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We are experiencing the Fourth Industrial Revolution, where the boundary between the digital and biological worlds is blurred by a fusion of technology and innovation. Building on the Third Industrial Revolution, which automated production through electronics and information technology, the Fourth is disrupting every industry in the world — and the environmental protection industry is no exception. Big data has been one of the buzz terms in the current Revolution, and organizations around the world have been leveraging its versatility to pursue green initiatives to protect our planet.

Big data has limitless potential. When it comes to environmental protection, big data plays an important role in saving labor and time. Compared to data collected manually by scientists, big data can be collected more efficiently and provides richer insights. Here are a few interesting examples of big data being used in the green technology industry.

Vestas — Improving Performance through Data Analysis

Vestas installed sensors in turbines which monitored rotational speed, vibrations, temperatures, oil pressure filters, etc. For its latest model of turbines, up to 1,000 sensors have been installed, transmitting real-time data that is analyzed to help optimize product development and turbine performance, as well as service and maintenance.

By taking advantage of big data and analytics, Vestas has been able to increase the effectiveness of wind power to provide clean and sustainable energy. For example, big data and analytics helped Vestas’ lost production factor1 to reach 4.4 percent in 2016, which is almost four times greater than the figure in 2015, while the industry average is 3.6 percent. According to Vestas, this translates into savings of €150 million for its customers.

Siemens — Remotely Controlling over 7,500 Wind Turbines All in One

The remote diagnostics center increases energy output by reducing the time of trouble-shooting onsite and the number of visits by experts and service teams. Siemens uses vibration diagnostics and data analysis to find signs of potential malfunctions which need to be fixed.

In fact, according to Siemens, 97% of common failures can be identified and dealt with before severe damages happen. 85% of unexpected deviations can be analyzed and evaluated so that turbines can be safely restarted remotely without sending the problems to the service team2 .

1 Lost production factor is a variable defined as the electricity production generated if the turbine is operating when the wind is blowing

2http://www.energy.siemens.com/us/en/services/renewable-energy/wind-power/remote-diagnostics.htm" style=”color:blue;text-decoration:underline”>http://www.energy.siemens.com/us/en/services/renewable-energy/wind-power/remote-diagnostics.htm

Conservation International — Protecting Endangered Species with Big Data

CI uses HP’s Vertica Analytics Platform to monitor and analyze the data collected by camera traps installed in the tropical forests at 16 sites across 15 countries. The system delivers massive volumes of data on trends, tropical forest health and early warnings of endangered species for conservation efforts.

According to CI, more than three terabytes of data have been collected from two million camera traps equipped with four million climate sensors. The analytic platform has analyzed data nine times faster than previous methods. With big data and its efficiency, scientists have been able to detect ecological changes in practically real time and respond proactively to environmental threats as they emerge.

Big Data Driving a Sustainable World

Reference:

https://www.alibabacloud.com/blog/Big-(Green)-Data_p68905?spm=a2c41.11113900.0.0

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