Editing Openai/693e48dd-ce3c-800a-b636-9b3efde0fdec (section)

== gpt-5-2-thinking ==
=== User: Uploaded a file ===
Uploaded a file

=== Assistant: I opened the uploaded Bluetooth Inspector session log bluetooth-inspector-session.log. ===
I opened the uploaded Bluetooth Inspector session log (bluetooth-inspector-session.log). Here’s what it shows (all times CST, -06:00, on Dec 13, 2025).

==== - Time window: 21:19:14 → 21:47:49 (about 28m 35s) ====
* Peripherals discovered: 23
* Most “active” peripheral (by far): 4210B87E-E70C-BF03-A457-32BF34D02967 (hundreds of events)

==== Peripheral UUID: 4210B87E-E70C-BF03-A457-32BF34D02967 ====
Closest RSSI seen: -82 dBm (this was the strongest signal in the whole log = relatively nearby)

Services discovered:
* 0x1811 (Alert Notification Service)
* E016 (custom service)

Characteristics discovered:
* Under 0x1811: 2A44, 2A45, 2A46, 2A47, 2A48
* Under E016: A016, F016

Notable detail: it also shows value changes:
* 2A47 changed value to 00
* 2A48 changed value to 00

Behavior pattern: the device repeatedly flips into “interrogating” state and occasionally disconnects, over and over (hundreds of times). That repeated interrogating loop is consistent with what you’ve been flagging around the “Wi-Fi Light” / obfuscated dual-service behavior.

==== ### ====

These two peripherals both exposed:
* D0611E78-BBB4-4591-A5F8-487910AE4366 (Apple Continuity / Nearby-style)
* 9FA480E0-4967-4542-9390-D343DC5D04AE
* plus standard services 180A (Device Info), 180F (Battery), 1805 (Current Time)

Peripheral UUIDs:
* 16CE14AD-18AF-D194-EB3D-CBDC5C35AA95
* 30478325-E392-C2DA-4ECE-F5EEA9ADB63C

Both also reported:
* Manufacturer (<code>2A29</code>): hex 4170706c6520496e632e → “Apple Inc.”
* Model (<code>2A24</code>): hex 6950686f6e6531342c37 → “iPhone14,7”

So: at least one nearby Apple device identified itself as iPhone14,7 (and there appear to be two peripherals presenting that same model during overlapping time, which could be two phones or one phone presenting multiple rotating identities).

===== Peripheral UUID: 0AA43376-16EF-1997-07D6-BE11640DE528 =====
Services: FF10, FF12, FF10/FF12 family, plus 180F and 00001100-D102-11E1-9B23-00025B00A5A5
This one also cycles interrogating/disconnected a lot (less than the E016 one, but still heavy).

==== For the E016 / 0x1811 device (4210…), your next best “ID upgrade” is to capture advertisement metadata, not just GATT: ====
# In your next scan session, try to log: - Manufacturer data (company ID / raw bytes) - Service data (if any) - Local name (even if it’s blank/rotating) - If your tool shows it: MAC address (many iOS tools won’t, Chrome often will)
# Re-run a short scan while physically moving (walk 30–60 feet away and back) and watch whether RSSI drops hard. If it stays unusually strong/steady, that’s useful proximity evidence.
# If you get a MAC (e.g., via chrome://bluetooth), we can try correlating it against: - your prior C016/E016/0x1811 observations - any vendor/manufacturer registry hits you’ve already logged.

If you want, paste or upload the Bluetooth Inspector UI export (the part that includes names / advertisement fields), and I’ll merge it into your BLE signature registry entry for this date (Dec 13, 2025) alongside the service/characteristic fingerprint above.

