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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.

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Peter Rukavina

June 12, 2019
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Transcript

  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/
  2. The Story Begins I became interested in where we get

    our electricity on Prince Edward Island.
  3. Electricity Flow

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

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

  10. W&W - Bigfoot (Uriel M Deephouse Remix) by urielm 122

    MW 122 BPM
  11. Wind Energy

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  16. 155% of our electricity load from the wind 10:30 p.m.

    7:30 a.m. 8 Hours
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  19. Home Electricity 
 and Water

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  31. Taking Stock

  32. • 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.
  33. Measure Your City

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  40. 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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  44. SNACKS Sensor Network Around Charlottetown’s Key Surroundings

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  53. 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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  55. 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.
  56. 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.
  57. Thank you. Slides at https://l.ruk.ca/aapt