Daniel Sims is taking a data-driven approach to parenting. With a daughter on the way, he’s building a device that will measure a slew of environmental factors to determine how they affect an infant’s sleep patterns.
“I purchased a FitBit that I’ll be clipping to her pajamas to measure basic sleep patterns, but I wanted a higher level of detail as to outside factors. We’re planning to add sensors that measure motion, temperature, barometric pressure, humidity, light, time of day, movement in the room, etc.,” Daniel says. “We are looking to gather as much data as possible, connect it to a neural network, and predict a baby’s nighttime cry before the baby cries.”
Daniel is storing the data he collects in a database, and using Temboo’s database Choreos to communicate between the database and his Arduino-controlled sensors. Then, he’s using Tableau Desktop to visualize the data and reveal trends. Once he has a large dataset, he’ll use a neural network to predict wake-up times and identify possible causes. He’s also setting up an emergency SMS alert system that will text him if there’s a problem, like a high temperature level in the baby’s room or an extended period of crying. He may even leverage other Temboo Choreo bundles, such as NOAA for weather or Fitbit for sleep patterns, to integrate extra data sources among the various factors he is already collecting.
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