标签：#IoT

Even though networking fundamentals are often taught at the early stages of a tech career, their relevance becomes far more important when you begin working with distributed IoT and edge-driven architectures. Concepts like subnetting, routing, NAT, DNS, firewalls, and VPNs evolve from simple textbook ideas into core architectural tools that determine how devices communicate, how secure the system remains, and how reliably data moves between the edge and the cloud. This refresher looks at these fundamentals from the perspective of someone building and supporting real IoT and edge environments. The goal is not to re-teach the basics, but to reconnect them with the realities of large-scale, low-power, and cloud-connected systems. 1. Subnetting as the Backbone of IoT Network Segmentation Subnetting plays a much bigger role in IoT and edge-driven environments than most people realize. In traditional networking, subnets help organize traffic and reduce broadcast noise. In IoT, they become a core part of the system architecture. When you’re dealing with sensors, gateways, and edge compute nodes running side by side, the network must be segmented in a way that keeps each function secure and predictable. A typical LoRaWAN setup shows this clearly. The gateway LAN, the packet-forwarder network, and the edge analytics node usually sit in different subnets. This separation allows you to apply strict ACLs around what each component can communicate with, especially because IoT devices often have limited security controls of their own. Subnetting also helps manage traffic flow, ensuring that noisy sensor broadcasts don’t interfere with time-sensitive edge workloads. Beyond security, good subnet design improves fault isolation. If a node misbehaves, the impact is contained within its segment. This structure also supports multi-tenant IoT deployments, where different applications or departments share the same physical infrastructure without touching each other’s data paths. In short

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The ring maker says that its business has shown significant revenue growth over the past year.

Ultrahuman is targeting a $200 million annual revenue run rate by January 2027 as it builds a new Qualcomm-powered smart ring.

The Builders Stage is returning to TechCrunch Disrupt, bringing together founders, startup operators, and investors for practical conversations on what it takes to build and scale.

Vijay Pande — who left a16z's roughly $4 billion biotech practice last year to start the much smaller, AI-native VZVC — talks about why biology is finally shifting from a "discovery" science to an "engineering" one, why clinical trials are still brutally expensive, and why he thinks open, shared datasets (not walled-off ones) are what will actually let AI transform medicine.

I knew I’d officially become a ‘longevity influencer’ this month when a company called Generation Lab reached out to offer me the chance to write about—and even receive—their new rejuvenation treatment, an injectable combination of two existing drugs which they call 1 Generation. This wasn’t just any antiaging treatment, either. A company fact sheet says that…

Hoomanely has developed a smart bowl to measure and record dogs' feeding data, then tells owners if behaviors change.

ESP32 Energy Metering with HLW8032, BL0942, and ESPHome ESP32 energy metering with HLW8032, BL0942, and ESPHome is not just about reading voltage, current, power, and energy. This article explains how to design the UART boundary, reporting cadence, calibration, entity model, and diagnostics as one stable data path. Many ESP32 energy metering projects start well. You connect an HLW8032 or BL0942 module, enable the matching ESPHome component, and Home Assistant quickly shows voltage, current, power, and energy. But reading values is not the same as building an energy metering node that can run reliably over time. The core conclusion is this: the hard part of ESP32 energy metering is not whether HLW8032 or BL0942 can be read. The hard part is designing the metering chip, UART, Wi-Fi behavior, ESPHome entities, calibration, and diagnostics as one stable data path. If the project focuses only on sensor YAML, it can later fail on transient loads, serial conflicts, unstable sampling, Wi-Fi reconnects, Home Assistant database growth, and calibration drift. In this article, an ESP32 energy metering node means an edge device where ESP32 reads voltage, current, power, and energy from a metering chip such as HLW8032 or BL0942, then exposes those values through ESPHome to Home Assistant or another upper-layer platform. It is suitable for device energy monitoring, trend observation, and low-risk operational diagnostics. It should not be treated as a billing-grade meter or an electrical protection device. If the goal is to monitor the energy behavior of one appliance, one small circuit, or one commercial device inside Home Assistant, ESP32 + ESPHome + HLW8032/BL0942 is a fast and low-cost path. If the goal is billing, electrical protection, high-accuracy compliance measurement, or safety interlocking, use certified meters, protection devices, or industrial acquisition hardware instead of stretching an ESPHome node beyond its boundary. 1. Why energy metering is more fragile than or

A fixed-schedule solar baseline drifts out of sync with the sun throughout the year. In Phoenix the sun is up for 13 hours 10 minutes in late August and 10 hours 2 minutes at the December solstice. A flat daily kWh target flags that entire winter as a fault, then stays quiet on the July afternoon when one string dies at 2pm under full sun. The fix is to anchor the baseline to the actual sun instead of the clock, and most of what you need for that does not require an irradiance forecast. One thing before any code: sun geometry tells you when a system should be producing and when it should peak. It does not tell you how much light actually reached the panels. That is irradiance, and cloud cover swamps it. If you want modeled output in kWh, reach for Forecast.Solar or Solcast, which fold in weather and your array's tilt and azimuth. What follows is the free, dependency-light layer underneath that: the daylight window, the solar-noon peak, and the day-length trend. TL;DR Sun geometry (sunrise, sunset, solar noon, day length) catches a specific class of solar underperformance with no irradiance data. Gate alerts to the real daylight window so your monitor stops crying "underperformance" before sunrise. Track the daily production peak relative to solar noon. A persistent shift across comparable days can reveal shading, orientation, or system changes that a total-kWh check misses. Normalize a flat kWh target by day length so winter stops tripping false alarms. First-order fix, not a physics model. One call to an astronomy endpoint returns all of it. Code below in curl, Python, and Node. For real production forecasting, use an irradiance API. Sun times are the sanity layer, not the forecaster. Sun times will not predict your kWh, but they eliminate common timing-based false alarms and can surface useful production-shape anomalies early. Pull sunrise, sunset, solar noon, and day length once a day, gate your alerts to daylight, watch the peak, and scale the target for season.

