Hi HN,
I built SentryRF because I was frustrated by the lack of granular control on Android for identifying unwanted tracking devices. While Google's native "Unknown Tracker Alerts" are a good start, they often feel like a black box with limited diagnostic tools.
The Tech:
Signal Analysis: Instead of just listing every BLE/wifi device, SentryRF uses signal strength (RSSI) and temporal patterns to distinguish between a "passing" device (someone walking by with an AirTag) and a "following" device (a tracker on your vehicle), even peeping-toms.
Hardware Sensors: I’ve integrated the magnetometer and ambient light sensors to help find non-broadcasting devices (like "dead" GPS units or wired pinhole cameras) by detecting magnetic anomalies and infrared emissions.
Sound Locator: I implemented an audio-guided proximity algorithm that increases beep frequency as you approach the source. It’s essentially a Geiger counter for Bluetooth and wifi signals.
Privacy (The most important part):
Zero Cloud: There is no backend. No scan data, location data, or telemetry ever leaves the device.
No Accounts: You don’t need to sign up. I don't want your email or your name.
Permissions: It requires quiet a few permissions, but I’ve documented exactly why each is needed in the app’s onboarding.
Why I’m showing it here:
I’m looking for technical feedback on the signal smoothing I’m using for the proximity tracker and any edge cases I might have missed regarding the rogue cell tower (IMSI catcher) detection.
The app has a 7-day free trial so you can test the "Pro" features (like the Sound Locator) without paying a cent.
I'll be around all day to answer questions about the stack or the detection logic!
I built SentryRF because I was frustrated by the lack of granular control on Android for identifying unwanted tracking devices. While Google's native "Unknown Tracker Alerts" are a good start, they often feel like a black box with limited diagnostic tools.
The Tech:
Signal Analysis: Instead of just listing every BLE/wifi device, SentryRF uses signal strength (RSSI) and temporal patterns to distinguish between a "passing" device (someone walking by with an AirTag) and a "following" device (a tracker on your vehicle), even peeping-toms.
Hardware Sensors: I’ve integrated the magnetometer and ambient light sensors to help find non-broadcasting devices (like "dead" GPS units or wired pinhole cameras) by detecting magnetic anomalies and infrared emissions.
Sound Locator: I implemented an audio-guided proximity algorithm that increases beep frequency as you approach the source. It’s essentially a Geiger counter for Bluetooth and wifi signals.
Privacy (The most important part):
Zero Cloud: There is no backend. No scan data, location data, or telemetry ever leaves the device.
No Accounts: You don’t need to sign up. I don't want your email or your name.
Permissions: It requires quiet a few permissions, but I’ve documented exactly why each is needed in the app’s onboarding.
Why I’m showing it here: I’m looking for technical feedback on the signal smoothing I’m using for the proximity tracker and any edge cases I might have missed regarding the rogue cell tower (IMSI catcher) detection.
The app has a 7-day free trial so you can test the "Pro" features (like the Sound Locator) without paying a cent.
I'll be around all day to answer questions about the stack or the detection logic!