Збирач потоків

A desktop satellite never leaves the desk, but it behaves as if it were about to launch. The prototype collects and logs environmental and motion data, exactly as it would on a suborbital flight. The result is a compact electronic platform that shows how far a sensing system can be shrunk without losing any functions.

The heart of the system is an ESP32-C3 Mini, which acts as the main controller. Two sensors are entrusted to it: a BME680 for temperature, humidity, atmospheric pressure and gas resistance, and a BMI323 that adds a 3-axis accelerometer and gyroscope. The sensors talk to the ESP32 over an I²C interface, a choice that keeps the number of wires low and simplifies the wiring.

Record-breaking weight and size

The numbers tell the story of the project’s philosophy well. The prototype weighs 21 grams, below the initial target of 30 grams. Its dimensions are 28 × 28 × 33 mm, a volume that fits in the palm of a hand. To reach this result, connectors, PCB material, wiring and mechanical structure were all reduced, while the sensing and computing functions were kept intact.

Every gram saved counts, because in a future real launch weight translates directly into cost and complexity. Miniaturisation is not just an aesthetic matter: it is proof that a complete telemetry system can fit in a minimal volume.

Dashboard and flight data management

A software dashboard monitors and stores the measurements collected by the sensors. The system organises the recorded flight data into files that can be viewed, downloaded or deleted. This structure makes it possible to analyse the readings after a test session, without having to keep the satellite connected to a computer during acquisition.

The workflow is simple: start the collection, the satellite logs the data, then download the files for analysis. Having a dashboard also makes the system suitable for anyone who wants to experiment with long acquisitions or with changing conditions.

• ESP32-C3 Mini as the main controller
• BME680 for temperature, humidity, pressure and gas
• BMI323 for acceleration and rotational motion
• I²C bus to connect the sensors to the controller
• Software dashboard to monitor and archive the data

The project shows how an electronics platform inspired by satellites can be built from easily available components. Those who want to dig deeper can look at the maker’s site, where the details of the system are available. The development board used is a compact solution for IoT projects, suitable for anyone who wants to replicate the prototype or start from a similar base.

The desktop satellite is not meant for space, but to prepare the ground for those who will go there. The combination of environmental and inertial sensors covers the basic needs of a flight experiment: pressure, temperature, humidity, gas, acceleration and rotation. At 21 grams, the system leaves room for larger payloads or bigger batteries in a possible future launch.

Source: https://circuitdigest.com/news/barely-21-grams-this-satellite-prototype-tracks-the-environment

Related products

• Mini ESP32-C3 module

The post A Desktop Satellite with the ESP32-C3: 21 Grams of Telemetry appeared first on Open Electronics.

A buzzer module emits a sound to signal a danger or the end of a set time. It also serves to confirm a command. There are two types: passive, such as the KY-006 and Ks0019, and active, such as the KY-012 and Ks0018. AdriRobot tested them with an Arduino UNO, with a Multi Test Shield and with the micro:bit board.

Active and passive buzzer module: the difference

The buzzer is an audio signalling device. It can be mechanical, electromechanical or piezoelectric. In the active module there is an internal oscillator: you just power it and the sound starts. The passive module has none, so the control circuit must supply it with a square wave between 2 and 5 kHz.

The piezoelectric buzzer is based on a ceramic disc with a metallic layer. It is robust and cheap. That is why it is used for narrow-band alarm signals, for example in household appliances and in medical technology. Electromagnetic buzzers, on the other hand, have a metal diaphragm set vibrating by an electromagnetic circuit, with the electronics already integrated.

The four modules compared

The KY-006 and KY-012 have the same circuit, made up of a connector and the buzzer. Only the type of buzzer changes, passive in the first and active in the second. Of the connector only GND and signal are used, so the current comes from the Arduino pin. Each module also measures 15 × 19 × 9 mm and weighs 2.4 g.

The Keyestudio Ks0018 (active) and Ks0019 (passive) modules are more elaborate. An NPN S8050 transistor acts as a switch between the control pin and the buzzer. There are two resistors: one on the base and one in series with the power supply. This way the control pin only supplies the current for the transistor. The connector therefore has three connections: GND, signal and 3.3 or 5 V power. Finally, these modules measure 30 × 20 × 10 mm and weigh 3 g.

