CS Biodiversity
Biodiversity and Ecology Information Platform
In the past 10 years, infrared trigger camera and camera trap technology have been widely used in nature reserves because of its obvious advantages over traditional survey methods, especially for the monitoring and research on the terrestrial large and medium-sized animals. According to incomplete statistics, camera trap technology has been used for wildlife monitoring and research in 80% of China’s national nature reserves, and images and videos of more than 200 rare and endangered species have been obtained.
Followed by a large number of camera deployments and massive amounts of image and video data are two challenges to a nature reserve. One is how to effectively store, organize and manage massive amounts of camera trap data. The other one is how to intelligently analyze massive amounts of camera trap data. To help nature reserve solve these challenges, the Chinese Biodiversity Observation Network – Mammals (Sino BON-Mammals) and Computer Network Information Center (CNIC), CAS developed an open cloud service for camera trap data management and intelligent analysis. Based on the cloud service, nature reserves will be able to create sample areas, add sample points, and upload camera trap data in a self-service manner. On the cloud side, the uploaded camera trap data is stored and managed, and through object detection and species identification, image and video data are intelligently analyzed based on deep learning technology.
The capabilities of on-demand provision of cloud service can help nature reserve store and manage massive amounts of camera trap data. Intelligent analysis and visualization can significantly improve the data analysis capabilities of the nature reserve. Through object detection and species identification based on deep learning technology, the service can help reserve filter out invalid data, implement automatic identification of animal species, and greatly reduce the workload of researcher and reserve staff. It also provides effective support for subsequent analysis like wildlife distribution and active rhythms, etc. This open cloud service will also be a collaborative platform for global camera trap data sharing and analysis service and contributes to global biodiversity research and protection.
Co-chairs
Joe Miller, Global Biodiversity Information Facility, Europe
Zhishu XIAO, Institute of Zoology, CAS, China
Secretariat Contacts
Yingchao PIAO, CNIC