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Collecting and Visualizing Real Time Environment Data in the City of Charlottetown

Collecting and Visualizing Real Time Environment Data in the City of Charlottetown

A presentation to the Atlantic Association of Planning Technicians Annual Meeting on June 12, 2019 in Sackville, NB.

Peter Rukavina

June 12, 2019
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  1. Collecting and Visualizing
    Real Time Environment Data
    in the City of Charlottetown
    Atlantic Association of Planning Technicians

    June 12, 2019

    Peter Rukavina

    Reinvented Inc., Charlottetown

    https://ruk.ca/

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  2. The Story Begins
    I became interested in
    where we get our electricity
    on Prince Edward Island.

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  3. Electricity Flow

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  4. https://tso.nbpower.com/Public/en/SystemInformation_realtime.asp

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  5. Golf at 50BPM by user707748013
    50 MW
    50 BPM

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  6. W&W - Bigfoot (Uriel M Deephouse Remix) by urielm
    122 MW
    122 BPM

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  7. 155% of our electricity
    load from the wind
    10:30 p.m. 7:30 a.m.
    8 Hours

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  8. Home Electricity 

    and Water

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  9. Taking Stock

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  10. • Sensors are cheap, and there are a lot of things
    we can measure.

    • Being peripherally aware of things we can
    measure can positively alter our behaviour.

    • Data communication via wifi is a technical and
    support challenge, and doesn’t scale.

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  11. Measure Your City

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  12. LoRaWAN
    • LoRa = Long Range (and low power)

    • LoRaWAN is a networking protocol for connecting
    gateways and devices.

    • Excellent for transmitting small amounts of data over
    long distances with little power.

    • Helps solve the “data communication over wifi is a
    customer support nightmare” issue.

    • Helps solve the “wifi devices use a lot of power” issue.

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  13. SNACKS
    Sensor Network Around Charlottetown’s Key Surroundings

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  14. SNACKS Stack
    • Sensor nodes (low-powered Arduino boards) broadcast
    readings, which are picked up by strategically-placed The
    Things Network gateways.

    • Gateways send readings to The Things Network.

    • Application on The Things Network sends readings to
    Amazon IoT service where they are archived in a
    database.

    • A web application visualizes the archived readings.

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  15. SNACKS Challenges
    • Battery management in off-the-shelf LoRaWAN-equipped
    Arduino devices isn’t great (~2 weeks battery life or less).

    • “Onboarding” a new sensor node is more complicated
    than it needs to be.

    • Visualization technique hasn’t been real-world-tested yet,
    so we don’t know if it’s optimal.

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  16. SNACKS Next
    • Work on battery life issues (possibly adopting
    Amersfoort’s custom board).

    • Look at a broader range of sensors (particulate matter,
    solar radiation, radon, sound, etc.)

    • Explore the possibilities of using LoRaWAN to manage
    water and electricity meters at scale.

    • Roll out devices to citizens and start to gather data.

    • Continue to be curious.

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  17. Thank you.
    Slides at https://l.ruk.ca/aapt

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