Big Data vs The Environment Challenge

If governed by the right policies, big data analytics can be a huge help in aiding scientific study on an environmental level. With the correct application of study and algorithm, the planet can benefit from harnessing the benefits it can provide.

Where Big Data begins

Big Data is a term for large volumes of digital information usually on a grand scale in terms of size. It can range in many forms and focus on a person, factions of people and time frames where it is combined into larger groups of information. Once all of this information is collated, in-depth inferences are drawn up to generate results.

Big data is used to answer any amount of problems on the planet via analysis of huge volumes of information. Understanding the complex and sheer size of the information requires analytical tools and artificial intelligence.

The Next Step

With focus on climate change and global warming, scientists have worked on developing methods of combining big data and machine learning with an aim of designing gas-filtering polymer membranes.

Using plastic films as membranes in separating gases such as nitrogen and carbon monoxide, it became possible to separate carbon dioxide from other gases for purification and facilitation of carbon capture.

Selecting the materials required was where big data analytics and machine learning came in, as the thousands of plastics that could be produced had to be analyzed due to variations in chemical structure.

Environment Challenge

As it pertains to environmental policy and management, a commitment is required by companies at the opening of data streams to make data open to all. Big data has already analyzed over 700 thousand images supplied via satellite to reveal 2.3 million kilometers of forest land was lost in the first 12 years of this century as well as a loss of over 20,000 square kilometers of tidal flats since the mid 80’s.

With focus on energy efficiency from big data, large energy savings and reductions in heat were proven a thirty-fold reduction in energy required running neural network training algorithms. This is explained in further detail in the journal Nanotechnology, titled “Maximised Lateral Inhibition in Paired Magnetic Domain Wall Racetracks for Neuromorphic Computing.”

Big data analytics also can play a huge role in predicting an accurate foresight into atmospheric and oceanic shifts through data sourced through a variety of channels. This can assist potentially affected businesses and governments as well as individuals in the ability to make preparations and reduce impact and potential hazards. By tapping into environmental observations and Earth system modelling, Big data analytics and Machine learning could be utilised by nations to understand phenomena and learn from flaws and responses prior to protect from the effects of climate change.

Big data will require full collaboration on information to reach its goal pertaining to the environmental challenges, but in its earliest footsteps into the field, the results have provided key advantages in global safeguarding.