Testing with Arduino: square wave and tone()

To test a passive module you need an Arduino UNO, some Dupont jumpers and the KY-006 or the Ks0019. In the first sketch digital pin 3 goes from high to low with short pauses. This way the square wave is built by hand. Alternatively you use tone(pin, frequency, duration), which generates a square wave with a 50% duty cycle.

The command also produces only one tone at a time. If another pin is already playing, the call has no effect, while on the same pin it changes the frequency. To stop the sound you use noTone(pin). In AdriRobot’s example the buzzer sounds at 500 Hz and at 1000 Hz for one second each. Then it stays silent for five seconds.

The active module is simpler. With the KY-012 or Ks0018 a signal pin at high level makes the buzzer sound. At low level it stops it.

Multi Test Shield and micro:bit

The Multi Test Shield is a shield built by AdriRobot, compatible with the Arduino UNO R3. It is used to test the sensors of the 37-in-1 kit. The KY-012 is inserted on the JP2 connector. This way the sketch alternates sound and silence and shows the various phases on a small OLED display.

The Ks0018 and Ks0019 modules can also be connected to a micro:bit board. You need the Keyestudio Micro:bit Sensor V2 shield and three female-female Dupont cables. The program is also written with the MakeCode block editor and saved directly onto the board.

Where to find the modules

The individual modules are in the catalogue: the passive buzzer module KY-006 and the active buzzer module KY-012. Both are also part of the box of 37 sensors for Arduino, Raspberry Pi and robotics.

Source: the original article by AdriRobot includes the complete sketches, the MakeCode programs and other examples of buzzer use in projects.

Related products

• Passive Buzzer Module, 3.5V to 5.5V Operating Voltage
• Active Buzzer Module with 3.5V to 5.5V Operating Voltage
• Box of 37 sensors for Arduino/Raspberry Pi/robotics

The post Active and passive buzzer modules: KY-006 and KY-012 with Arduino appeared first on Open Electronics.

Intelligent power and sensing technology firm onsemi of Scottsdale, AZ, USA says that its latest EliteSiC silicon carbide (SiC) hybrid power module technology has been adopted by renewable energy technology firm Sungrow for its PowerTitan 3.0 energy storage platform. The integration enables improved efficiency and enhanced system performance for utility-scale battery energy storage systems (BESS)...

Стипендіатки Верховної Ради України 2026 року з КПІ Інформація КП чт, 10/15/2026 - 12:00

Microchip Technology Inc of Chandler, AZ, USA has launched the POL-05-20S-T, a radiation-tolerant point-of-load (POL) converter, designed to address the demanding power requirements of space processing applications. The new device uses gallium nitride (GaN) power devices to deliver up to 20A of output current with high efficiency and power density...

Perfect Paul ][ is a drop-in DECtalk emulator card for the Apple ][, designed by Michael Wessel. It brings the high-level speech synthesis of the DECtalk, historically expensive and out of reach, to an ordinary 8-bit computer. Operation is straightforward: you write DECtalk commands to the card’s memory addresses using POKE, and the Apple ][ starts talking. No software rewrite is needed, because the card presents itself to the bus as just another peripheral.

The heart of the project is a Raspberry Pi Zero based on the RP2040. Around it sit an I2S DAC, an amplifier, a speaker and the bus interface logic. So the complete chain runs from the command written to memory all the way to the sound coming out of the speaker, with no external stages. Michael Wessel’s repository collects the project code, and it is the starting point for understanding how DECtalk commands are translated into audio.

The Apple ][ bus and the interface logic

The card presents itself at a set of memory addresses on the Apple ][. This is the key point of the project: interfacing happens by writing DECtalk commands to those addresses using POKE. Existing software therefore needs to know nothing about the card; it just has to address the commands in the right place. The bus interface logic acts as a bridge between the 8-bit world of the computer and the RP2040, which receives the commands and turns them into speech synthesis.

