Hi all,
with a team, we started developing, since one/two months, an experimental Java application that can be used to monitor earthquakes world-wide in real time.
It enables selection of seismic stations downloaded from publicly available seismic networks via fdsnws services supplied by real time data from publicly available seedlink servers.

All the calculation are made by self-made algorithms by Jakub.
Magnitude is estimated just empirically by trying to fit the observed data with some logarithmic functions. It basically uses the maximum intensity to determine the Magnitude. Initially we had implemented Md magnitude, but it just gave a lot of false values.

Seismic wave travel time table, are generated using TauP seismic travel time calculator and iasp91 model.

The correct hypocenter is calculate using a Sunflower seed arrangement. Making the Hypocenter search more effective and distributes the searched points evenly, based on the stations P and S waves.

Thanks @YacineB . I’m working on a similar project (estimating quake magnitudes) and following a similar process, so just wanted to reassure myself I wasn’t wasting my time!

I’m working on an estimation algorithm for local (close) quakes which are usually small in magnitude. The problem is that most quake magnitude estimation methods are aimed at big quakes as these are important to quickly assess for Tsunami warnings etc. As a result they typically use quite low frequencies (down to P=30s, or 0.033Hz say). At that frequency, small local quakes don’t overcome the background noise, so the magnitude is over estimated. If you use a higher bandpass floor the method, of course, under-estimates the magnitude, so I’m working on statistically recalibrating the coefficients to suit a higher bandpass floor (I’m working with 0.7Hz as that’s what I have most data for).

Fantastic Software! I use it alot while idling around in the house, has so much potential!
Here’s a video of New Zealand of 2 Earthquake’s occuring in under 3 minutes.
(One Weak and Shallow, One Light and Deep Down)