Ido Roseman's Blog

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  • איך עובדות רשתות Meshtastic ו-MeshCore

    דמיינו שאתם יוצאים לטיול בהרים, מפליגים בים, נמצאים באזור מבודד או אפילו חיים בעיר שבה התקשורת הסלולרית נפלה ואינה זמינה. איך אפשר לשלוח הודעה לחבר שנמצא כמה קילומטרים מכם, בלי אינטרנט, בלי Wi-Fi ובלי לשלם לחברת סלולר? זאת בדיוק הבעיה שרשתות LoRa Mesh מנסות לפתור.

    בשנים האחרונות צוברות פופולריות שתי פלטפורמות קוד פתוח שמאפשרות להקים רשתות תקשורת עצמאיות באמצעות משדרי רדיו זעירים וזולים יחסית: Meshtastic ו-MeshCore.

    העניין הגובר בפרויקטים האלה אינו מקרי. השילוב בין רכיבי רדיו זולים, בקרי מיקרו בעלי צריכת חשמל נמוכה, תוכנת קוד פתוח וקהילות משתמשים פעילות הפך את הקמתה של רשת תקשורת פרטית ועצמאית לפרויקט נגיש גם לחובבי אלקטרוניקה ולאנשים ללא ידע מוקדם בתקשורת רדיו.

    מעבר לשימושים של טיולים ותקשורת באזורים מרוחקים, יש כאן גם משהו שמדבר במיוחד לקהילת ה-Makers: אפשר לרכוש לוח פיתוח קטן, להתקין עליו קושחה מוכנה, לחבר אותו לטלפון, ולהיות חלק מרשת תקשורת שהמשתמשים עצמם בונים ומתחזקים.

    מה שבעיני חובבי האלקטרוניקה הוא פרויקט טכנולוגי מרתק, בעיני קהילת ה-Preppers הוא חלק מתשתית תקשורת חלופית  כחלק מההיערכות למצבי חירום, אסונות טבע או תרחישים שבהם תשתיות התקשורת הרגילות אינן זמינות. עבורם, היכולת להקים רשת תקשורת עצמאית, שאינה תלויה בחשמל מרכזי, באינטרנט או ברשת סלולרית.

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  • Bringing AI to the LoRa Mesh: Building a Smarter MeshCore Bot with Ollama

    I’ve been experimenting with LoRa mesh networks, AI agents, and running local LLMs with Ollama. At some point, it occurred to me: why not bring them together?

    Both Meshtastic and MeshCore already have chatbot projects that let you interact with a bot over the radio. They’re useful, but many rely on fairly rigid commands. You need to know the right syntax, remember what the bot can do, and phrase your requests in a way it understands.

    I wanted something more natural. What if you could simply ask your mesh network a question, and let an AI figure out what information it needs?

    That idea led to mesh-ai-bot, a project that combines a local Ollama server with a LoRa mesh network, giving an AI assistant access to actual network information.

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  • Designing a Battery-Powered IoT Device: The Fundamentals That Determine Battery Life

    Battery-powered IoT products can look deceptively simple. Choose a wireless microcontroller, connect a battery, add a USB-C port if you want the device to be rechargeable, and the job appears to be done. Easy.

    In practice, reliable battery-powered wireless design is a system-level exercise. The processor, radio, sensors, voltage regulator, user interface, communication protocol, firmware behavior, battery chemistry, and even the enclosure can all affect operating life.

    Whether the product uses the large battery in a vehicle or the tiny rechargeable batteries in a pair of earbuds, conserving energy is almost always important. In this article, I will explain the fundamental principles that guide the design of an efficient battery-powered wireless device.

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  • If Nobody Uses It, Is It Really the User’s Fault?

    I recently received an email from an association I belong to. The message was, essentially: We spent a lot of money building a great new website, invested hundreds or thousands of volunteer hours, and yet many members barely use it. Please go in and use it.

    It struck me as an interesting contrast with how we usually think about products and marketing in the business world.

    Imagine a company launching a new feature after spending a significant amount of money developing it. Six months later, hardly anyone uses it.

    Would the company send an email to its customers saying:

    “We invested a lot of money in this feature. Please start using it.”

    Probably not.

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  • The Cable Drawer Philosophy

    Every engineer has (at least one) drawer, box, or shelf that slowly becomes a resting place for cables, adapters, chargers, and connectors whose original purpose is half-remembered at best.

    Mine is no exception.

