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The proposal is for creating a protype of a seismometer node which can connect either to the QCN or can be monitored over a web dashboard (for realtime monitoring).

Student: Shrey Dabhi
Possible Mentors: Stephanie Lockwood-Childs, Steve Arnold
Code: NA
Wiki: NA


This project is currently just a proposal.


About you

IRC: sdabhi23
Github: sdabhi23
School: Institute of Technology, Nirma University
Country: India
Primary language (We have mentors who speak multiple languages): Hindi
Typical work hours (We have mentors in various time zones): 11 - 14, 16 - 20, 21 - 23 IST
Previous GSoC participation:

About your project

Project name: BeagleBone Remote Seismometer Node


The aim of the project is to create a prototype network of seismometer nodes. The current proposal aims to have a prototype of sensor node for QCN which can be left unattended, if a consistent internet connection is available.

Currently the Quake Catcher Network relies on internal mobile device sensors and external USB sensors. The internal mobile device sensors are not so reliable as the mobile devices are generally constantly in motion, on the hand the external USB sensors which are connected to laptops might or might not be connected to the internet 24/7.

Using remote seismometers which consists of a BeagleBoard connected to a standard QCN accelerometer, this problem can be solved easily as we can have a BeagleBoard running 24/7 with an extrenal power supply and provide internet connectivity using WiFi or cellular connections.

We will also be able to monitor these remote sensors through a web app being served by the BeagleBoard over the internet / wireless LAN.


Community bonding period

  • Finalize the technology stack for the web dashboard.
  • Finalize the third party accelerometer best suited for our purpose.

2017-06-06: Milestone #1

  • Investigate the exact capabilities of the provided model of BeagleBoard.
  • Get the BOINC software (used by QCN) up and running.

2017-06-13: Milestone #2

  • Install the standard QCN sensor.
  • Start working on the web dashboard.

2017-06-20: Milestone #3

  • Test and calibrate the QCN sensor
  • Start working on the interface for 3rd party accelerometers.

2017-06-27: Milestone #4

  • Try and make the BOINC software identify the connected 3rd party sensor (if possible)

2017-07-04: Milestone #5

  • Bug fixing and documentation

2017-07-11: Milestone #6

  • Calibrate the 3rd party accelerometer.
  • Automate the process of calibration on booting-up the device.

2017-07-18: Milestone #7

  • Test the 3rd party sensor with the custom interface library/driver.

2017-07-25: Milestone #8

  • Bug fixing and documentation.
  • Test the web dashboard with static data.

2017-08-01: Milestone #9

  • Capture data from both the type of sensors and redistribute it over the QCN software and a datastore onboard the BeagleBoard.

2017-08-08: Milestone #10

  • Visualise the data from the datastore on the web dashboard.

2017-08-15: Milestone #11

  • Testing, bug fixing and documentation.

Experience and approach

  • I have done projects with Arduino and Bluetooth technology. Also I have some experience with Raspberry PI.
  • Link to the video presentation of a college project which uses a LPG gas sensor and a Bluetooth communication module on an Arduino Nano.
  • I was easily able to deploy a similar project as described here using Arduino Nano and ADXL335 accelerometer. But the proposed project is different in the sense that a complete network of interconnected nodes will be deployed which will communicate with a single client server.


I can use the vast documentation and help available through forums, wikis, IRC and other means to find solutions for my problems. Also there is this large and awesome community of QCN for additional help. And also as a last resort I can also consult my colleagues and other faculties in my university for further support.


To make a less expensive, hackable and easy to deploy network for hobbyists and researchers alike to monitor seismic activities round the clock in their region and access and upload it on QCN.