The Urban Wildlife Institute (UWI) specializes in studying the interactions between animal species and the ever-changing urban environments they reside in. By placing camera traps throughout the Chicagoland area, UWI monitors the different types of wildlife and their behavior during all seasons of the year. The Chicago researchers have partnered with cities across the US to create the Urban Wildlife Information Network (UWIN), where they share the data and knowledge they’ve gathered with other researchers in order for them to understand the urban ecologies in their respective cities. Studying these species patterns and habits throughout the country will help UWIN strive towards the common goal of establishing scientific standards to help solve the myriad of conflicts that arise with urban biodiversity.
Currently, UWIN researchers analyze the photos taken from camera traps and record any detections of species they find and store them in Microsoft Access databases. With photos taking up large amounts of server storage space, UWI partnered with Pariveda to move their existing photo import and animal detection process to the cloud, as well as partnering with a data science company called Uptake to use machine learning to automate the identification and classification process of these photos in the future. By accumulating animal tracking data, UWIN will be able to run reports to show trends and behaviors throughout the year and across the country.
The application is built using the Google Cloud Platform, using Angular for the front end and serverless NodeJS Cloud Functions for the backend. These cloud functions are responsible for the storage of the photos into Cloud Storage and the tracking of metadata in Cloud SQL. Pariveda also integrated with Uptake’s ML platform to train their classification model and tag future photos.
To learn more about the project click here.