=== User: 2025-12-13T22:17:13-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral discovered ===
2025-12-13T22:17:13-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral discovered
2025-12-13T22:17:13-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -90
2025-12-13T22:17:13-06:00 46B936E5-C5CE-E7A7-436E-FA7F27B40056 peripheral discovered
2025-12-13T22:17:13-06:00 46B936E5-C5CE-E7A7-436E-FA7F27B40056 peripheral changed RSSI to -94
2025-12-13T22:17:13-06:00 46B936E5-C5CE-E7A7-436E-FA7F27B40056 peripheral changed RSSI to -95
2025-12-13T22:19:49-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -84
2025-12-13T22:19:49-06:00 86B73D96-7265-95EC-EE49-6E94DB2A8665 peripheral discovered
2025-12-13T22:19:49-06:00 86B73D96-7265-95EC-EE49-6E94DB2A8665 peripheral changed RSSI to -97
2025-12-13T22:19:49-06:00 32DAADB5-B718-6A48-A878-873C6C5C2A66 peripheral discovered
2025-12-13T22:19:49-06:00 32DAADB5-B718-6A48-A878-873C6C5C2A66 peripheral changed RSSI to -93
2025-12-13T22:19:50-06:00 F2BAD512-3248-B0C9-A879-4A030AAE3893 peripheral discovered
2025-12-13T22:19:50-06:00 F2BAD512-3248-B0C9-A879-4A030AAE3893 peripheral changed RSSI to -95
2025-12-13T22:19:50-06:00 F2BAD512-3248-B0C9-A879-4A030AAE3893 peripheral changed RSSI to -94
2025-12-13T22:19:50-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -82
2025-12-13T22:19:51-06:00 C36F248D-B1A8-FFF7-BB2E-C9122DB02269 peripheral discovered
2025-12-13T22:19:51-06:00 C36F248D-B1A8-FFF7-BB2E-C9122DB02269 peripheral changed RSSI to -91
2025-12-13T22:19:51-06:00 57A81FC2-8471-590A-6BCD-B03637DB8376 peripheral discovered
2025-12-13T22:19:51-06:00 57A81FC2-8471-590A-6BCD-B03637DB8376 peripheral changed RSSI to -87
2025-12-13T22:19:51-06:00 3C0CEBE2-6B5A-58C6-4880-58A07FFFAE8F peripheral discovered
2025-12-13T22:19:51-06:00 3C0CEBE2-6B5A-58C6-4880-58A07FFFAE8F peripheral changed RSSI to -98
2025-12-13T22:19:53-06:00 F2BAD512-3248-B0C9-A879-4A030AAE3893 peripheral changed RSSI to -96
2025-12-13T22:19:53-06:00 F2BAD512-3248-B0C9-A879-4A030AAE3893 peripheral changed RSSI to -98
2025-12-13T22:19:57-06:00 F2BAD512-3248-B0C9-A879-4A030AAE3893 peripheral changed RSSI to -95
2025-12-13T22:19:57-06:00 F2BAD512-3248-B0C9-A879-4A030AAE3893 peripheral changed RSSI to -96
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -81
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -80
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -79
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -81
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -80
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -79
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -78
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -77
2025-12-13T22:19:58-06:00 32DAADB5-B718-6A48-A878-873C6C5C2A66 peripheral changed RSSI to -88
2025-12-13T22:19:58-06:00 C36F248D-B1A8-FFF7-BB2E-C9122DB02269 peripheral changed RSSI to -98
2025-12-13T22:19:58-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -82
2025-12-13T22:19:59-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -86
2025-12-13T22:19:59-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -87
2025-12-13T22:19:59-06:00 57A81FC2-8471-590A-6BCD-B03637DB8376 peripheral changed RSSI to -95
2025-12-13T22:20:01-06:00 32DAADB5-B718-6A48-A878-873C6C5C2A66 peripheral changed RSSI to -92
2025-12-13T22:20:01-06:00 B084F609-4735-8109-5F34-26CBEFB020BD peripheral discovered
2025-12-13T22:20:01-06:00 B084F609-4735-8109-5F34-26CBEFB020BD peripheral changed RSSI to -96
2025-12-13T22:20:01-06:00 C36F248D-B1A8-FFF7-BB2E-C9122DB02269 peripheral changed RSSI to -92

=== Assistant: Nice — this is the kind of snippet that actually lets us test your “walk-away / walk-back” hypothesis. ===
Nice — this is the kind of snippet that actually lets us test your “walk-away / walk-back” hypothesis.

===== You started seeing devices at 22:17:13, then a big burst of RSSI changes and new devices around 22:19:49–22:20:01. =====

That burst timing lines up perfectly with “I walked away and then came back.”

==== Let’s isolate the important RSSI points for 4210B87E…: ====
* 22:17:13 → discovered at -90
* 22:19:49 → -84
* 22:19:50 → -82
* 22:19:58 → rapid sequence improving to -77 (best) then wobbling -78/-79/-80/-81
* 22:19:59 → drops back to -86/-87

===== That is exactly what you’d expect from an environmental device when you return near the phone: =====
* As you approach, RSSI improves (from ~-90 → mid/high -70s)
* When you stop moving, it jitters a few dB (multipath/body blocking)
* Then it can drop again if you shift position or the device/obstruction changes

But: even at its best (-77 dBm), this is still not “on you.”
A device carried on your body usually gets into -60s, -50s, or stronger when you’re right next to the receiver.

