Launching today

Trailsense

Launching today

See where people are hiking, without cameras

5.0•2 reviews•

60 followers

See where people are hiking, without cameras

5.0•2 reviews•

60 followers

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Trails can get busy, and others stay empty, but how do you know? We built Trailsense to answer that. Our solar-powered nodes count hikers using anonymized wifi probe requests, the pings a phone sends while scanning for known networks. A dashboard turns those counts into a clear view of how busy each trail is over time. No cameras, no app for hikers to install, and no personal data ever leaving the device.

Trailsense Reviews

Name: Trailsense
Rating: 5.0 (2 reviews)

The community submitted 2 reviews to tell us what they like about Trailsense, what Trailsense can do better, and more.

5.0

Based on 2 reviews

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•42 reviews

What's great

Bypassing the privacy gridlock of public space monitoring by avoiding optical tracking (cameras) or active user participation (apps) is a massive structural win for municipal data collection. Relying on passive WiFi probe request sniffing allows the system to tap into the background beaconing loops that modern smartphones already execute, completely eliminating user-onboarding friction. The core engineering achievement here is the edge-computing isolation: the nodes process incoming radio frames locally, stripping hardware identifiers instantly and emitting only plain, aggregated integer counts over low-power networks. Open-sourcing the node firmware on GitHub is the ultimate trust mechanic for public infrastructure projects, providing the definitive compliance transparency that local tourism boards and environmental agencies require to clear strict data privacy audits.

What needs improvement

The primary technical strain point for passive WiFi sniffing is the erratic nature of modern OS-level MAC randomization and background scan throttling. Both iOS and Android continuously update their probe intervals based on whether a device is moving, locked, or running specific background apps, meaning a node can easily overcount a group that stops to rest or completely miss hikers with aggressive power-saving protocols active. The dashboard needs a highly sophisticated calibration heuristic to translate raw ping telemetry into accurate physical headcounts, accounting for users carrying multiple wireless devices (like smartphones paired with smartwatches). On the hardware side, deploying independent solar-powered IoT nodes under heavy forest canopies or in high-alpine environments means the units face severe solar charging degradation and harsh thermal cycles that will test battery resilience and casing seals over a full winter season.

vs Alternatives

I’ve looked into alternative public trail-monitoring frameworks, ranging from traditional physical counters like pneumatic pressure pads and infrared break-beams to heavy optical surveillance cameras and aggregated third-party fitness app data (like Strava Metro). While infrared beams are simple, they are highly fragile, frequently tripped by wildlife, and fail to capture group density or directional flow. Camera setups are an absolute legal and GDPR nightmare for municipal deployments in open nature. Fitness app data provides excellent detail but introduces severe demographic bias, capturing only enthusiast runners and cyclists while ignoring casual walkers. I chose to back the Trailsense architecture because it provides an un-intrusive, municipal-grade mesh network that delivers objective, real-time density metrics without turning public wilderness into a surveillance state.

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