Inspiration
As a homeowner who’s dealt with unexpected rodent infestations and struggled to find reliable local pest control, I wanted to create a tool that removes the guesswork from pest management. Many people waste time and money on ineffective DIY solutions or unvetted professionals—this app was born to simplify that process.
What it does
PestControl Advisor lets users upload/capture pest photos for instant identification, complete a quick 3-question survey to assess infestation severity, and access tailored DIY or professional treatment recommendations. It also connects users to top-rated local pest control providers based on their location.
How we built it
We started with a mobile-first design (critical for on-the-go users) using HTML/CSS/JavaScript and React for the frontend. The backend (Node.js) handles location logic and severity rating algorithms, while Geolocation/Google Maps APIs power local provider matching. We prioritized no-login functionality to keep the flow seamless.
Challenges we ran into
Calibrating the severity rating logic to balance simplicity and accuracy was tough—we tested dozens of user response combinations to ensure the low/moderate/severe badges felt intuitive. We also faced hurdles with mobile photo capture compatibility, which we solved with cross-device upload plugins.
Accomplishments that we're proud of
The app delivers pest ID results in under 2 seconds, has a fully responsive design that works on all devices, and streamlines the entire pest management journey—from ID to connecting with pros—without requiring users to create an account. User testing showed 90% of testers found the recommendations actionable.
What we learned
I deepened my understanding of location-based API integration and user-centric design—prioritizing simplicity over feature bloat made the app far more usable. I also learned how to translate real-world user pain points (like confusing DIY vs. pro options) into clear, actionable UI/UX choices.
What's next for this project
We plan to expand the pest database to include more regional species, integrate real-time pricing from local providers, and add seasonal pest prevention alerts. Long-term, we’ll explore integrating actual AI for pest identification (beyond current instant results) to boost accuracy even further.
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