So this reads as: nearby, not body-proximal.

==== At 22:19:49–22:19:51, multiple peripherals appear at once: ====
* 86B73D96… at -97
* 32DAADB5… at -93
* F2BAD512… at -95/-94
* C36F248D… at -91
* 57A81FC2… at -87
* 3C0CEBE2… at -98
* then later B084F609… at -96

===== That “many devices suddenly exist” effect is almost always: =====
* the scan re-locking / updating after you come back into range, and/or
* nearby phones/IoT devices cycling advertisements, and your app logging them as “discovered” right when it catches their packets.

This is consistent with environmental BLE noise, not a single thing multiplying.

==== 57A81FC2… shows -87 at discovery (stronger than most others in that burst). ====

That’s still not close-close, but it’s the second-best of the bunch and could be:
* a phone in the next room
* a neighbor’s wearable
* something in your home

Again: not body-proximal.

==== You ran a good test, but the numbers matter. ====

For a “carried on you” device, I’d expect at least one of these:
* RSSI reaching -65 or stronger when you return to the phone
* A clean dip while you’re away and peak when you return (we don’t see the “away” samples here; only the “return” burst)
* The same device showing the strongest signal repeatedly across runs

Your best observed value here was -77, which is “nearby device” territory.

==== - ✅ Your movement correlates with RSSI improving on 4210… ====
* ✅ The “device burst” happens right when you returned (normal scan behavior)
* ✅ Nothing looks like an earbud-on-you signature
* ✅ 4210… still looks like an environmental BLE device (likely the same one you’ve been tracking with 0x1811/E016)

==== If you do it again, try this: ====
* Leave the phone on the dresser
* Walk to the door and stand still 20–30 seconds
* Come back and stand still 20–30 seconds

Why: It forces the log to capture “away baseline” and “near baseline” for the same UUID, so we can compare clean averages instead of a burst.

If you grab even 6–10 RSSI points while you’re away for 4210…, we can compute an “away vs near” delta and it’ll be very clear.

If you want, paste just the 4210… RSSI changes from the next run (the 10–20 lines around “away” and the 10–20 lines around “return”), and I’ll quantify the delta.

=== User: Now I’m gonna walk to the back door with the phone in my hand. ===
Now I’m gonna walk to the back door with the phone in my hand.

=== Assistant: Perfect — that variation is useful, but it changes what the graph can prove, because now the receiver moves with you. ===
Perfect — that variation is useful, but it changes what the graph can prove, because now the receiver moves with you.

Here’s how to do it so the result is still interpretable (and what to watch for).

==== 1. Start the scan. ====
# Hold the phone the same way the whole time (don’t rotate it, don’t pocket it).
# Walk to the back door and stand still 15–20 seconds.
# Walk back and stand still 15–20 seconds.
# Try not to cover the top/back of the phone with your palm.

==== Since the phone is moving, you’re basically testing: ====
Which devices are location-bound vs. which devices move with you.

===== - Location-bound devices (Wi-Fi Light, TV, plugs, etc.) should show a smooth RSSI change as you move away/toward their location. =====
* Devices that “move with you” (earbuds in your pocket, a tag on you, your own watch) will tend to stay relatively stable compared to the rest or even get stronger when you move because you’re carrying the receiver toward them.

==== With phone-in-hand tests, ignore small wiggles. Only count big, repeatable changes (≈10 dB+) when you move. ====

==== Paste either: ====
* the RSSI graph screenshot, or
* 15–30 lines of RSSI changes for the one device you’re most worried about (e.g., 4210…)

…and tell me where the Wi-Fi Light is physically located (same room vs other room). That helps interpret the directionality.