• Raspberry Pi Zero based on RP2040, the core that generates the synthesis
• I2S DAC to convert the digital signal to analog
• Amplifier to bring the signal up to speaker level
• Speaker for the final audio output
• Bus interface logic toward the Apple ][ memory addresses

The flow is linear. The Apple ][ writes a DECtalk command to an address on the card. The interface logic delivers it to the RP2040. The Raspberry Pi Zero processes the command and produces the digital audio stream. The I2S DAC converts it, the amplifier raises its level and the speaker makes it audible. What’s more, the same chain can be adapted: according to the author, it would be easy to port the card to other 8-bit machines as well, changing only the bus interface part.

What you need to rebuild the card

Anyone wanting to try the build starts from a short list. At the centre is the module with the RP2040, then the audio board with I2S DAC and amplifier, then the speaker and the interface logic toward the Apple ][ bus. For the audio output you can use a 2 W, 8 ohm speaker with a diameter of 66 mm, which covers the 400-4,500 Hz band with 86 dB of sensitivity: more than enough figures for synthetic voice. The delicate part remains the bus interface, because compatibility with the computer depends on it.

The project does not publish power consumption or cost figures, so none are invented here. What matters is the choice of a software emulator instead of the original DECtalk hardware: this way, high-level speech synthesis becomes accessible to anyone with an Apple ][ at home. In particular, the fact that commands go through memory addresses means that even programs written decades ago can find their voice again, without patches.

For those who want to see the card in action, the author has published a demonstration video. Those who prefer to get their hands on the code will find the material to start replicating or adapting the project in Michael Wessel’s repository. The path to porting it to other 8-bit machines, after all, goes right through there: change the interface logic and keep the audio chain intact.

Source: https://github.com/lambdamikel/perfect-paul-ii

The post Perfect Paul ][: Michael Wessel’s DECtalk Emulator for the Apple ][ appeared first on Open Electronics.

The rapid expansion of AI and its multifaceted applications have opened myriad avenues, while posing critical challenges that must be addressed in real time. Anwesh Koley of ELE Times, caught up with Sanjay Wadhwa, Chairman & Managing Director, NASH Group of Companies, to decode the latest technological advancements and India’s role in this growth story.

ELE Times: Share your thoughts on the increasing role of Smart Vision technologies in quality inspection, predictive maintenance, and operational efficiency.

Sanjay Wadhwa: Smart Vision is becoming central to the next phase of industrial transformation because it addresses four priorities that every manufacturer is focused on today: consistency, repeatability, speed, and traceability. As production environments become more complex and volumes rise, manual inspection alone cannot deliver the level of repeatability and real-time assurance that modern manufacturing demands.

AI-enabled vision systems bring intelligence directly into the production process. They can analyse visual data in real time, identify defects, recognise deviations, and support faster corrective action. More importantly, they provide a highly repeatable method of inspection, reducing the dependence on individual inspector judgement, fatigue, or differences in interpretation. This creates a much more consistent quality standard across shifts, operators, and production lines.

At NASH, we see Smart Vision not simply as an inspection tool, but as a broader capability across quality, security, monitoring and process intelligence. The ability to capture and analyse the same parameters consistently over time also creates a valuable digital record that can be used for traceability and continuous improvement.

Its value also extends beyond defect detection. When visual data is integrated with machine, process, and enterprise systems, it helps leadership identify weak points, understand recurring issues, and improve decision-making. In predictive maintenance, continuous monitoring can reveal early signs of deterioration, enabling teams to intervene before failures affect productivity.

The larger opportunity is to convert visual information into repeatable, reliable, and actionable intelligence. That is where Smart Vision will play a defining role – not only in improving operational efficiency but also in strengthening quality systems enabling predictive intervention, reducing process variation and ultimately building more efficient and resilient manufacturing operations.

ELE Times: How are Indian engineering and manufacturing companies building globally competitive Industry 4.0 solutions?

SW: Indian engineering and manufacturing companies are steadily moving from being execution-led partners to becoming creators of globally relevant industrial technology. This shift is being driven by strong engineering talent, deeper manufacturing experience, and growing collaboration with global technology ecosystems. The real transition is from “Make in India” to “Engineer in India, Innovate in India & Scale for the World.”

