CritterCross

Inspiration The catalyst for CritterCross Alert was a deeply unsettling and heartbreaking personal experience. While driving, I came across a small baby monkey injured on the side of the road. It was bleeding, terrified, and in immense pain. As I stood there, a profound sense of helplessness washed over me—I wanted to help, but there was no immediate system in place to do so. These animals are living beings that feel pain just as we do; the forest is their home, and they deserve to be safe within it. I realized I couldn't just walk away and forget it. I needed to channel that distress into an actionable solution to protect our wildlife and ensure no one else has to feel that same helplessness.

What it does CritterCross Alert is a community-driven mobile application and data dashboard designed to promote safe coexistence between humans and wildlife. It actively prevents collisions and aids injured animals through three core features:

Dynamic Geo-fenced Alerts: Warns drivers of approaching animal hotspots with scaling alert radii based on their speed.

Crowdsourced Intelligence: Allows users to log live sightings, which are processed through a time-decay algorithm so drivers only see relevant, active threats.

Emergency SOS Loop: An integrated dispatch system that connects drivers directly to wildlife rescue organizations for rapid triage of injured animals.

How we built it As a solo developer, I built the entire conceptual framework, application logic, and UI/UX architecture using Google AI Studio.

Ideation & Logic Setup: I used Gemini models within AI Studio to iteratively map out the complex logic required for the app, such as the dynamic alert radii and the hotspot mapping features.

UI/UX Prompting: I generated the specific "dusk-shift" color palette (optimized for low-light dawn/dusk driving when most collisions occur) and designed the 10 mobile screens and 6 dashboard views purely through advanced, structured prompting.

System Instructions: By configuring custom system instructions in Google AI Studio, I was able to rapidly simulate how the app's backend would triage an SOS report, ensuring the workflow between a driver and a rescue dispatcher was seamless.

Challenges we ran into Building this as a solo project under a strict time limit was immensely challenging. Turning a raw, emotional idea into a practical, workable software architecture required intense focus. I struggled with figuring out how to simulate real-world testing environments without a live user base. Furthermore, increasing the app's utility so it was truly animal-friendly—and not just a human convenience tool—required multiple pivots, ultimately leading to the addition of the dedicated SOS Rescue Dispatch dashboard.

Accomplishments that we're proud of I am incredibly proud of designing a comprehensive, end-to-end ecosystem completely on my own. Translating the helpless feeling I had on the side of the road into a functional SOS rescue feature is my most meaningful achievement.

What we learned I learned that empathy is the most powerful driver for innovation. Technically, I discovered the immense potential of leveraging large language models in Google AI Studio to accelerate software architecture and UI/UX design. I learned how to structure complex application state flows—like managing user permissions, alert details, and verification timelines—and how to design an interface that prioritizes critical safety and fast response times over generic aesthetics.

What's next for CritterCross The ultimate goal is to evolve CritterCross Alert into a worldwide, implementable platform. I plan to partner with local NGOs, integrate publicly available DOT (Department of Transportation) roadkill datasets to pre-seed the hazard maps, and develop the fully functional frontend code for both iOS and Android. My mission is to scale this network globally, transforming road infrastructure planning and saving as many innocent animal lives as possible.