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Monkey Snaps is a mobile phone-based camera trap for animal behavioral studies. With researcher workflow and harsh climates in mind, we designed a modular camera trap that transfers photographs remotely, is completely compartmentalized for easy maintenance, is entirely waterproof, and is minimally disruptive to wildlife. The trap is distinct from off-the-shelf models in that it uses a mobile phone, opening up the world of real-time data analysis, remote data transfer, location stamping, and a host of customizable features for various research objectives.

Collaborators: Mark Breneman, Michael Uzzi, Ryan Viglizzo


Motivation: As part of a Wildlife Observations class, we have been exposed to the work of Tony Di Fiore, a behavioral primatologist working at the Biodiversity Station in Tiputini, Ecuador. We identified ways in which his camera traps could be improved with current technology.

Their existing camera traps present the following problems and challenges to their workflow. Firstly, the traps require a fair amount of human monitoring. Setup is challenging because there is no viewfinder access on their camera traps, so this process necessitates mounting and remounting.  Photo extraction and changing the batteries requires opening up the unit’s interior to the elements, and cannot be done remotely.  Additionally, after photo extraction, the current workflow requires human recognition of subjects in each photo which takes the largest amount of time. Within any set of images, there are several false positive triggers as well.

At the Tiputini Biodiversity Station  camera traps face some of the harshest environmental conditions. With daily rain and 80% humidity current camera traps are insufficiently designed to protect the components.  At the moment Tony's group has no usable camera traps as a result of corrosion.

Development: With these conditions in mind, we set about creating a camera trap that is entirely waterproof and never needs to be opened outdoors. We designed a system that allows for remote photo transfer and that is modular to allow the components to be readjusted in the field easily.

Software Development: We went about designing for remote photo transfer through the use of an Android phone. The Nature Calls app is opened on the phone and connected to a PIR sensor via an Arduino. The app tells the camera to take a picture whenever the PIR signal is high (triggered). The system runs with the screen off to save battery life, although we haven't figured out a way to make this system less battery intensive than their current traps. When the researcher wants to access the photos, they walk up to the camera trap with another handheld device, enable bluetooth on the trap and download the images. The images are timestamped and can have a customized naming system including gps location and other metadata. All of the code for the project is available for use and customization on github.

Hardware Development: Due to the environmental constraints, we build each piece to be enclosed in a waterproof housing and join together. This way, each piece could be moved, modified or replaced without exposing the other elements to humidity. Extra space in the Arduino housing allows researchers to add sensors to their trap, either to optimize the system against false triggers or to collect other environmental data. Due to issues with reflection within the camera housing, we added an external flash.