At NASH, our focus has been to build capability across the full product lifecycle — from design and engineering to embedded systems, Artificial Intelligence of Things (AIoT), Smart Vision, industrial computing and advanced manufacturing. This end-to-end capability allows us to develop solutions that are relevant to Indian operating conditions while meeting global expectations on quality, reliability, repeatability and scalability.

A strong example is the development of India’s first Industrial Motherboard, which reflects how Indian engineering strengths can translate into specialised platforms for industrial applications. Alongside this, our vertically integrated Design-to-Manufacturing approach enables us to customise solutions for specific customer needs without compromising robustness, repeatability, or scale.

For Indian companies, the opportunity is much larger than manufacturing for the world. India has the engineering depth, industrial base and entrepreneurial mindset to design, develop and manufacture competitive technology solutions for global markets. The ability to combine cost-effective engineering with global standards, interoperability, and long-term lifecycle support can become an important competitive advantage.

The next phase will depend on how effectively organisations combine engineering excellence, technology innovation, manufacturing discipline, and customer understanding. Equally important will be the ability to build solutions that are repeatable, scalable, secure, and capable of integrating with global industrial ecosystems. Companies that bring these together will be well positioned to shape Industry 4.0 solutions not only for India, but for global industry.

ELE Times: What are the existing opportunities and key challenges for manufacturers adopting AI-led industrial technologies at scale?

SW: The opportunity for AI-led industrial technologies is significant because manufacturers are under pressure to improve uptime, quality, productivity, and planning accuracy at the same time. AI can help organisations make sense of large volumes of operational data and convert that data into faster, more informed decisions. Predictive maintenance can shift teams from reacting to breakdowns to preventing them. AI-led vision systems can improve inspection consistency, and intelligent planning tools can support capacity decisions during new program ramp-ups.

However, scaling AI is not only a technology deployment exercise. The real challenge is moving from successful pilots to solutions that can be deployed repeatedly and economically across machines, lines, and plants. The challenge lies in the foundation. Data must be reliable, standardised and available at the right level of detail. Machines must be connected, processes must be consistent, and teams must have the ability to interpret insights and act on them quickly.

Cybersecurity is another critical consideration. As operational technology, enterprise systems and external ecosystems become increasingly connected, manufacturers must ensure that digital transformation does not compromise operational resilience or data security.

Therefore, the core challenge is not access to AI tools. It is building the digital, organisational, and engineering maturity required to move from pilot to scale and implement AI sustainably, securely and with measurable business value.

ELE Times: How do you foresee the future of intelligent factories? What are the technologies that will define the next decade of industrial innovation?

SW: The intelligent factory of the future will be connected, adaptive, and increasingly self-aware. We will see AIoT, Smart Vision, edge computing, advanced automation, and intelligent analytics working together as one integrated operating layer rather than isolated technology investments.

AIoT will provide real-time visibility across machines, utilities and production lines. Smart Vision will support autonomous quality inspection, safety monitoring, and process intelligence. Edge computing will enable faster decisions at the point where data is generated, while Digital Twins will enable manufacturers to simulate and optimise processes, capacity and changes before implementing them in the physical factory. AI will help manufacturers move from monitoring operations to predicting, optimising and continuously improving them.

The next evolution will be from connected factories to learning and increasingly autonomous factories. Digital twins and simulation will allow manufacturers to test changes before implementing them, while AI will increasingly move from providing insights to recommending and, within defined boundaries, executing decisions. The ability of different systems to communicate and learn from each other will be critical to achieving this at scale.

ELE Times: How is the “Make in India” initiative progressing and what role is NASH playing in this initiative?

SW: The Make in India initiative has evolved from a manufacturing-led movement into a larger national capability-building programme, and NASH is proud to be contributing to that transition. For us, Make in India is not only about assembling products locally; it is about creating end-to-end ownership across design, engineering, embedded electronics, software, testing, validation and manufacturing.

