According to the most recent reports, the number of wild animals roaming the planet is
predicted to decrease by two-thirds by the end of 2020. The preservation of the planet’s
natural biodiversity is essential for the better operation of our natural ecosystems. Hence,
animal ecological data collection is being accelerated by affordable and available sensors. 

These technologies have a great deal of potential for understanding ecology on a global
scale, but they are constrained by present processing techniques that ineffectively turn data
into useful knowledge. Animal ecologists may benefit from the vast datasets produced by
contemporary sensors by fusing domain expertise and machine learning techniques. 

How Ecology & Conservation will be accelerated by technology? 

Animal variety is vanishing in a previously unmonitored way. There is currently a lack of
knowledge about this loss, which affects not only genetic variety but also ecological and
behavioral diversity. Up to 17,000 of the more than 120,000 species monitored by the IUCN
Red List of Threatened Species have a status of “Data deficient”. 

Tools that can quickly analyze wildlife diversity and population dynamics at a wide scale and
with great spatiotemporal precision, from individual animals to global densities, are critically
needed. In this perspective, we seek to connect ecology and machine learning to
demonstrate how pertinent technological advancements might be used to meet this
pressing need for animal protection.

How animals are monitored Traditionally Vs Technologically? 

Traditionally, data gathering for the management and protection of animal species is done
by human field workers who count animals, watch their behavior, and monitor natural
areas. Such initiatives are costly, labor-intensive, and time-consuming. 

Due to difficulties in removing observer subjectivity and guaranteeing high inter-observer
reliability, as well as frequently inevitable animal reactions to observer presence, they might
also lead to biased datasets. Hence, the number of animals that can be viewed concurrently,
the complexity and temporal resolution of the data that can be gathered, and the size of the
physical area that can be efficiently monitored are all inexorably limited by human physical
and cognitive limitations.

New sensors expand available data types for animal ecology and recent developments in sensor technologies have significantly increased data collection capacity by lowering costs and extending coverage in comparison to traditional approaches, opening up new opportunities for ecological studies at scale. High-resolution remote sensing has made it possible to study many previously inaccessible conservation-related places, and digital tools like camera traps consumer cameras, and sound sensors are collecting vast volumes of non-invasive data.

Study of Animal Movement & Migration through Data Labeling & Annotation

The study of animal movement and migrations is being revolutionized by new on-animal
bio-loggers, such as miniature tracking tags and sensor arrays with accelerometers, audio
loggers, cameras, and other monitoring devices. These devices allow researchers to track
individuals over their lifetimes and across hemispheres with high temporal resolution.
Data labeling projects are already successfully analyzing millions of camera trap images
automatically, giving wildlife conservation researchers and professionals the information,
they need to investigate animal diversity, abundance, and behavior. Utilizing ML significantly
lowers analytical expenses in addition to pure acceleration, with the reduction in multiple
factors. Moreover, Ecological workflows that incorporate machine learning could result in
integrated hybrid modeling tools and better ecological model inputs. 

Therefore, preserving Earth’s Biodiversity is essential to keeping the equilibrium of the
planet’s ecosystem as a whole. The authorities frequently do not have access to fine-scale
data since the current animal monitoring systems are either unable to scale internationally,
do not have the proper resolutions or both.

Want to know how DATA LABELER can help you? Or do you have a Use Case in
mind? Contact Us Today!