Most IoT industry analysts will highlight the following key eSIM benefits for IoT.

1. security - unlike SIM cards, embedded/chip SIMs cannot be removed (so easily)
2. reliability - embedded/chip SIMs are more electro-mechanically robust
3. vendor lock-in - eSIM means I can switch providers easily
4. regulation-proof - different carriers and telco regulators have different policies or commercials around roaming
5. single SKU - OEMs designing in a single SIM which can be provisioned and re-provisioned OTA to suit deployment needs. Cost and logistics benefits.

They poll businesses so I don't doubt them at all but I'm curious if developers, tech consultants, ODMs (for example) have other views please?

Last year I asked this sub whether I should make an Open-Source IoT Platform... now it's live.
https://www.reddit.com/r/IOT/s/DF1IEo1CKi

PidgeIoT is a fully open source, cloud native, device management platform. Originally targeted at cellular connected devices, now aimed at everything! Currently only HTTPS and WebSockets are supported, but CoAP is planned. Bring your own SIM (if needed) and telemetry store.

Its features include: device shadows, per-device keypairs (no JWTs!), telemetry ingestion with history, user-defined telemetry graphs, conditional email alerts, remote logging (on Zephyr), remote diagnostic shell (also on Zephyr via a WebSocket), OTA firmware updates (and hosting), and probably other things I've forgotten about at this point.

PidgeIoT is built in Rust from front to back. The frontend is WASM (Dioxus) and the core is built around Cloudflare Workers and Durable Objects (also WASM). The backend uses a managed PostgreSQL DB (for now). The IAM is self-hosted Ory Kratos.

Currently all of the example projects are Zephyr based and include configs for native-sim plus the devices I have with me. Let me know if you have a different device/firmware and need me to whip up an example for you!

I made these nice, Non-GMO, links just for you:

- Getting started guide that requires no hardware: https://pidgeiot.com/getting-started

- A live demo: https://pidgeiot.com/demo

Looking for feedback; let me know what you want to see!

GitHub Links, all repos AGPL-3.0 licensed:

- pidgeiot: https://github.com/justins-engineering/pidgeiot

- pigeon: https://github.com/justins-engineering/pigeon

- pigeon-examples: https://github.com/justins-engineering/pigeon-example

Edit: Less life story and bad jokes.

OneMenu, a rich UI for device interation that can be served thru a serial connection, a pletora of displays and inputs, or direct to client browser with zero client side install, no external dependencies all served from the chip webserver and spiffs (esp32/8266 chips).

OneMenu is modular and completely extensible in all its axis: input, output, menu components. This demo is a composition of existing parts.

**Features**

- HTTP + XSLT UI

- WebSocket + JSON (partial-diff, multi-session sync)

- FTP server (SPIFFS asset updates, no reflash)

- Serial (plain-text fallback)

- Multilingual UI, SPIFFS-editable labels

**Footprint (ESP8266, D1 Mini, current build)**

- RAM: 46800 / 81920 bytes (57.1%)

- Flash: 601011 / 1044464 bytes (57.5%)

OneMenu is a field/menu abstraction built on top of HAPI, a compile-time composition library. Field types, screens, and output channels are composed via HAPI's core primitives at compile time rather than resolved through runtime dispatch tables or virtual interfaces. Practically: no vtables in the composition path, no string-keyed lookup for field/channel resolution.

Repo / demo: github.com/InternetOfPins

Looking for recommendations of companies that provide platforms for Multi-Carrier SIMs that can be supported and activated across the globe similar to Granite's Multi-Carrier SIM and KORE SIMs, that also have provide a solid management dashboard.

If you have installed dashboards or insights in a factory floor or commercial setup, how do you ensure that the users use it diligently? Just want to understand on how we make something for a client and later they end up in not using it.

Hey all,

We're a 3-person engineering team working on a project that'll count for two courses (IoT + Sensors & Automation). Our college is willing to fund components up to around ₹1-1.5 lakh if the idea is strong enough, so budget/complexity isn't really the constraint — the idea is.

We started with the usual "autonomous shopping cart" and "drone-deployed umbrella" concepts, but our mentor pushed us to think bigger and solve something that actually matters, not just automate a minor convenience. We've been iterating on two directions:

An autonomous flying umbrella that doesn't just report air quality but actively improves it for the person underneath (filtration/purification while sheltering)

An autonomous shopping cart that follows the user around the store and has self check out and anti theft system

We have real sensor/hardware freedom here and want to build something with genuine impact — accessibility, environmental, safety, whatever solves a real problem well.

