Camera Trap 3.0

Camera Trap 3.0 will maximize the data collected and adaptability to different species and environments, communicate in real time, while minimizing cost, power, and weight.
Open for Entries

The Problem

Camera traps - trail or game cameras that fire when an animal is detected - have been used in mainstream ecological research since the late 1990s. Currently available camera trap models are primarily designed for hunters and do not necessarily capitalize on the advances in low-cost/high resolution cameras, computing power, and connectivity. The next generation of camera trap technology will require a low cost, open source instrument that can improve the speed, coverage, and capability of wildlife researchers to harness scientific data for conservation.

Even though camera traps are widely used by ecological & wildlife researchers, commercial manufacturers primarily cater to hunters. Rather than having the capability to gather multiple types of data about the target species (animal behavior, etc.) and its environment, these cameras focus solely on animal presence, leading to less robust scientific data.

Top face of the Raspberry Pi model B+
Lucas Bosch

The Challenge

The Next Generation Camera trap should be:

  • A low-cost, open-source, networked, modular system
  • Low power and/or highly efficient, durable, ultra-portable
  • Adaptable and able to capture a variety of species in various environments (including extreme environments, underwater, and/or in tree canopies)
  • Able to greatly improve the speed, coverage, and capability of wildlife researchers to harness scientific data for conservation
  • Capitalize on sensor, analytics, and camera & video improvements and advances

Camera models should aim to capture as many design characteristics as possible and/or meet the research needs extremely well in chosen species and/or environment.

Problem Statement

Accessibility to low-cost, open source technology continues to revolutionize the capability of researchers, but conservation biology has not yet taken full advantage of the opportunities available. Field scientists are still using outdated and unnecessarily expensive technology that is not built with their needs in mind, compromising the quality and ease of research. A number of the challenges camera traps face can be directly addressed through open source technology, with little to no performance tradeoffs.

False Triggering by non-animal movement leads to a rapid loss in battery life and a massive increase in image data which researchers then have to spend time sorting through. Because most commercially available trail cameras are triggered by a single passive infrared sensor, any movement, including plant life waving about in wind, will cause a trigger and subsequent picture or pictures.

Lack of durable housing for research environments also presents an issue. Because commercial camera traps are meant to be mounted to a tree and capture docile wildlife, the equipment is not designed to be rigorous enough for fieldwork with a variety of species over longer periods of time. Insects frequently breach the sealing of the camera trap and damage the wiring, and water getting into the casing destroys expensive electronics.

Respond to this Challenge!

We welcome the submission of proposed solutions to the Camera Trap 3.0 Tech Challenge. Going from an idea to a tangible solution is no easy task.

Share your project on the Digital Makerspace to shape and improve your idea. You’ll benefit from the technical expertise of the Tribe and connect to additional financial and technical resources. We’ll help you navigate the tech development process and identify market opportunities. Through collaboration, we build conservation solutions that are impactful and have the potential to scale.


Camera Trap 3.0

SenseCam - made 4 conservation

Market Shaping Phase
A commercial camera trap that's built specifically for conservationist, not just to find the biggest antlers.

NextGen Camera Trap

Conservation X Labs
Market Shaping Phase
Hi-Tech Animal Spying


Sanjana Paul [328]
Researcher in Electrical & Computer Engineering
Virginia Commonwealth University
Richmond, United States