Coming from South-East Asia, we have seen the devastation that natural disasters can wreck havoc on urban populations

We wanted to create a probe that can assist on-site Search and Rescue team members to detect and respond to nearby survivors

What it does

Each Dandelyon probe detects changes in its surroundings and pushes data regularly to the backend server. Additionally, each probe has a buzzer that produces a noise if it detects changes in the environment to attract survivors. Using various services, visualise data from all probes at the same time to investigate and determine areas of interest to rescue survivors.

What it consists of

  • Deployable IoT Probe
  • Live data streams
  • Data Visualisation on Microsoft Power BI
  • Data Visualisation on WebApp with Pitney Bowes API(

How we built it


  • Identified the sensors that we would be using
  • Comprises of:
    1. Cell battery
    2. Breadboard
    3. Jumper Wires
    4. Particle Electron 2G (swapped over to our own Particle 3G as it has better connectivity) + Cellular antenna
    5. GPS + external antenna
    6. Sound detector sensor
    7. Buzzer
    8. Accelerometer
  • Soldered pin headers onto sensors
  • Tested the functionality of each sensor
    1. Wired each sensor alone to the Electron
    2. Downloaded the open source libraries for each sensor from GitHub
    3. Wrote a code for main function for the sensor to communicate with the Electron
    4. Read the output from each sensor and check if it's working
  • Integrated every sensor with the Electron
  • Tested the final functionality of the Electron


  • Infrastructure used

    1. Azure IoT Hub
    2. Azure Stream Analytics
    3. Azure NoSQL
      1. Microsoft Power BI
    4. Google Cloud Compute
      1. Particle Cloud with Microsoft Azure IoT Hub integration
  • Backend Development 1. Flow of live data stream from Particle devices 2. Supplement live data with simulated data 3. Data is piped from Azure IoT Hub to PowerBI and Webapp Backend 4. PowerBI used to display live dashboards with live charts 5. WebApp displays map with live data

  • WebApp Development Deployed NodeJS server on Google Cloud Compute connected to Azure NoSQL database. Fetches live data for display on map.

Challenges we ran into

Hardware Integration Azure IoT Stream connecting to PowerBI as well as our custom back-end Working with live data streams

Accomplishments that we're proud of

Integrating the Full Hardware suite Integrating Probe -> Particle Cloud -> Azure IoT -> Azure Stream Analytics -> PowerBI and Azure Stream Analytics -> Azure NoSQL -> Node.Js -> PitneyBowes/Leaflet

What we learned

What's next for Dandelyon

Prototyping the delivery shell used to deploy Dandelyon probes from a high altitude Developing on the backend interface used to manage and assign probe response

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