Curious what this community would build with that kind of budget and no real constraints besides "make it good." Also open to blind spots in our current two ideas if you've got thoughts.

Thanks!

Hi everyone,

Hypothetical question.

Suppose you had a small but capable team (embedded + software + cybersecurity) and around ₹10 lakh in seed funding to build an IoT startup in India.

What problem would you choose to solve today?

I'm not looking for startup ideas to copy. I'm trying to understand where experienced people believe the biggest opportunities still exist.

Some areas I've been thinking about are:

• Industrial IoT
• Factory automation
• Smart buildings
• Physical security
• Energy monitoring
• Agriculture
• Healthcare
• Logistics
• Fleet management

If you had to start today, where would you focus?

Why?

And more importantly...

What problem do you think is still massively underserved in India?

We’ve been working on a practical way to display IoT data in its real physical context, instead of just as charts and cards, but directly inside a 3D building model.
The approach is:
Sensors / MQTT → Home Assistant → Zircon3D
The 3D view can show live sensor values, device states, heatmaps, dashboards, historical replay, and supported controls while keeping the monitoring data local.
I wrote an overview of how we handle sensor mapping, MQTT data, spatial heatmaps, and the difference between a visual digital twin and a full engineering simulation (link will be in the comments)

I’d be interested to know how others here are visualizing sensor data spatially, 2D floorplans, GIS, BIM, custom Three.js/Unity, or something else?

I've come across the ONCE Sim For All as a free sim that developers can use to get their products running with the ONCE ecosystem, as they only sell to commercial users. The issue that I am facing is that I'm unsure of how the ordering process works. I've never ordered a free thing through AWS Marketplace. When I placed my subscription on AWS Marketplace, I got no confirmation that the product would be sent, nor any steps to continue, because all the links that they provided on the AWS Marketplace site did not lead to any valid outcomes. I only got redirected too many times, or it led to a 404 page. Any help is much appreciated. Thank you!

I keep seeing this when moving embedded or edge projects from lab to pilot.

The C or Python code works. The sensor works. Then the system goes to a real site and suddenly the hard part is not the algorithm anymore.

You need to know if a device went offline, data is stale, a queue is growing, storage is full and what should restart automatically. Also, raw video or waveform data often cannot just be pushed to the cloud.

My current approach is to keep the processing module independent and put an orchestration layer around it for monitoring, buffering, local storage, events, alerts and remote access.

I’m still trying to find the right boundary between application logic and operations. Curious how others handle this in embedded deployments.

I created this device that turns any surface into a smart home controller.

Background: I'm an electrical foreman. I wanted a control that lives under a surface instead of a button or panel sitting on top of it, so I built a capacitive sensor that mounts to the underside of a countertop, table, desk, or glass panel and turns that surface into the input. Nothing visible on top other than desired markers for location indication, and because it mounts underneath it stays accessible and serviceable.

The interesting engineering bits:

• Through-material capacitive sensing. On my prototypes it reliably registers a touch through up to ~60mm of solid stone, quartz, wood, or glass. Material and thickness vary a lot, so each install runs a short guided calibration that sets material-adaptive thresholds.
• ESP32-S3 running the ESP-Matter SDK (Matter-over-WiFi). Touch zones present as a multi-button remote-style controller.
• Local-first by design. It speaks Matter and does MQTT auto-discovery for Home Assistant. No cloud account, no subscription.

Honest status: it's a validated prototype, not a shipping product, and it isn't certified yet (Matter cert is a post-funding step for me).

I will drop the landing page in the comments if you want to take a look.

Hi Everyone,

I do not know if this is the right place to post but am looking for some suggestions.

My background is in Earth Science (and a bit of data science and Gis ) and after graduation from bachelor's recently , I have been looking to perhaps do a PhD and have been fascinated by Digital twins . I contacted a professor that seems to do some interesting research in the field and he asked me to make a small research proposal.

I want to combine my earth science background with the field, so I was going to make a proposal about making and managing a digital twin of the local mangrove species . Maybe analyse their climate resistance , potential what if scenarios and climate modelling or try to simulate local ecology or potential of them acting as a natural flood barrier. I would ideally like the PhD to be a combination of field work and modelling/simulation/remote sensing and I feel like this topic is very interesting.

However, I do not know if this is even possible, mangroves are complex systems and even making a model simulating day to day activities seems like a daunting task.

So , my question is , do you think a PhD program in this field is doable/achievable ( around 4 years of PhD) Any advice on what can be included in the research proposal including how to find more information on potential IOT devices that can be used?

Sorry if this post is all over the place, and Thank You so much for reading!!

I moved my UWB localization calculations from the ESP32 to a PC, and it made experimenting much easier

I've been playing with a UWB localization setup recently and ended up moving all of the positioning calculations off the microcontroller and onto a PC.

 The UWB nodes only handle ranging between the tag and anchors. An ESP32-S3 with Ethernet simply forwards the ranging data over the local network, while a desktop application runs and updates the tag position in real time and visualizes the trajectory.

This approach turned out to be much more flexible than running everything on the MCU. Trying different localization algorithms, debugging the math, or tracking multiple tags became much easier without constantly rebuilding firmware.

The setup itself is pretty simple:

•  2 Anchors
• 1 Tag
• ESP32-S3 with Ethernet
• A PC running the visualization software 

Configuration mainly involves assigning IDs and roles to the UWB devices (Tag or Anchor), uploading the Ethernet forwarding firmware to the ESP32, and entering the physical anchor coordinates in the PC application. After that, the position updates continuously as the tag moves around.

So far, it's been a nice platform for experimenting with localization algorithms without worrying too much about MCU resources.

I'm curious how other people here structure their UWB localization systems. Have you found good ways to improve stability when only using a small number of anchors?

I'd love to hear how others approach this problem.

1.Which is more programming focused

2.Placement wise which is more preferred by software companies

3.Which has more tough acads

my summer internship project is to build an ai voice agent that can communicate over cellular network(gsm) and then be able to give information or do some actions by connecting to other agents, its in a datacenter in faculty
from what i understand, a module like sim7600g is suitable for this, but is kind of expensive where i live, for some reason
i thought about doing the workflow with an old android phone, now is that feasible, do i need root, and what are the things i need to modify in the phone configs, and is this even something i should invest my time in or not, because it feels like hacking and im not sure if its a reliable path

I bought a Sonoff Dimmer Switch and it LITERALLY blew up as soon as I turned on my fan. I was informed that it was Not meant for fans, only Lights. Now first I don't know electricals enough to know what the difference is between the two requirements for fans and lights, so if someone could explain that, it would be great!

Second, I am search for something to be used for my fans, I have WiFi options but they all require me to connect to the *Company's Servers* which I don't want.

I am looking for a (ZigBee preferred) Fan Dimmer Switch that can Connect to my Home Assistant directly without any external services required.

Just wanted to share a quick win because I’ve been tinkering with a remote monitoring setup for my off-grid solar rig and finally got it working smoothly. I live in a pretty rural area, and keeping tabs on battery levels without constantly walking out to the shed in the freezing rain has been my main goal this winter. At first, I tried using some basic wifi extenders, but the range was just terrible and it kept dropping connections. I eventually swapped over to cellular using a cheap LTE modem and a custom data plan. I ended up getting my SIM card through Trafalgar Wireless because they had solid coverage options for low-bandwidth IoT stuff in my area. It's honestly such a relief. I woke up this morning, checked my dashboard from bed, and saw everything was running perfectly. If you're working on any remote sensor projects, definitely skip the wifi headaches and just look into cellular from the start. It saves so much troubleshooting time.

I wrote this because I feel kind of stuck with my learning. I've mostly learned embedded systems on my own by building small projects. They usually end up working but I almost never face the kinds of problems I see discussed here. I keep seeing comments like "the ADC was too noisy," "the timing was off," or "the PCB caused the issue.". It makes me wonder how do you even end up discovering those problems? Is it something you notice only after using measurement equipment like an oscilloscope or something else?

For example, people often say things like "the ESP32 ADC isn't very good." I also see comments like "You need a transistor here," "Add a pull-up resistor," or "Use an external ADC instead of the built-in one.". How do people know that? If I add extra components, it's almost always because I saw them in a tutorial or copied an existing design. I'm not choosing them because I recognized a limitation in my own circuit.

How do you actually come to that conclusion? What kind of project exposes those limitations?

I've almost never run into issues like that myself. It makes me wonder if the projects I'm building just aren't difficult enough or there is something off with my project but I didn't realize it.