    And I fully understand how irrational it is.

    On paper, it makes no sense. Most of these things are obsolete, redundant, or easily replaceable. Any reasonable system would suggest throwing them away, standardizing, and buying new only when needed.

    I know all of that. I agree with all of that.

    And yet, I still keep them.

    Because somewhere in the back of my mind lives a quiet, slightly stubborn belief: maybe next month or in ten years, I’ll need this exact thing again.

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  • Reviving a Dead AC Remote with Aluminum Foil and 10 Minutes of Work

    A few weeks ago, the power button on my air conditioner remote started acting up.

    At first it needed a harder press. Then a firmer press. Eventually I found myself jabbing at it repeatedly like I was trying to negotiate with the remote rather than operate it.

    The rest of the buttons worked perfectly, so throwing away the remote felt wasteful. Besides, as an engineer, opening things up is usually more satisfying than replacing them.

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  • Ask Your Store Anything: Building a Real-Time AI Interface

    A few days ago, a friend showed me how he uses Claude AI to generate reports about his online store. Some of the insights were straightforward, things you could easily get from a pivot table, like which color or size sells the most. Others were more involved, like figuring out how many orders come from coastal areas. Since he sells fishing gear, that kind of geographic insight could directly influence where to focus marketing efforts.

    The real bottleneck in his workflow wasn’t the analysis, it was the setup. Every time, he had to log into the store’s back office, export an Excel file, and then upload it into Claude. It worked, but it was clunky and repetitive. So I offered to help automate it.

    Enter MCP Servers

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  • Turning a Wiring Mistake Into a Tool

    I was building a small gadget: a blinking light activated by a magnet hidden inside a princess wand.

    I sketched out a simple NE555 timer circuit and verified the design on a breadboard. Everything worked perfectly. Since I only needed a few units, fabricating a PCB felt like overkill—too expensive and too slow to ship.

    So I went old-school. I grabbed pen and paper and translated the design to fit a stripboard layout. Then I soldered the handful of components, connected the batteries… and nothing. It didn’t work.

    Somewhere along the way, I made a mistake.

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  • How AI Helped Me Send Pictures Through a Network That Wasn’t Meant For It

    Many years ago, I was sending high altitude balloons to the sky with cameras attached. I wanted them to broadcast these images live to the ground. The solution I used was analog SSTV which ham with good antennas could receive. I also experimented with digital images over APRS. The idea was to decentralize the reception with numerous stations already operating and bridged to the internet.

    In the past year there is a boom of local hams using Meshtastic, which is based on long range lora communication and packet relaying. I wondered if I could revisit this project using the new technology.

    TL;DR it’s not that easy

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  • Measure Twice, Cut Once: The New G-code Tool for Laser Makers

    Whether you are a seasoned maker or just starting out with laser cutting, there is a universal moment of tension: hitting “Start” on a job and hoping the laser follows the path you actually intended.

    One wrong setting or a miscalculated offset can lead to wasted material or, worse, a ruined project. To solve this, I’ve been working on LaserView, a dedicated web-based tool designed to give you total peace of mind before the laser ever touches the workpiece.

    What is LaserView?

    LaserView is a lightweight, fast, and intuitive visualizer for G-code files specifically prepared for laser cutters. Instead of sending your files blindly to the machine, you can drop them into LaserView to verify the geometry, check the paths, and ensure everything is exactly where it should be.

    Why Use a G-code Previewer?

    Most CAM software provides a preview, but seeing the raw G-code in a neutral environment is a critical “sanity check.” LaserView helps you:

    • Catch Errors Early: Spot disconnected lines, incorrect scaling, or paths that extend outside your machine’s work area.
    • Verify Power & Speed Commands: Ensure your G-code commands are being interpreted correctly by the visualizer.
    • Save Material: By catching a mistake in the browser, you save the wood, acrylic, or leather that would have been wasted on a bad run.
    • No Installation Required: Because it runs in the browser, you can check your files from any computer in the workshop without installing heavy software.

    Open Source and Accessible

    I believe in the power of the maker community, which is why LaserView is open source. Whether you want to use it as-is or dive into the code to see how it parses G-code, the project is available for everyone.

    How to Get Started

    Using the app is simple. Just export your G-code from your preferred design tool (like LightBurn, Inkscape, or Fusion 360), and load it into the LaserView interface. You’ll get an immediate visual representation of the laser’s path, allowing you to “measure twice and cut once”—digitally.

    Happy making!