This is where NASH has become a preferred partner for customers who are looking for long-term value, reliability, and technology depth. We continue to evolve with industry requirements and have built strong capabilities to support sectors that demand high-quality, mission-critical hardware. A significant example is the movement of complete banking hardware programmes from China to India, where NASH has enabled local design-to-manufacture execution with the required scale, quality and responsiveness.

Our strength lies in combining product engineering, embedded systems, AIoT, industrial computing, smart vision, and advanced manufacturing under one integrated ecosystem. With a strong R&D foundation and over 180+ engineers, we are able to innovate faster, customise solutions for Indian and global customers, and add value at every stage of the product life cycle.

As the country builds deeper capabilities in electronics, industrial technology, EV, renewable energy and automation, NASH is focused on strengthening indigenous technology creation rather than depending on external ecosystems. Our work on industrial motherboards, LFP battery technology, and embedded platforms reflects this commitment. We believe the next phase of Make in India will be driven by companies that can design in India, manufacture in India and deliver globally competitive products. NASH is aligned to that vision, and we see our role as enabling customers to localise critical technologies while maintaining global standards of performance, quality and innovation.

ELE Times: Brief us about the current state of Lithium-ion technology for EVs in India and how NASH Energy is poised to deliver the required technology.

SW: Lithium-ion technology today is at an important inflection point in India’s EV journey. While the initial phase of adoption was largely driven by battery availability and cost, the market is now maturing towards a stronger focus on safety, reliability, lifecycle performance, thermal stability and localisation of critical materials & technologies. For Indian operating conditions, especially in mobility and energy storage applications, LFP chemistry is gaining strong relevance because of its inherent safety, durability and suitability for long-term use. At the same time, as applications evolve, there is a need to remain chemistry-agnostic and continuously evaluate other cell chemistries that can serve specific performance, energy density and use-case requirements.

At NASH Energy, our focus is to build deep technology and manufacturing capabilities across the battery value chain. We are working on LFP cell manufacturing along with advanced battery packs, battery management systems, power electronics and integrated energy storage solutions, while also exploring adjacent chemistries that may be relevant for future mobility and energy storage applications. This approach allows us to address not just the cell requirement, but the complete technology stack needed for reliable and scalable EV and industrial applications.

India has a significant opportunity to move beyond battery assembly and establish itself as a strong hub for cell technology, engineering and manufacturing. NASH Energy is well-positioned to contribute to this transition by combining technology expertise, manufacturing capability and application-level understanding to deliver safe, dependable and Made-in-India energy solutions for the evolving EV ecosystem.

ELE Times: How are AIoT, edge computing and intelligent automation reshaping modern manufacturing techniques?

SW: The convergence of the Artificial Intelligence of Things (AIoT), edge computing, and intelligent automation is transforming manufacturing from rigid, centrally scheduled assembly lines into adaptive, decentralised, and autonomous production ecosystems. This is possible by moving intelligence closer to machines, processes, and operators, instead of delayed action/analysis.

Primary decision drivers for the transformations on the Factory Floor:

• Ultra-Low Latency Quality Control
• Condition-Based & Prescriptive Maintenance
• Dynamic Shop-Floor Orchestration
• Live Digital Twins & Closed-Loop Tuning
• Adaptive Resource & Energy Optimisation

At NASH, we see these technologies as the foundation of smarter, more responsive industrial ecosystems. By integrating embedded electronics, industrial computing, AI and software, our solutions support applications such as predictive maintenance, process monitoring, machine vision, OEE analysis and industrial automation. These capabilities also help similar manufacturers reduce downtime, improve quality consistency, enhance traceability, and optimise resource utilisation.

For us, the value of AIoT and automation lies in solving real operational challenges, not in adopting technology for its own sake. When implemented with the right hardware, software and manufacturing expertise, these technologies enable faster decision-making, higher reliability, and more flexible production. This is how modern manufacturing is evolving from reactive operations to intelligent, data-driven and future-ready factories.

The post Interview | Sanjay Wadhwa, Chairman & Managing Director, NASH Group of Companies appeared first on ELE Times.