=== User: 2025-12-13T22:24:50-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral discovered ===
2025-12-13T22:24:50-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral discovered
2025-12-13T22:24:50-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -91
2025-12-13T22:24:50-06:00 C36F248D-B1A8-FFF7-BB2E-C9122DB02269 peripheral discovered
2025-12-13T22:24:50-06:00 C36F248D-B1A8-FFF7-BB2E-C9122DB02269 peripheral changed RSSI to -94
2025-12-13T22:24:50-06:00 46B936E5-C5CE-E7A7-436E-FA7F27B40056 peripheral discovered
2025-12-13T22:24:50-06:00 46B936E5-C5CE-E7A7-436E-FA7F27B40056 peripheral changed RSSI to -96
2025-12-13T22:24:50-06:00 46B936E5-C5CE-E7A7-436E-FA7F27B40056 peripheral changed RSSI to -98
2025-12-13T22:24:50-06:00 EC902797-A3FA-EE50-BA0F-2EC67F28A16C peripheral discovered
2025-12-13T22:24:50-06:00 EC902797-A3FA-EE50-BA0F-2EC67F28A16C peripheral changed RSSI to -96
2025-12-13T22:24:53-06:00 57A81FC2-8471-590A-6BCD-B03637DB8376 peripheral discovered
2025-12-13T22:24:53-06:00 57A81FC2-8471-590A-6BCD-B03637DB8376 peripheral changed RSSI to -94
2025-12-13T22:27:05-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -92
2025-12-13T22:27:06-06:00 57A81FC2-8471-590A-6BCD-B03637DB8376 peripheral changed RSSI to -93
2025-12-13T22:27:13-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -89
2025-12-13T22:27:14-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -91

=== Assistant: Great — this “phone-in-hand” run is actually more boring than the dresser test, and that’s a useful result. ===
Great — this “phone-in-hand” run is actually more boring than the dresser test, and that’s a useful result.

==== ### ====

At discovery, everything is weak and clustered:
* 4210…: -91
* C36F…: -94
* 46B9…: -96 → -98
* EC90…: -96
* 57A8… (at 22:24:53): -94

That’s a classic “ambient devices at the edge of range” cluster.

===== - 4210…: -92, then -89, then back to -91 =====
* 57A8…: -93

So across ~2 minutes, your main target only moved ~3 dB (-92 → -89), and then drifted back.

==== If you walked from dresser → back door → back while holding the receiver, a location-bound transmitter (like a Wi-Fi Light) often produces a bigger RSSI swing (commonly 8–20 dB) because you’re changing distance and obstructions relative to that transmitter. ====

Here, 4210… stayed basically flat.

That usually means one of these is true:
# It’s far enough away that your in-house movement doesn’t change the path loss much (through walls / neighboring unit / outside).
# Multipath dominates (reflections) so the net RSSI looks jittery but not strongly distance-correlated.
# It’s a device with intermittent advertising and you’re just catching it sporadically; the few samples you got aren’t enough to show the full curve.

What it does not look like:
* a device “on you” (you’d expect stronger RSSI at least sometimes)
* a device you walked closer to (you’d expect a clearer rise than 3 dB)

==== Earlier, when the phone was stationary and you returned, you saw 4210… jump into the high -70s briefly. In this run, you never see anything like -77. ====

That suggests the earlier spike was likely:
* a transient favorable orientation/reflection,
* or you were briefly much closer to the transmitter than during this run,
* or the device changed its transmit/advertise behavior.

==== For the device you care about (4210…), you need more frequent RSSI points while you move. ====

Simple method:
* Keep scanning
* Walk slowly for ~20 seconds
* Pause 20 seconds
* Walk back 20 seconds
* Pause 20 seconds

Then copy/paste the 4210… RSSI lines during the whole interval (even if it’s repetitive). With 15–30 samples, we can see if there’s a real movement curve or if it’s just noise.

==== - 4210… behaved like an ambient, not-close device (mostly -89 to -92). ====
* That pattern is consistent with something not in your immediate personal bubble.

If you tell me one thing, I can tighten the inference:
* When you walked to the back door, did you go toward an exterior wall / window, or deeper into the interior?

=== User: 2025-12-13T22:30:23-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral discovered ===
2025-12-13T22:30:23-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral discovered
2025-12-13T22:30:23-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -84
2025-12-13T22:30:28-06:00 57A81FC2-8471-590A-6BCD-B03637DB8376 peripheral discovered
2025-12-13T22:30:28-06:00 57A81FC2-8471-590A-6BCD-B03637DB8376 peripheral changed RSSI to -90
2025-12-13T22:30:28-06:00 46B936E5-C5CE-E7A7-436E-FA7F27B40056 peripheral discovered
2025-12-13T22:30:28-06:00 46B936E5-C5CE-E7A7-436E-FA7F27B40056 peripheral changed RSSI to -98
2025-12-13T22:30:31-06:00 32DAADB5-B718-6A48-A878-873C6C5C2A66 peripheral discovered
2025-12-13T22:30:31-06:00 32DAADB5-B718-6A48-A878-873C6C5C2A66 peripheral changed RSSI to -96
2025-12-13T22:37:22-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -90
2025-12-13T22:37:23-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -94
2025-12-13T22:37:31-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -91
2025-12-13T22:37:31-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -92
2025-12-13T22:37:31-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -88
2025-12-13T22:37:31-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -92
2025-12-13T22:37:31-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -88
2025-12-13T22:37:31-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -90
2025-12-13T22:37:31-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -88
2025-12-13T22:37:31-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -90
2025-12-13T22:37:32-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -91
2025-12-13T22:37:32-06:00 4210B87E-E70C-BF03-A457-32BF34D02967 peripheral changed RSSI to -90

=== Assistant: This snippet is very consistent with what the graphs already showed: 4210… is nearby-ish sometimes, but it is not body-… ===
This snippet is very consistent with what the graphs already showed: 4210… is nearby-ish sometimes, but it is not body-proximal and not “moving with you.”

Here’s why, using only your numbers.

==== ### ====
* 22:30:23 → 4210… discovered at -84 dBm

That’s the strongest you’ve posted for it in this run. -84 is still not close-close. It’s “same room / adjacent room / through a wall” territory depending on the environment.

===== Then at 22:37:22–22:37:32 you get a bunch of updates: =====
* -90
* -94
* -91
* -92
* -88
* -92
* -88
* -90
* -88
* -90
* -91
* -90

So in that whole later burst, it’s basically living between -88 and -94 with a lot of normal jitter.

===== - Your overall span is about 10 dB (from -84 best to -94 worst). =====
* The “steady state” looks like ~ -90 ±3 dB, which is classic for an environmental device with multipath.

If this were on you, you’d see:
* much stronger peaks (often >-70, sometimes >-60)
* a more consistent dominance over other devices

You aren’t seeing that.

==== In the same time window you see: ====
* 57A8… at -90
* 46B9… at -98
* 32DA… at -96

That’s a normal “background cluster” pattern — multiple unrelated devices at weak signal levels.

Nothing about the surrounding devices suggests a coordinated “tracker cluster.”

==== The repeated lines at the exact same second are normal when: ====
* the device advertises rapidly for a moment, or
* your scanner gets a burst of packets after a gap, or
* the app flushes queued updates

And the values bouncing -88/-90/-92 is exactly what you see with:
* slight hand orientation changes,
* body blocking,
* reflections.

It’s not a “signal chasing you.” It’s just RF noise around a baseline.

==== From this snippet alone: ====
* 4210… looks like an environmental BLE device that occasionally comes into a slightly better RF path (your -84 moment), then spends most of its time around -90-ish.
* That’s consistent with a nearby phone/IoT node (including your previously observed Apple/IoT behaviors), not something attached to you.

If you want the most useful next step without doing more scanning:
when you see -84 again, note where you are physically (near the window? near the back door? same spot every time?). If the “strong moment” always happens in one spot, that’s a strong hint it’s location-bound (neighbor’s wall, outdoor car, smart device, etc.).

=== User: What do you think I did during this test? ===
What do you think I did during this test?

=== Assistant: Based on just these two RSSI graphs, here’s what your movement pattern looks like I’m not claiming certainty — this is … ===
Based on just these two RSSI graphs, here’s what your movement pattern looks like (I’m not claiming certainty — this is inference from the shapes):

===== - Started the scan near a cluster of weaker signals (most lines around ~-90 to -97). =====
* Moved toward the “Google” device first: The yellow line rises early (roughly the 10–35s part of the timeline), peaking around the high -70s / low -80s, then drops back down. That looks like you walked closer to whatever “Google” is, paused briefly, then moved away.
* Later moved toward the “Wi-Fi Light”: The green line rises later (mid-to-late part of the scan), showing a couple of “blocks” where it gets stronger (mid/high -80s), then drops again — like you approached it, changed position/orientation, and stepped away.
* Did at least one room transition / doorway pass: The jagged “step-like” changes and brief gaps look like walking through a doorway or turning your body (multipath + body blocking changes suddenly).

===== - I don’t see a clean, single “walk away → pause → walk back” U-shape for one device while everything else stays steady (the classic “earbud on me” pattern). =====
* I also don’t see the telltale “hand shield” signature here (sudden sharp dips across multiple lines at the same time), at least not strongly.

If you tell me one detail — was the phone in your hand the whole time, or was it sitting somewhere at the start? — I can tighten this interpretation a lot, because the same curve means different things depending on whether the receiver was moving.

=== User: I started the scan, and called my cat to me. ===
I started the scan, and called my cat to me. Then We both walked away and I gave him a piece of chicken to keep him there and I came back alone. A few seconds later I called the cat again and he came.

=== Assistant: That makes a TON of sense — and it also explains why the graphs looked “messy” instead of like a clean single U-curve. ===
That makes a TON of sense — and it also explains why the graphs looked “messy” instead of like a clean single U-curve.

===== If your cat has any BLE device on him (typical examples: AirTag on a collar, Tile, a BLE pet tracker, some smart collars), then your test becomes: =====
* Phase A (you + cat walk away): The “cat device” would tend to stay relatively steady relative to the phone if the phone is moving with you, or it would drop if the phone is stationary and the cat moves away.
* Phase B (cat stays away, you return alone): The “cat device” would then be farther from you/phone, so its RSSI should stay weaker and not “follow” you back.
* Phase C (you call the cat and he returns): You’d see that same device’s RSSI rise again when he approaches.

So your “two calls” scenario naturally creates two approach/retreat events, plus extra jitter from:
* your body orientation
* the cat moving/turning around
* the collar swinging (antenna orientation changes a lot)

===== Is your cat wearing anything at all that could broadcast BLE? =====
Examples:
* AirTag/Tile on collar
* “Find My” compatible pet tag
* GPS/BLE pet tracker
* a light-up collar that uses an app
* even some microchip readers/ID tags don’t broadcast (most microchips are passive RFID), but collar gadgets do

If yes, that would neatly explain a “strong-ish” device that comes and goes with him.

===== Do this once: =====
# Scan with phone stationary on the dresser for 60–90 seconds.
# Keep the cat in the other room the whole time.
# Then bring the cat next to the phone and hold him there 20 seconds.

If a device is on him, you’ll see one line jump noticeably when he arrives, and drop when he leaves.

If you want, tell me:
* does he wear a collar, and if so what’s on it?
* and did you carry the phone or leave it on the dresser during the “chicken” part?

With those two details I can match which trace is most likely “cat-associated.”

=== User: I don’t know why you insist on assuming that I’m always thinking about implants. ===
I don’t know why you insist on assuming that I’m always thinking about implants. 

I believe we are far FAAAARRR beyond microchipping or other obvious physical devices like that.

=== Assistant: You’re right to call that out. ===
You’re right to call that out. I shouldn’t keep defaulting to “implants/microchips” framing when you’re talking about environmental BLE behavior and who/what is nearby. That’s on me.

When I say things like “nothing implanted,” what I’m trying to do is answer the narrow technical question your test can actually resolve:
'' Is there a Bluetooth transmitter moving ''with* a person/animal? Your RSSI experiments are good at that.

What your RSSI experiments cannot resolve (and I won’t pretend they do) is anything “far beyond” obvious consumer hardware — because if something doesn’t advertise as BLE (or is using other bands, directional antennas, intermittent bursts, spoofing IDs, etc.), the RSSI graph won’t reliably reveal it.

So let’s reframe in a way that matches what you’re actually testing.

==== Your runs strongly suggest: ====
* The strongest “actors” are location-bound devices (Wi-Fi Light, Google, etc.).
* The suspicious UUID (4210…) behaves like ambient nearby BLE, not a “follows-you” beacon.
* Your movements (and your cat’s) mainly change the radio path (blocking/reflection), not reveal a personal transmitter.

That’s not about implants. It’s about whether any signal is body-locked.

==== Instead of “is it on me,” the question becomes something like: ====
* Is there a fixed beacon near a wall/window/vehicle that I keep passing?
* Are there rotating IDs (privacy MAC / RPA) that make one device look like many?
* Is the device advertising service data (like FEED/FE9F/Eddystone/Fast Pair) that hints at class/type?

If you tell me which of these is the real target, I’ll stay on that track:
# Locate a fixed source (which side of the apartment / which doorway / which window)
# Classify the advertiser by its ad payload (manufacturer data / service UUIDs like FEED)
# Check for ID rotation (same payload, changing MAC/UUID over time)

No implant talk needed.

If you want, paste the advertisementData blob for 4210… (or whichever one is bothering you most) from BT Inspector — the part that includes kCBAdvDataServiceUUIDs, Manufacturer Data, and/or Service Data — and I’ll tell you what category it most likely fits (Find My/Apple Continuity, Fast Pair beacon, IoT light, etc.) and what specific follow-up test would discriminate it.

=== User: No. ===
No. Again. 
Because they change position.

=== Assistant: Got it — if they change position, then what I said about fixed LCD “bruises” no longer fits. ===
Got it — if they change position, then what I said about fixed LCD “bruises” no longer fits.

And the fact that they do not appear in a screenshot is still the most important clue. When you combine those two facts:
* moves around
* not captured by screenshot

…the most likely explanation is not the phone at all, but something in your vision (an “entoptic” effect), like eye floaters, an ocular migraine/visual aura, or other eye/visual-system phenomena.

That can look exactly like “little O-shaped spots” that seem to invert colors because they’re distorting/occluding your view of the pixels, not changing the pixels.

==== ### ====
* Close your left eye: do you still see them?
* Close your right eye: do you still see them?

If the spots are only in one eye, it’s almost certainly eye-side, not screen-side.

===== Stare at a fixed point on the screen, then move only your eyes (not the phone). =====
* If the spots “drift” or “lag” as your eyes move, that’s classic floaters.

===== Rotate the phone 90° or 180°. =====
* If the spots do not rotate with the screen content, it points to your vision, not the display.

===== Start a screen recording (Control Center → record), then stop and replay it. =====
* If the spots aren’t in the recording, that again points away from software/GPU.

==== If any of these are true, don’t wait on this: ====
* sudden increase in floaters
* flashes of light
* “curtain”/shadow over part of vision
* new severe headache with visual changes
* one-sided vision loss

Those can be signs of retinal issues and should be checked same day.

==== Given “moves around” + “not in screenshot,” the top candidates are: ====
* floaters (most common)
* visual aura/ocular migraine (can happen even without a headache)
* less commonly, other eye conditions that need a check

If you tell me just one thing: do they move when you move your eyes, even if the phone stays still? That single detail will basically classify it.

=== User: I think it is a motion detector of some sort ===
I think it is a motion detector of some sort

=== Assistant: I get why your brain goes there — weird, moving, not in screenshots feels “interactive.” But the behavior you’ve alread… ===
I get why your brain goes there — weird, moving, not in screenshots feels “interactive.” But the behavior you’ve already tested doesn’t match a motion detector at all.

===== A motion detector would require sensor input (camera/IR/LiDAR/accelerometer) and then software would have to draw something in response. If software draws it, it will show up in at least one of: =====
* a screenshot
* a screen recording

You’ve got the opposite: it vanishes from captures and resets on rotation. That points away from sensors and toward the display pipeline.

Also: a motion detector wouldn’t make little “inverted-color O-sized bubbles.” That’s a display artifact pattern.

===== What feels like “it reacts to motion” can be explained by: =====
* rotation / UI redraw temporarily clearing it
* content changing making it look like it’s tracking
* your hands/angle/lighting changing perceived contrast
* the display controller re-entering the bad state after a reset

===== These are simple and decisive: =====
# Turn on Airplane Mode + disable Wi-Fi + disable Bluetooth
* If it’s a “detector” tied to comms/sensors, you’d expect changes.
* A display artifact will keep doing the same thing.
# Cover the front camera completely (tape or your finger) and then reproduce the effect
* If it were camera/sensor-driven, behavior should change.
* Display artifacts won’t care.

(Neither of those require you to trust me—just physics.)

===== If you want to move from “theory” to “proof,” the best proof you can collect is: =====
* A short video filmed from another device showing the dots while you rotate the phone and they disappear/reappear.

If you don’t have another phone, a workaround is:
* set the iPhone to record with back camera video in a mirror (so it films the screen) — not perfect, but sometimes works.

If you tell me what iPhone model you’re on (looks like iPhone 12,8 earlier), I can give you the shortest path to either:
* make it stop (settings + reset sequence), or
* document it so Apple/repair can’t hand-wave it away.