Is machine learning the future of species conservation? Pooling of biodiversity-related data by museums and development of big data solutions are propelling this trend.
The role of big data in biodiversity related issues is rising. A living being leaves such enormous amount of data that it’s difficult to conceive for human mind. This does not frighten the researchers in this field. Following the same trend, natural history museums are building their databases and opening them up for public. For instance, Natural History Museum in London and its ‘counterpart’ National Museum of Natural History in Paris have provided people open access to their database. With contributions from people around the world, they have developed a gigantic database called PREDICT that acts as a tool for predictive analysis on evolution of biodiversity. It contains no less than 3.2 million records from over 26,000 locations and represents over 47,000 species.
This innovation is in line with the recommendations given by IT giants. In an article published in the British newspaper The Guardian, Microsoft suggests monitoring the conservation of species and biodiversity by deploying intelligent sensors (camera, microphone, etc) that would collect data and by using artificial intelligence to capture high resolution imagery which would help understand land use patterns. The American firm also encourages governments and scientists to build a digital ‘dashboard’ to manage biodiversity.
To help conserve plant and animal species, innovative projects in this field have already developed practical solutions which are accessible to public at large. How to find out the future French champions of biodiversity? In June 2016, the Ministry of the Environment, Energy and the Sea organized the hackathon #HackBiodiv and rewarded new talents. Some of these are mentioned below:
– InvasivAlerte: This application detects the presence of invasive species in real time by analyzing the queries made on search engines and social networks. Its users can also report the presence of these species by sharing a geo-located photo.
– Greenwatch: It makes it possible to identify a species by taking its photograph. The photo is then analyzed by Google’s artificial intelligence application.
– MapPollen: This application uses the geolocated data of the different species of trees and identifies the areas which are most prone to pollen allergens. For this, it uses the data of the National Museum of Natural History and the open data of some cities.
How we improved our estimation of vegetated surfaces with Computer Vision Here at nam.R, we’re putting our hard work into building a Digital Twin of the French territory. We aggregate, clean and re-organize a large quantity of data of different […]
Overview of new practices: The data sources used in customer marketing are diverse. The traces left online by internet users are numerous. Marketers can easily observe consumers through their online shopping, apps, conversations on social media, browsing history or search […]
What are the reasons behind this gap and how can big data help resolve this paradox? It has been about twenty years that applying online has become a general practice. From SMEs to large groups, companies recruit online, either through […]
At nam.R we are working hard to build a Digital Twin of France, and to achieve that we use a lot of sources of information. One of the richest of them being aerial images. For us, humans, “reading” images is […]