Data Mining Paves the Way for a Better Understanding of Seismic Activity | Automation.com

Data Mining Paves the Way for a Better Understanding of Seismic Activity

Data Mining Paves the Way for a Better Understanding of Seismic Activity

By Andre Blanchard, Data Analyst 

Data mining continues to be a useful tool for industries all over the world. The rise of big data has brought about an even larger and richer pool of information available, which means that companies who rely on data mining are now incorporating automation as the necessary next step. Although data mining still relies on researchers and data scientists to input parameters and define search functions, automation can help crunch through large quantities of data once these constraints are set.

When handled effectively, data mining combined with automation can help advance industries and even save lives. Just last month, researchers from the Los Alamos National Laboratory were able to track seismic activity through data mining, resulting in a better understanding of how stress impacts the earth’s crust. Here in North Carolina we were recently hit by yet another string of earthquakes earlier this year, and the findings from Los Alamos have the potential to help earthquake prevention measures nationwide. 


Opportunities and Challenges in Automating Data Mining and Analysis

The researchers of the Californian earthquake study relied on a combination of automation and data mining to extract information from over 100 terabytes of data. By creating templates from previous seismograms, the researchers are planning to automate this template onto the full archive of recorded signals moving forward. Already, their work has uncovered small earthquake patterns and foreshocks that previously went undetected. 

The team also uncovered fault structures that will help in the construction of more accurate models for the surrounding area. These findings support other work being done at the research facility, most notably their use of machine learning to study earthquake simulations. 

All in all, the potentials of automation in data mining are only beginning to be explored as related software is on the rise. Market Research Gazette reports a CAGR of 9.1% from 2018 to 2025, and the promise of this projected billion-dollar industry has led to a spike in demand for experts in the field of data mining and automation — something that current talent pools are not prepared for. With this limited supply of expertise in mind, Yoss details that freelancers with data mining skills can fill these roles much faster because of their flexibility and availability. This provides a solution for companies looking to get necessary skilled labor from the top 1% of tech talent at a more efficient rate. Emerging data mining trends cut across a whole range of industries, thus emphasizing the need for more skilled professionals.

To further this discipline, tech professionals are at a unique position to develop the skillsets needed for data mining. While the Los Alamos research speaks to the increasing use of spatial and geographical data sets, data mining can also be used on multimedia formats and seasonal trends. Distributed data mining is another innovation just beyond our reach, where companies can collect information across different locations and organizations.



Going Beyond the Laboratory

With more information on how earthquakes happen and how we can predict them, the California seismic movement study also sheds light on how to develop better building practices to protect against earthquake damage. This news is timely, as designs for US nuclear plants are being revamped to protect against power loss, which requires scientists to amass data on recent nuclear power outages in order to determine their causes. Part of this involves assessing the external factors to nuclear power outages, which means that the geographic models and data sets that emerge from this earthquake study will prove very useful. 

The results also come at a time when businesses are trying to make their structures smarter and more tech-friendly. Automated and AI-enabled elevators promise to make buildings more energy-efficient while managing passenger traffic, and companies can now use these findings to ensure that this new technology includes better safety protocols in the event of an earthquake. Smart elevators rely on dispatched control systems and destination info, meaning there is ample opportunity to ensure that these communication technologies can also report power shortages across their system in the event of a natural disaster. 

As new strides in research and innovation are being made to utilize data mining in more fields, the technology is expected to have huge impact in furthering public knowledge and supporting private businesses.



About the Author

Andre Blanchard is an Atlanta-based data analyst with a passion for harnessing information for a wide variety of applications in areas like manufacturing, construction, and agriculture. When he’s not working, Andre enjoys reading and fishing. Feel free to reach Andre at [email protected] for any questions.

Photo by Markus Spiske on Unsplash

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