A cloud-based approach to rodent research

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MÍOS is an experimental concept for cloud-based research studies on colony-housed rodents. MÍOS leverages low costs sensors and micro-controllers and reduces the barriers to real-time, high-throughput data collection, visualization, and analysis.

MÍOS is under development and we welcome feedback on it.

Project Goals:

  • Scalable cloud-based system 
  • Monitoring and real time reporting of data from rodent home-cages
  • Compatible with existing rodent caging and facilities
  • Facilitate collaborations and increase reproducibility between research groups


  • Mobile app that can be configured to track dozens of hardware devices 
  • Real-time visualization of data from multiple cages, even across multiple locations 
  • Easy export of research data
  • Compatible with open-source cost-effective hardware to enable large-scale studies 


The MÍOS ecosystem is powered by Blynk, an IoT app platform. The MÍOS team (researchers at NIH and FDA) collaborated with engineers at Blynk to design and optimize three app widgets (Reports, DeviceTiles, and SuperChart) for tracking and exporting research data. The three widgets were developed by Blynk and have been made available to all users.  

Funding and terms:

The MÍOS project was funded by the NIH Intramural Research Program (NIDDK & CIT) and the Health and Human Services (HHS) Secretary's Venture Fund. This project is released under the terms of the Creative Commons - Attribution - ShareAlike 3.0 license:

  human readable:
  legal wording:

MÍOS was conceived by a team of researchers at the National Institutes of Health (NIH) and Food and Drug Administration (FDA), and all app development was done by Blynk. While MÍOS devices and designs are open-source and free, Blynk is a "freemium" service and some features cost money to use.  100% of this money supports the business operations of Blynk.  NIH, FDA, and members of the MÍOS team receive no royalties or payments from Blynk.

  • Benefits of IoT for rodent research

    Lex Kravitz05/24/2018 at 12:18 0 comments

    IoT data collection has found a home in many devices from our phones to our thermostats.  Somewhat surprisingly, IoT data collection is extremely rare in biological research labs.  Much data is still logged manually,  and even computer-generated data is often stored locally and transferred to other researchers by email or local data transfers.  MIOS is an experimental concept to explore using IoT to streamline the collection and visualization of research data.  Cloud-based research data collection has the inherent benefits of:

    1. Data is automatically archived and saved
    2. Data can be collected from multiple sites simultaneously, making multi-site studies as easy to run as single-site studies
    3. Problems in data collection can be visualized immediately, instead of being discovered at the conclusion of a study
    4. As data is in the cloud, data can be shared among researchers as soon as it is collected
    5. Cloud analytics can be used to process and visualize data much more quickly

    Our team worked with Blynk to develop app widgets that are suitable for visualizing and saving research data.  We will continue to work with them to improve these tools, and generate new tools specifically aimed at research data collection.  

    We also generated hardware devices that are useful for collecting research data.  These include an environmental monitor, a running wheel, and a feeding device.

  • Why MÍOS?

    Lex Kravitz04/17/2018 at 23:27 0 comments

    We developed MÍOS with the broad goal of addressing research reproducibility in research endeavors.  Our approach was to leverage low-cost sensors and microcontrollers to drastically lower the barriers to collecting large scale data from rodent home cages.  

    What is reproducibility?  Often, researchers in one location perform a study and publish it.  Over subsequent months or years, other researchers attempt to replicate the study, and unfortunately are often not successful.  Scientific disagreements are not a new phenomenon, in fact they are the basis for most scientific progress.  That said, we believe that cloud-based technologies can be used to: 

    1. Generate strongly powered data sets
    2. Allowing for more rapid understanding of trends in that data 
    3. Saving both time and money

    We believe that cloud based systems contain several unique advantages for research data collection.  MÍOS is an experimental concept for enabling cloud-based research studies on colony-housed rodents.  

View all 2 project logs

  • 1

    This tutorial will teach you the basic of monitoring and controlling multiple devices within Blynk.  You will learn how to easily create a mobile app, track and control two devices within the app, record data from them, and export that data for analysis.  We will use just two devices with one sensor each for this tutorial, but once you're comfortable with the concepts you can repeat these same principles to monitor dozens of devices with many sensors. If you do something cool with this please let us know in the comments! 

    We will use the Particle Photon as the microcontroller for this tutorial, but advanced users can use any microcontroller they'd like, as long as it connects to the internet.  

  • 2
    Install the Particle and Blynk apps on your phone and create accounts for each
    • Download the Particle app to your phone or tablet and make an account
    • Download the Blynk app to your phone or table and make an account.

    (For those who need quick gratification of seeing a working app scroll down to Step 9).

  • 3
    Set up both Photons to connect to the internet and the Particle cloud
    • Connect each photon to the Particle cloud.  The smartphone app will talk you through it, including connecting it to your WIFI network.  It is advisable that you become more familiar with and the Photon, so spend some time on their site.  Here are some quickstart instructions.
    • Connect a photo-resistor between GND and A5 (this is the sensor we'll track for this tutorial)

    To verify that each are functioning correctly, click the "Tinker" app, set pin D7 to "Digital Write" and pin A5 to "Analog Read".  You should be able to control the onboard LED on each photon, and read a value from the photosensor as well.

View all 9 instructions

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