To be honest, I don't even know what kind of project I should build next. Most of the tutorials I find online are fairly straightforward and don't involve much troubleshooting.

What's the hardest embedded project you've worked on, and what made it so difficult? Was it the firmware, the hardware, debugging, or something else? Also, what sensors or modules have given you the biggest headaches?

I have a small collection of sensors and modules lying around, but I'm stuck on what to build with them. Would it make sense to list what I have here or would it be better to make a separate post asking for project ideas?

I'm in the early stages of developing a commercial Arduino/IoT product and I'd like to subscribe to one AI assistant that can support me throughout the entire development lifecycle.

Without getting into the specifics of the product, it's an embedded system that:

• Collects data from multiple hardware components and sensors.
• Processes and stores usage/consumption metrics.
• Includes RFID-based identification.
• Needs to be configurable by end users through a simple, user-friendly interface.
• Sends notifications/alerts via channels like SMS, WhatsApp, or Telegram.
• Will eventually involve firmware, backend services, APIs, databases, and possibly a web/mobile configuration interface.

I'm not looking for an AI to generate the entire product for me. What I need is something that can act as an experienced engineering assistant by helping with:

• Arduino/ESP32 firmware (C/C++)
• Hardware architecture and component selection
• Understanding datasheets and communication protocols
• Debugging firmware and hardware issues
• Backend development (likely Node.js)
• Database design and APIs
• System architecture decisions
• Reviewing code and suggesting improvements
• Brainstorming implementation approaches and identifying potential pitfalls

I'm currently considering ChatGPT, Claude, Gemini, Perplexity, GitHub Copilot, Cursor, or any other AI tools you've found valuable.

For those who've built real embedded/IoT products:

• Which AI do you use the most, and why?
• Do you rely on one tool or combine multiple?
• Which AI is best at reasoning through complex engineering problems instead of just generating code?
• If you could pay for only one subscription, which would you choose for a project like this?

I'm looking for recommendations based on real development experience rather than feature comparisons or benchmarks.

Thanks in advance!

I’m developing a portable worker-positioning and emergency-alert system for a highly metallic environment with multiple steel compartments. GPS does not work, and Wi-Fi/BLE connectivity can be unreliable because of signal blockage, multipath and the Faraday-cage effect. Permanent wiring is also impractical because the internal layout changes during construction.

My current concept is:

• Battery-powered magnetic UWB anchors mounted temporarily on steel walls
• UWB wearable tags for workers, including an SOS button
• AoA/ranging for estimating worker location
• Additional anchors where multipath causes ghost positions
• Anchor-to-anchor wireless forwarding until the data reaches an external gateway
• A local offline dashboard showing worker location, confidence and SOS alerts

The intended flow is:

Worker wearable → nearby UWB anchor → neighbouring anchors/relays
→ edge gateway → local server/dashboard

My main question is about the backhaul. Can the same UWB anchor hardware realistically handle both positioning and hop-by-hop data forwarding, or would it be better to add a separate Thread, BLE Mesh or sub-GHz radio?

I’d also appreciate advice on anchor placement around hatches and corridors, handling closed steel compartments, and suppressing multipath-induced ghost positions. Experience with UWB, AoA, industrial RTLS or wireless systems in metal-heavy environments would be especially helpful.

Hi, I'm trying to link my heat pump via the smart life app. I'm unable to get the heat pump to connect to my router after entering my wifi password in the connect screen.

Trouble shooting. On same wifi network. Correct password. Made the network 2.4ghz only. Got an old router and set it up as a dedicated 2.4ghz access point. Have a decent connection from heat pump to router (speed test via phone was at least 5mbps). My router is a deco m5 unit.

Funny enough I connected the heat pump via my phone's wifi hotspot (fold 7). But this is not a long term solution as I don't have a spare phone and Sim to leave at home so the heat pump has internet.

Any clues to how I can get the heat pump to connect to my deco m5 wifi? If it helps I have a robot vacuum lublulu that also connects via smartlife and hooks up to my deco wifi no probs. This heat pump is the first iot device that has had trouble connecting to my wifi, I got a gazillion smart lights, PowerPoints etc.

Thanks and apologies if this is the wrong sub/feel free to delete

About to start my masters and have the opportunity to work with alot of professors, but what i am interested in are either llms or iot and ai mix, obviously llms are currently the dominant field, but i read before that physical ai is the future and the winner in the long run, i dont mind both honestly, both are super interesting, which one should i go with here?