PoseGuard: Privacy-First Farm Security at AI Sense

The Problem: Monitoring Farm Entry Without Surveillance

This year at AI Sense, I had the opportunity to work on my team’s project, PoseGuard, which began with a deceptively simple question: how can a farm keep track of who enters and leaves without recording video or sending sensitive data to the cloud?

In a farm, such as those at our local farms in Maryland, most movement is expected during the day, so when someone approaches a gate after hours, the farm needs to know whether it’s a worker finishing a shift, an animal passing through, or a person attempting to sneak in.

A Privacy-First Approach to Security

PoseGuard was built for exactly this situation, using a privacy-first approach that focuses on how people move rather than who they are. Instead of storing video, the system watches entry points and reduces human motion to anonymous skeletal stick-figure data, allowing it to flag unusual behavior while keeping identities completely private.

Built for Real-World Farm Conditions

Designed to run directly on small, low-power devices like a Raspberry Pi as well as in areas with unreliable internet, PoseGuard had to be efficient, resilient, and compliant with privacy standards like GDPR from the ground up.

Rethinking Pose Estimation Outside the Lab

Working on the project pushed us to rethink how pose estimation could function outside of ideal lab conditions, forcing us to simplify models and rethink how often data is processed so the system remains fast and reliable.

From Movement to Meaningful Alerts

In practice, this means the system can recognize actions like crouching behind equipment or climbing over a fence, log only the essential movement information, and send an alert without ever capturing a face or saving footage.

Translating Human Intuition Into Logic

One of the biggest challenges wasn’t writing code, but translating human intuition into logic and teaching a system how to understand what “suspicious” looks like when all it sees are moving joints and angles.

Trust Built on Privacy

Today, PoseGuard reliably does just that, and farmers trust it because it protects their land without compromising the privacy of the people who work there.

Looking Ahead

As the project continues, we’re exploring ways to expand its reach through alternative alert systems and broader industrial use, but its core idea remains the same: security doesn’t have to come at the cost of privacy, and thoughtful AI can quietly protect real-world spaces while staying out of sight.