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Big-Data is helping in wildlife conservation


Big data is on the boom these days. It has been helping every field. Let us see few of the projects of Big Data in Wildlife Conservation that has used Big data and Machine Learning as their key components.
Big Data in Wildlife Conservation

2. Big Data in Wildlife Conservation

In this section, various projects are discussed below which shows the aid of Big Data in Wildlife Conservation.

2.1. The Great Elephant Census

 In Africa alone, more than 12,000 elephants have been killed each year since 2006 and if this goes on, that day is not far when there will not be any elephant left on this planet. The protection of ecosystem is vital not only to wildlife but the communities around them to complete the ecosystem cycle and Big Data is helping in the same. In 2014, a survey The Great Elephant Census was launched by Microsoft co-founder Paul Allen to achieve a greater understanding of elephants number in Africa. 90 researchers traversed over 285,000 miles of the African continent, over 21 countries to conduct this research.

One of the largest raw data sets was created in this survey. The survey has shown that African elephant numbers has become only 352,271 in 18 countries and has gone down by 30% in seven years. This highlighted the need for on-going monitoring to make ensure better response times to emergency situations. Big Data is having a huge impact on conservation efforts that is going to help protect the Elephant population of Africa.

2.2. eBird

This project was launched in 2002. It is an app that helps users’ in recording bird sightings as they find any and input this data into the app. The app was created with a target to help create usable Big Data sets that could be of value to professional and recreational bird watchers. These data sets are then being shared with professionals like teachers, land managers, ornithologists, biologists and conservation workers who have used this data to create BirdCast, a regional migration forecast giving real-time predictions of bird migration for the first time ever. This uses machine learning to predict migration and roosting patterns of different species of birds. This will provide benefits by providing more accurate intelligence for land planning and management and allowing necessary preparations for areas prone to roosting bird gatherings.
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