Data has quickly become one of the most valuable resources for any organization. New tools and data-collection schemes have made it possible to gather and analyze massive sets of data—dubbed “big data.” These data sets allow us to discover patterns and relationships that we couldn’t have found with traditional approaches.
A Better Picture with Big Data
With big data and big data analytics, researchers can have the best possible picture of the issue they’re facing — allowing them to see correlations they may have missed with smaller data sets or less advanced analytic techniques.
Networks of sensors are being used to collect data on air pollution, providing the best possible information for climate researchers, businesses and governments who want to take steps to improve air quality. These groups are also adopting big data technology to process the large volumes of data collected by these sensors and create visualizations of air quality from that data. These visualizations can help researchers draw connections between geography and data—identifying areas where air pollution has trended up over time, and identifying potential causes.
Big data is also being used to improve conservation. For example, the journey of migrating birds is fraught with human-made danger—like hunting, fishing operations and navigation-disrupting light pollution. With advance notice, it’s possible for scientists to mitigate some of these dangers, pushing for moratoriums on hunting and fishing and requesting that people turn their lights out when possible.
However, these strategies only work if you know when the birds will take flight. Despite the seasonal regulatory of migration, the migratory patterns of individual birds remain challenging to predict. New migration-prediction algorithms, however, can change this.
By taking advantage of more than two decades of radar data, one forecast model was able to explain more than 80 percent of the variance in bird migration patterns—giving scientists a much better idea of when birds will need protection from human-made danger.
Using Big Data to Optimize Resource Use
Big data analytics can also help businesses and governments optimize their use of resources, cutting back on the consumption of water and energy.
For example, networks of sensors can collect data on a buildings’ water and energy use, allowing businesses to see where they may be inefficiently spending resources. In some buildings, HVAC systems are left running 24/7 or when not seasonally appropriate—like heating systems that continue to function through the summer or exhaust fans that run even when the building is unoccupied. With big data analytics, companies can pinpoint and cut back on unnecessary energy and water use.
Some advanced systems can even automatically adjust b
Current estimates show that just a one percent improvement in efficiency across the economy could save $276 billion over the next 15 years while also significantly cutting back on the use of resources—helping both businesses and the environment.
How Big Data Is Reshaping Environmental Protection
Big data can significantly help organization defend the environment. Applications of big data technology can provide better information on topics like air quality and migratory patterns, allowing researchers and organizations to mount the most informed response possible to issues like air pollution and man-made dangers to migratory birds.
Big data analytics can also help companies become more sustainable by reducing their use of resources. Automated building systems, driven by big data collection, can automatically deactivate systems that aren’t in use, saving energy.
uilding systems to optimize the use of energy. These systems can, for example, deactivate lighting when the system detects that no worker is using a certain room or corner of the office.
Analysis of energy data can also detect machine malfunctions that don’t impact operations but do create large, previously undetected energy spikes. One company discovered a rooftop unit that consumed 40 percent more energy than it needed as a result of these malfunctions.
There’s also evidence that other cost-saving measures—like the use of cloud computing over on-site processing—can provide businesses with further savings and reduced energy use.