The company won't say if medical devices are affected or if any customer data was exfiltrated.

Counting the creatures in the world around us is critical for a raft of conservation efforts. It helps scientists gauge biodiversity, track migration, and spot invasive species. That census-taking, though, often requires humans to tabulate what they see, trap, or otherwise sense—a potentially laborious, costly process that can still leave gaps. But developments over the…

ESP32 + Python: From Microcontroller to IoT Artcal 0: Introduction When it comes to transferring data from one place to another, things can sometimes become tricky, especially when communication happens between the hardware and software levels. In this article series, I would love to share the experience and knowledge I’ve gathered while working with ESP32 and Python. We’ll explore how these two technologies can work together, starting from the basics and gradually moving towards more interesting and practical projects. If you have any questions, suggestions, or ideas along the way, feel free to share them in the comments section below. I’d love to hear from you and discuss them with the community. So, without further ado, let’s begin! 🚀 What is ESP32? Think about Esp32 as a microcontroller with Internet facilities, consisting WiFi, Bluetooth and a own wireless data transfer protocol called ESP-NOW between ESP32 chips. Nowdays, the developers have made development boards integrading these chips for the easy use. ESP32 is a family of microcontrollers developed by Espresiff. This can read sensor inputs, process data, contol devices and specially connect to the internet. This is like Arduino but better, faster and smaller. With these information that we have, we can speak about this board as, "A powerful microcontroller that can interact with electronic components and communicate with other devices through Wi-Fi, Bluetooth, and other communication methods." Python??? We use different languages to tell the same thing but in different ways. We use programming languages to tell the computer the same thing but in different approches. Some languages can be hard to learn and some are easy. Some are well developed and some are not. Python programming language was created back in 1980s by Guido Van Rossum, with the development begining around 1989. It was publicly released in Feb, 1991. 🐍 1989 — Guido van Rossum developing Python. 🐍 1991 — The first public release. 🐍 2000 — Py

Michael Polansky — better known publicly as Lady Gaga's partner and a former top deputy to Sean Parker — has quietly spent years building an AI-driven startup that keeps living human skin tissue alive for weeks outside the body to discover new skincare compounds, and is only now going public about it.

Architecture is not a fixed choice made once; fitness is a moving target driven by changing regulations, tech, and markets. Even a sound design can silently stop fitting over time without bad calls. Spanning seven articles on context stores, gateways, and topologies, this collection treats architecture as an evolving sociotechnical craft where teams deliberately shape friction, fitness, and flow. By InfoQ

When the biotech company Insilico Medicine used its computer models to propose a promising drug for pulmonary fibrosis, it enthusiastically claimed in a press release that the molecule had been “discovered by” its generative AI platform. Insilico leads a pack of companies using AI to rapidly come up with drug ideas humans might never think…

An effort to transform the world of sports through steroid use doesn't exactly seem to be bearing financial fruit.

It's the data, stupid.

The scanning and bloodwork health startup founded by Spotify's founder will officially launch in New York in about a month.

Controller Area Network (CAN) is one of those technologies that quietly powers a huge number of embedded systems. It is commonly found in cars, EVs, industrial controllers, robotics, and other distributed systems where multiple devices need to exchange data reliably over a shared bus. For development and debugging, it is useful to connect that CAN network to a computer. The problem is that a standard computer communicates through USB, while CAN uses a dedicated differential bus. A USB-to-CAN interface solves this problem by translating between the two. In this project, we will explore the DSD TECH SH-C30L USB-to-CAN adapter , learn how its different firmware modes work, connect it to a PC, and then use an Arduino UNO with an MCP2515 CAN module to create a simple bidirectional CAN communication setup. The goal is not just to make the hardware work, but also to understand what happens between the Arduino, CAN bus, USB adapter, and computer. SH-C30L USB-to-CAN Adapter Overview The SH-C30L is a compact USB-to-CAN interface designed to connect a computer directly to a CAN network. It is based on an STM32F072C8T6 microcontroller, which contains an integrated CAN controller. This allows the adapter to handle CAN protocol processing without requiring a separate external CAN controller. The microcontroller communicates with the computer through USB, while a dedicated CAN transceiver handles the physical CAN interface. The transceiver converts the controller's logic-level signals into the differential CAN_H and CAN_L signals used on a CAN network. One of the interesting aspects of the SH-C30L is its firmware flexibility. The adapter can work with Candlelight firmware , which allows it to operate with Linux SocketCAN and compatible CAN applications, or with SLCAN firmware , where it behaves more like a serial CAN interface. This makes the same hardware useful with different operating systems and software environments. The adapter supports both CAN 2.0A and CAN 2.0B frames, wit