Detecting Microorganisms in Water Using Deep Learning

This Omdena Local Chapter Challenge runs for 6 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by San Jose, USA Chapter.

The problem

Normally, water needs to be sent to a laboratory for tests. This is an expensive and time consuming process and the results are not immediately available at the point of use. What we need is an easily accessible and usable method for detecting microorganisms (in other words, bacteria) in drinking water.

The goals

• Create a low-cost method that is easy to access and easy to use for detecting microorganisms (bacteria) in drinking water.
• Train a CNN (or equivalent) to recognize and classify bacteria using Computer Vision techniques. Data: EMDS (Environmental Microorganism Image Dataset).
• Use inexpensive microscopes (paper/digital – with costs ranging from $20 – $100) of different magnifications (140x, 400x, 1000x) to find the best for the task.
• Deploy the trained and tested model on a mobile phone.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level. A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment. And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapter work