News, articles, guides, analytics, projects and startups from the embedded industry.
Topics of the channel:
◽️ machine learning
◽️ internet of things
◽️ embedded software
◽️ advanced electronics
◽️ new engineering ideas
⤵️ Share and subscribe!
Created
Between 1 April 2019 and 31 August 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
8 measurements spanning 6 days, net +32. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 13,936–13,979 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 21:38
13,974
+7
11 Aug 2026, 23:57
13,967
+4
10 Aug 2026, 23:23
13,963
+6
9 Aug 2026, 20:21
13,957
+16
8 Aug 2026, 21:18
13,941
-3
7 Aug 2026, 19:56
13,944
+2
7 Aug 2026, 04:30
13,942
no change
7 Aug 2026, 04:23
13,942
first reading
Engagement
11 posts held, back to 11 May 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 17 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
21.8%
avg views ÷ 13,974 subscribers
Avg views / post
3,040
5 posts measured
Reaction rate
0.388%
reactions ÷ views · ER floor
Posts in window
5
of 11 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 5 August 2026
Posts held
11 (11 May 2026 – 5 August 2026)
Views total
15,200
Reactions total
59
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Aug 2026, 02:14 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
≈1,060
Videos
≈230
Links
≈737
Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
2m 20s
Average length
35s
Measured directly from 4 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
123 reactions across 11 posts, in 3 distinct kinds. The most used accounts for 80.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
99
80.5%
👌
16
13.0%
👎
8
6.50%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 11 of the 11 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 123reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 11 May 2026 to 5 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
🧠 Qapla': Training AI on ESP32 microcontroller
Qapla' is an open-source project that demonstrates training a transformer model entirely from scratch on an inexpensive ESP32-S3 microcontroller.
Instead of running a pre-trained model, it performs the complete training process—including backpropagation and weight updates—directly on the device.
Features of the project:
➡️Full on-device transformer training
➡️Handwrit…
💻 Barely Adequate Browser ESP32
Babe32 is a lightweight text-based web browser for ESP32-S3 touchscreen boards such as the Cheap Black Display. It renders a subset of HTML with 🇳🇱 LVGL library, supports optional image loading, and focuses on practical browsing without JavaScript.
Features of the project:
➡️Direct browsing with proxy fallback
➡️HTML rendering and forms
➡️Touchscreen navigation and keyboard
➡️WiFi, h…
🧑🚀 ESP32-based Plane Radar
Plane Radar is an open-source ESP32 firmware that transforms an ESP32-C3 with a 1.28-inch round display into a live ADS-B aircraft radar. It visualizes nearby aircraft in a sonar-style interface, showing their position, distance and flight details in real time.
Features of the project:
➡️Live ADS-B aircraft tracking
➡️Sonar-style radar display
➡️Flight context and weather
➡️Wireless OTA …
💻️ Nvidia quietly increases Jetson prices by up to 101%
NVIDIA has raised prices across its Jetson modules and developer kits by up to 101%, following earlier product discontinuations linked to rising LPDDR4 memory costs.
The largest increases affect the Jetson Nano module (from $99 to $199) and the Jetson AGX Orin 32GB module (from $899 to $1,799). The popular Jetson Orin Nano Super Developer Kit has also increase…
🔐 ESP32 Ad-Blocking Dongle
This project turns a low-cost ESP32-C3 microcontroller into a compact backup DNS ad-blocking device. By using smart data compression techniques, it can block hundreds of thousands of domains while operating with very limited memory and power.
Features of the project:
➡️Blocks 537,000 domains
➡️Uses 40-bit hashing
➡️Requires only 50KB RAM
➡️Offers 10ms DNS responses
The novelty of this pr…
🫡 Building a DIY Robot Vacuum with OOMWOO
OOMWOO is an open-source robot vacuum that you can build yourself using affordable, off-the-shelf components. The project is currently in active development, with a working software simulation already available while the hardware design and documentation continue to evolve.
Features of the project:
➡️Fully open hardware, firmware, and software
➡️Local-first operation with n…
📸 Optocam Zero - Raspberry Pi Zero based compact digital camera
Optocam Zero is a compact DIY digital camera built around a Raspberry Pi Zero and off-the-shelf electronic components. It is designed as a playful, easy-to-build device inspired by toy cameras, with an emphasis on portability and simplicity. The housing is fully 3D printable, making it accessible for makers to reproduce and customize.
Features of the p…
📺 The current state of LLMs in software engineering
Great video which summarizes of what's going on in software engineering when it comes to AI. As a someone who works as a software engineer himself and has been actively using LLMs for the past few years, I can say that they are nowhere close to replacing software engineers.
⛓ https://youtu.be/zfYsSFY4l18
#video #programming
👩💻 Understanding the Linux Kernel: The Linux Kernel Startup
This article explains how the Linux kernel starts up after a computer is powered on, focusing on the x86_64 architecture. It walks through the boot process step by step, from the bootloader handing control to the kernel to the early initialization of memory, hardware, and CPU features.
Complex topics such as page tables, interrupts, memory encryption, KAS…
🧠 ClawdMeter Token Dashboard
Clawdmeter is a desk dashboard built around the ESP32-S3 and the Waveshare ESP32-S3-Touch-AMOLED-2.16 board. It monitors Claude Code token usage in real time on a 2.16-inch AMOLED display, helping users keep track of their limits through animated visuals and live statistics.
Features of the project:
➡️ESP32-S3-powered dashboard with a 480×480 AMOLED touchscreen display
➡️Real-time Claud…
🤖 OpenQDD - 3D-printed open-source robotic actuator
The author designed this robotic actuator to be a powerful, easy-to-build, and relatively inexpensive solution to creating dynamic robots. Robots like Spot, Atlas, and the MIT mini cheetah easily impress the eye with their agility, speed, and overall ability to mimic natural motion. With OpenQDD, creating high-performing actuators at an affordable price is possible…
👍10👌2
Showing the 11 most recent of 11 posts we hold for @embedded_system. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank
Citation-graph rank — 763,957 of 1,169,250entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Referenced elsewhere
This handle named by sources this register does not control and did not measure — each shown exactly as found, attributed by name, dated to when it was read.
Hacker News
This handle was named once in a Hacker News comment or story, via the public Algolia search API. HN comment and story text has no confirmed reuse licence, so nothing quoted from either is reproduced here — only that a mention exists, when, and by whom, with a link to read it at the source.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“Embedded Systems” (@embedded_system), 13,974 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/embedded_system.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.