An Automatic Weighting System for Wild Animals Based in an Artificial Neural Network: How to Weigh Wild Animals without Causing Stress

• Main Authors: Javier Bustamante, Carlos León, Jesús Marín, Miguel Ángel Leal, Manuel Baena, Julio Barbancho, Carlos Rodríguez, Diego Francisco Larios
• Format: Article
• Language: English
• Published: MDPI AG 2013-02-01
• Series: Sensors
• Subjects: sensor network; habitat monitoring; neural networks; computational intelligence
• Online Access: http://www.mdpi.com/1424-8220/13/3/2862

This paper proposes a novel and autonomous weighing system for wild animals. It allows evaluating changes in the body weight of animals in their natural environment without causing stress. The proposed system comprises a smart scale designed to estimate individual body weights and their temporal evolution in a bird colony. The system is based on computational intelligence, and offers valuable large amount of data to evaluate the relationship between long-term changes in the behavior of individuals and global change. The real deployment of this system has been for monitoring a breeding colony of lesser kestrels (Falco naumanni) in southern Spain. The results show that it is possible to monitor individual weight changes during the breeding season and to compare the weight evolution in males and females.