How Terra Seismic uses Big Data in practice
Earthquakes –and associated problems like tsunamis, aftershocks and public health emergencies – take a huge toll on human life. Despite advances in medical science and emergency response, the rate of fatalities resulting from earthquakes has increased gradually over time, largely because of increased population density in areas affected by seismic activity.
Although a lot of research has been carried out into seismic activity over many years, until recently, many geologists and other academics have believed that earthquakes are, for the most part, impossible to predict.
Terra Seismic says its “Satellite Big Data” technology can predict earthquakes with 90% accuracy, anywhere in the world. The company’s algorithms monitor live streaming data from satellite images and atmospheric sensors, and analyse this information alongside historical data from previous quakes.Atmospheric conditions can show patterns of energy release, and even unusual cloud formations can give clues that a quake may be about to occur.When predictive modelling techniques are applied to this amalgamated data, far more accurate predictions can be made.
Since first testing this technology in 2004, Terra Seismic says it has predicted 90% of major earthquakes.
The technical details
Terra Seismic captures and monitors data from environmental monitoring stations on the ground in key areas of seismic activity, as well as live streaming satellite images and historical seismic activity data. The company has created its own opensource, custom algorithms using Python to analyse the data, and these algorithms process large volumes of live satellite data every day. Data is stored and distributed from Terra Seismic’s in-house Apache servers.
Ideas and insights you can steal
The combination of predictive modelling and statistical analysis, backed by large amounts of real-time data, shows us how even things that were previously considered impossible can be achieved. Humans may not recognise that a certain pattern of activity in data correlates to a particular likelihood of an event taking place. (In this case, the event is an earthquake, but, in theory, it could feasibly apply to any type of activity and event.)Whatever you are trying to predict, if there is a correlation to be found, then a computer will be able to spot it.
You can read more about how Terra Seismic is using Big Data to drive success in Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results.
Bernard Marr is an internationally bestselling author, futurist, keynote speaker, and strategic advisor to companies and governments. He advises and coaches many of the world’s best-known organisations on strategy, digital transformation and business performance. LinkedIn has recently ranked Bernard as one of the top 5 business influencers in the world and the No 1 influencer in the UK. He has authored 16 best-selling books, is a frequent contributor to the World Economic Forum and writes a regular column for Forbes. Every day Bernard actively engages his almost 2 million social media followers and shares content that reaches millions of readers.