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The underlying story is real, but “prevents roadkill” overstates what was demonstrated. Four students at STEM School Highlands Ranch in Colorado built Project Deer, a prototype that combines a thermal camera, AI-assisted image classification and in-car light-and-sound alerts. It was intended to give drivers more time to react to wildlife—not to steer, brake or guarantee that an animal would avoid a vehicle.
What Project Deer was designed to do
Project Deer follows a simple chain: thermal camera → image processing → animal classification → driver warning → human response. A camera mounted toward the front of a vehicle looks for heat signatures. A machine-learning system was intended to classify those thermal images as deer or other animals, then activate an alert inside the cabin.
The available reports do not establish the model’s architecture, training-set size, detection range, latency, accuracy or false-alarm rate. They also do not show that it controlled steering, applied brakes or communicated with a vehicle’s automated safety systems.
Who created it?
The team was an all-female student group at STEM School Highlands Ranch in Highlands Ranch, Colorado. Its members were:
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- PREMIUM MATERIAL: The deer whistle is made of new ABS plastic material with thicker wall thickness and durable, it can resist bad weather and work well even in extremely hot and cold weather conditions.
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- Siddhi Singh
- Dhriti Sinha
- Robyn Ballheim
- Bri Scoville
Computer-science teacher Tylor Chacon sponsored the project. The students called themselves the Rubber Duckies. Singh initiated the idea while looking for a project for Samsung’s Solve for Tomorrow competition. CBS Colorado identified the students, school and prototype.
Why wildlife collisions are a serious problem in Colorado
Colorado’s forested and mountainous roads cross animal habitat, creating frequent encounters between vehicles and wildlife. Different reports measure different parts of that problem:
| Measure | Reported figure | What it means |
|---|---|---|
| Wildlife-related collisions | About 4,000 annually | Vehicle crashes involving animals, as reported in coverage of Colorado data. |
| Driver costs | About $80 million annually | Estimated financial impact in Colorado; not a count of animals killed. |
| Reported animal deaths | 7,338 statewide in 2022 | A separate animal-death measure cited by Rocky Mountain PBS. |
| Deer deaths in Douglas County | 179 in 2022 | A local figure, not a statewide collision total. |
These numbers should not be added together or treated as interchangeable. A collision count, repair and injury costs, and recorded animal deaths describe different parts of the same broader issue, which also includes habitat fragmentation and disrupted wildlife crossings. Rocky Mountain PBS provides the local statistics and project context.
How thermal imaging could help
Unlike an ordinary visible-light camera, a thermal camera detects infrared radiation associated with heat. In principle, that can make an animal easier to notice at night or before headlights fully illuminate it. The students’ concept also addressed the need to distinguish animals from rain, snow, sleet, windblown debris and other moving or warm objects.
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Thermal imaging is not a guarantee of visibility. Performance depends on temperature contrast, atmospheric conditions, lens and sensor quality, field of view, mounting height, vegetation and the animal’s distance and angle. An animal hidden behind brush, a guardrail or a tree may remain difficult to detect. Outdoor Life describes the concept and its environmental challenges.
What the students actually demonstrated
The clearest reported demonstration used the school’s therapy dog, Daisy. Mounted on a remote-control car, the prototype recognized the dog and produced an audible warning. That shows a proof of concept: the system could connect a camera, processing hardware and an alert.
It does not establish performance with wild deer, highway-speed traffic, darkness, snow, complex terrain or animals crossing suddenly. No reported test measured warning time before impact, classification accuracy, missed detections or a reduction in real collisions.
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Competition result and funding
The Rubber Duckies won Colorado’s stage of Samsung’s Solve for Tomorrow, a competition that asks students to apply technology to community problems. They advanced to the national stage but did not win nationally. The state award provided technology and educational resources for continued development.
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What remains unproven
Detection distance and reaction time
A warning matters only if it arrives before the driver has too little distance to brake safely. The reports do not establish Project Deer’s detection range, usable warning time or performance relative to headlights.
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False alarms
People, pets, livestock, roadside machinery, other vehicles, heated surfaces, reflections and moving vegetation could all resemble a target. Frequent incorrect alerts can cause drivers to ignore genuine warnings.
Missed animals
Dense vegetation, small animals, multiple animals, sudden side entries, camera dirt or ice, poor calibration and severe weather can produce false negatives. Missing an animal is the most consequential failure mode.
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Recognizing that something is warm is easier than distinguishing a deer from an elk, bear, moose, person or equipment. The team discussed eventually expanding beyond deer to elk, bears, moose and smaller mammals, but those were future ambitions rather than capabilities established in the reported demonstration.
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Driver behavior and safety
An alert still depends on a person who may react late, misunderstand it or swerve dangerously. Drivers should never treat an experimental warning device as autonomous driving, and should avoid evasive maneuvers that create a greater risk to occupants or other road users.
Vehicle integration
A consumer system would need weatherproof mounting, reliable power, a clear field of view, compatibility across vehicles, minimal distraction, cybersecurity protections if connected to vehicle networks, and a liability framework for failures. No source establishes that Project Deer completed those steps. LiDAR was discussed as a possible future addition, not as a confirmed component.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Is Project Deer available to buy?
No verified retail product or official purchase page was identified in the available reporting as of August 18, 2026. The project was described as a prototype in redevelopment, with possible future windshield or dashboard mounting and additional machine-learning work. The sources do not establish a company, production run, patent, safety certification, automaker adoption or public field trial after the 2024 reports.
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Teacher Tylor Chacon was quoted estimating that a future third-party version might cost roughly $1,000 to $2,000, including a specialized AI-processing chip. That was a prospective system estimate, not a manufacturer’s price, current retail cost or amount consumers can pay today. A generic thermal camera or dashcam should not be assumed to provide Project Deer’s proposed classification and warning capability.
Why the headline needs correcting
Calling this a device that “prevents roadkill” suggests an autonomous intervention that the evidence does not support. The accurate description is: four Colorado high school students built a prototype intended to reduce wildlife-vehicle collisions by warning drivers when it detects a possible animal. That is a meaningful engineering achievement, while still leaving the essential safety questions—accuracy, reliability, reaction time and real-world collision reduction—unanswered.
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