CEM Box

Team 45: Lab Rats

Kiran Ramjisingh, Miguel Gorres, Raahi Desai, Shashank Pachava

Problem Statement

• Identified Problem:

Current methods of monitoring wildlife populations involve frequent, manual in-person checks to confirm presence of, identify, collect data on, and release animals caught with box traps placed in an area designated for monitoring. This can lead to inefficient time spent checking many empty traps, and increased stress for the animal due to being trapped and handled. These drawbacks can be nullified with the features of our CEM (Continuous Ecological Monitor) Box.

• Target Audience:

Entire populations of animals can benefit from ecologists learning more about their dynamics and behaviors, and a world with greater biodiversity is healthier and benefits us all.

• Themes:

Environmental Monitoring, Agricultural Excellence

• Importance of the Problem:

Data collected on animals, especially target species of conservation such as rare, protected, and/or endangered species, especially in a quick and non-intrusive manner, is crucial for research and forming management plans to conserve and protect wildlife.

Project Description

• Solution Overview:

Our CEM Box is a streamlined method of collecting data on wildlife. It can be placed flush with a fence, forest edge, or other landscape feature to funnel an animal up a slope (dirt, wooden, etc.) into the CEM Box, where it will be examined in a non-intrusive and timely manner, then automatically released via an unlocked door. The data collection of the CEM Box can help determine population counts and density, spatial distribution, habitat data, and be used to limit disease spread. It also increases the ability to detect the presence of an elusive animal, pests, or its intended use: a target species for conservation,.

• Unique Value Proposition:

The CEM Box allows for automated data collection and release, reduced travel time to study sites, and safe monitoring of many species.

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Technical Description

• Hardware Components:
• Control System: Arduino Uno
• Animal detection and data collection: Knock Sensor, Ardu-camera, Ultrasonic sensor
• Animal release: Servo motor
• Software & Tools: Arduino IDE and Python for image analysis
• Technical Challenges: Learning to use the Arduino Camera and laser-cut construction, acquisition of materials and tool shortage

Live Demo

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Future Work:

• Implement camera and image analysis for wildlife sorting
• Include a load cell array to collect weight data in addendum to size
• Install battery and SD card for full autonomy
• Increase weather/animal resistance, more sturdy housing

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Any Questions?