AI-Powered Smart Alert System for Outdoor Security

Requirement (Business problem)

Outdoor security systems commonly generate excessive false alerts due to basic motion detection, leading to user fatigue and lowered satisfaction. The market is saturated with hardware-focused solutions, but there's a lack of intelligent software that delivers accurate, timely alerts. Our goal was to build a smart, low-cost AI layer to improve actionable insights and user trust — especially in the Dutch market.

Issue (User problem)

Users often receive irrelevant motion-based alerts or fail to notice real threats due to alert fatigue. This results in missed security events, frustration, and reduced confidence in the system. There's also little incentive for users to switch to smarter systems due to integration barriers.

Design (Solution)

I led the product vision and roadmap to build a lightweight AI-powered alert system using YOLOv11 and BOTSort for object detection and tracking. Features included dynamic masking, user-defined zones, and real-time notifications. We targeted open-API camera systems to reduce setup friction, allowing seamless integration with existing devices.

End result (Impact/Outcome)

This project was developed as a concept-stage prototype by a cross-functional team of 5–7 people. Initial tests demonstrated promising results in reducing false alerts and improving relevance through smart detection models. While not yet deployed at scale, the project validated the feasibility of offering a lightweight, AI-driven alert system with strong potential for integration into existing camera ecosystems. It also helped define a clear path toward future development and potential partnerships.

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