RestSeeker

A means to search for relevant sport activities and healthy ways to spend free time in the vicinity of a User. Applies to sports choices and tourist activities in the area as well.

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  • Finland

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  • Challenge #2: Space-Powered Performance – Transforming Sports

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Description

Through real-time satellite and biometric data, we aim to recommend our users the type of activities that they can engage in based on their health and the environment. Users can engage in our recommended activities, collect points, and then get access to various provided by our local partners. Our service can be accessed in the form of a mobile app, which supports various os systems, including Android and Apple. We provide 2 tier subscription - the free tier which provides only recommendations based on weather and the subscription tier which provides you an AR software which allows you to see how you would engage in the activity as well as data about pollution and health. 

For this project, we are using satellite data to track location, humidity, temperature, and sound (noise) from user's location along with user's health data from ECG sensor. We will integrate these datas to get personalized exercise or hang out location based on their health condition, classifying whether the user has normal or crticical heart condition. We use Grove Beginner Kit, Kineis receiver, and Movesense ECG sensor for the hardware. The user does not always need to use Movesense ECG sensor, they can use whatever wearable things or just their mobile phone health application (Apple Health, Samsung Health, Xiaomi Health, etc.) to get the personalized recommendations. Here are several important things about the github file.

  1. basiccode is containing main code you could use for retrieve satellite info
  2. Lead I is an ECG data from Movesense Sensor. There is also a ready-to-use CSV data for Lead I
  3. Apple-data is exported heat beat (BPM) data from apple watch. it's not ECG graph, just a value of BPM per day
  4. Satellite data is retrieved in satellite.csv
  5. You can check the flowchart in the hackathon.jpg


Our team consists of 5 members:

  • Yunseon Lee - Health Technology Engineering, Aalto University
  • Fathia Maheswari Nugraha - Health Technology Engineering, Aalto University
  • Ngan Le - Business Analytics, Aalto University
  • Aidar Oshakbayev - Business Analytics, Aalto University

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