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Create Xamarin app based on BLE to help fight coronavirus spread

amlocekamlocek Member

Hello,
I'm not sure if this is the best place but I don't know any Xamarin devs personally so I thought I might find someone able to help me here.

The idea is simple: use BLE advertisement data to record social interaction on a smartphone (without storing the data in the cloud). I think I know how to do it but it will take me too long as I am not an experienced Xamarin dev. I know C# and have experience with cloud, IoT and BLE.

This is a non commercial project.

I am based in Sydney at the moment.

Adam

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  • GtheBGtheB USMember ✭✭

    Hi, not sure if I'm the right person. I develop via Xamarin on Android, have experience using Bluetooth and beacons, and have developed location-aware android software for Real Estate agents (like open house invites). So, can you describe 'It' a little bit more? Also, the time frame?

  • amlocekamlocek Member

    Great, here are some more details:
    1. The app would scan for BLE devices every n seconds and record advertisement data which includes TxPower (transmitter power), RSSI (received signal strength) and DeviceId. If we could filter down only smartphones (look at advertised services?) then we would create a social distance measure as a proxy for exposure to Covid (e.g. total time near other people weighted by proximity). All data would be saved only locally.

    1. The app would advertise itself over BLE with a random DeviceId (could change every n minutes or hours).

    2. No personal data is collected so no user accounts, phone numbers etc. Collection of GPS data is not necessary but might be optional.

    3. No data is uploaded without explicit consent.

    4. Once BLE advertisement data is collected it becomes useful for data scientists: if a user has a Covid test they can record it in the app (neg or pos result). If they agree the result is uploaded to a cloud service (only the DeviceID and test result is needed) so that other users are notified and their app searches through local BLE records for a DeviceId match and calculates risk of exposure conditional on being close to an infected person.

    5. Data scientist could fit models for risk of infection as a function of social distance index. Models can run locally in smartphones or if user agrees in the cloud. If there is predictive power in this approach then it would help with testing strategies, social distancing policies etc.

    Adam

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