perfectly captured the spirit of the category.

Next up is the Nespresso Shield from [Steadman]. This clever gadget literally listens for the telltale sounds of the eponymous coffee maker doing its business to not only estimate your daily consumption, but warn you when the machine is running low on water. The clever non-invasive method of pulling data from a household appliance made this a strong entry for the Creative Genius category.

Last but certainly not least is this comprehensive IoT weather station that uses machine learning to predict rainfall. With crops and livestock at risk from sudden intense storms, [kutluhan_aktar] envisions this device as an early warning for farmers. The documentation on this project, from setting up the GPRS-enabled ESP8266 weather station to creating the web interface and importing all the data into TensorFlow, is absolutely phenomenal. This project serves as a invaluable framework for similar DIY weather detection and prediction systems, which made it the perfect choice for our World Changer category.

There may have only been three winners this time around, but the legendary skill and creativity of the Hackaday community was on full display for this contest. A browse through the rest of the submissions is highly recommended, and we’re sure the creators would love to hear your feedback and suggestions in the comments.

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