Our team is joined together from across the United States (Florida to California). In the spirits of the Beach Hacks we wanted to come up with a unique idea that would hack the beach and tackle multiple challenges.

What it does

LifeGuard will enable lifeguards to do their jobs smarter and faster.

LifeGuard uses the stream deck to provide lifeguards with an efficient and easy way to understand what's currently going on and what will be coming to the beach.

The steam deck provides the following features with the ease of a click:

  • Instant 911 and help distress texts
  • Provides current wave status
  • Current weather conditions
  • Forecast weather conditions
  • Rip Tide Warning Detection

How we built it

Steam deck details (A node.js app running on windows):

  • Instant 911 and help distress calls: Used twilio to automate text message when an emergency is detected. Also integrated snapchat bitmoji kit to identify and send message other life guards.
  • Provides current wave status: Used machine learning (openCV) to teach our program what calm waves looked like. The analysis done is stored in the google cloud
  • Current weather conditions: Set-up a Arduino Mega with four sensors (UV, gas, dust, and humidity) to simulate data of current conditions to help determine the current weather conditions.
  • Forecast weather conditions: Interface with weather forecasting API( to determine what the weather conditions will be an hour from when the quarry was made.
  • Rip Tide Warning Detection: Used machine learning(autoML and openCV) to teach our program what rip tides looked like.

Challenges we ran into

  • Finding data to for the machine learning took more time than we anticipated.
  • Getting familiar with the hacking process.

Accomplishments that we're proud of

  • Coming up with a project that we created together and were able to integrate multiple goals together.
  • Producing a concept demo that simulates how the tool can enhance a life guards work process.
  • Come to a hack-a-thon together as a team.

What we learned

  • Google autoML needs to improve how they interact with users that already have pre-filtered data.
  • Stream deck was challenging to program natively, but it was a fun challenge.
  • Since this was my first hack-a-thon I learned that these events are about learning and pushing yourself out of your comfort zone.

What's next for LiveGuard

  • Incorporate real video feeds into the design.
  • Implement Linux and Raspberri Pi interface for stream deck.
  • Add more usability features that will improve the consistency and performance of life guards. Ultimately help them keep our beaches safe and the millions of visitors coming to beach world wide.

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