DigiKey, the global distribution leader of electronic components and automation products, today announced a $100 million investment over the next 18 months to expand its global product distribution centre in Thief River Falls, Minn., and its order management system. This escalation of capacity and automation is designed to support sustained growth in demand for its industry-leading same-day fulfilment model.

Expansion at record-growth pace

The investment funds the next phases of DigiKey’s product distribution centre (PDC) expansion, adding high-volume picking capacity and advanced automated packing operations. The first new automated packing system is already on site and will be in use this year, with additional multi-line packing automation phased in as part of the investment program.

The announcement follows a year of extraordinary growth for the company. DigiKey is on pace to grow more than 50 percent in 2026, and projects continued double-digit growth in the year ahead.

“Our customers choose DigiKey because they know we’re fast and they know we’ll be fast tomorrow,” said DigiKey CEO Dave Doherty. “A $100 million commitment says exactly that: we’re expanding capacity and automating where it counts to keep same-day fulfillment the standard, not the exception.”

Building for future scale

The expansion continues the design philosophy behind the company’s purpose-built product distribution centre: building in capacity ahead of demand. DigiKey’s state-of-the-art, 2.2 million-square-foot product distribution centre expansion project opened in Aug. 2022 and was designed for scalable growth, with many open spaces and much of the fourth floor left empty for future expansion.

New picking bays, order retrieval automation and expanded packing operations will process a growing share of order volume across multiple product form factors with higher speed and efficiency. Every investment in DigiKey is focused on the ultimate goal of sustainable growth.

“Simplification creates capacity, and capacity creates growth,” said Doherty. “We’re redirecting resources from legacy work to future capabilities and investing in where we’re going, not just where we’ve been.”

The investment reinforces DigiKey’s position as a global leader in electronic component distribution, serving one million customers annually with more than 1.9 million products in stock and ready to ship the same day from the product distribution centre.

The post DigiKey Commits $100 Million Investment Over Next 18 Months to Expand Global Distribution Operations appeared first on ELE Times.

pSemi offers the PE566212 and PE566213 2.4-GHz SOI front-end modules (FEMs) for Bluetooth, Zigbee, and Thread applications. Each module integrates a power amplifier, low-noise amplifier, and RF switch in a compact 1.8×1.8×0.63-mm LGA package, simplifying RF design. Applications include smart home devices, wireless audio, wearables, and sensing systems.

The FEMs provide transmit output power up to +20 dBm, a receive noise figure of 1.8 dB at 13 dB of gain, and typical bypass-path loss of 0.8 dB. According to pSemi, the FEMs offer 5 to 10 times the range of a standalone SoC. Based on pSemi’s UltraCMOS+ SOI process, they offer a highly integrated silicon-based alternative to GaAs- and SiGe-based front ends.

The PE566212 supports Bluetooth Basic Data Rate (BDR) and Bluetooth Low Energy (BLE), with 22.5 dB of transmit digital gain control in 1.5-dB steps. The PE566213 adds Bluetooth Enhanced Data Rate (EDR) support at up to +11.5 dBm and offers 15 dB of transmit digital gain control in 1-dB steps. Applications include smart home devices, wireless audio, wearables, and sensing systems.

The front-end modules are available now, along with corresponding evaluation boards.

PE566212 product page 

PE566213 product page

pSemi

The post Integrated FEMs ease 2.4-GHz RF design appeared first on EDN.

A liquid-cooling cold plate, Frore’s LiquidJet Diamond integrates a diamond heat spreader to cool hotspots in high-power-density AI GPUs. Its 3D, short-loop, multistage cooling architecture can be customized to match a GPU’s power map, directing coolant to the hottest areas before cooling the rest of the GPU die, high-bandwidth memory (HBM), and other SoC chiplets.

Compared with conventional skived cold plates, LiquidJet Diamond achieves up to 75% higher heat-transfer efficiency and more than 150% higher maximum power density. Frore also claims 16–22°C lower GPU temperatures and 30–35% higher AI tokens-per-watt efficiency.

Beyond thermal performance and hotspot management, LiquidJet Diamond offers a seamless drop-in upgrade for hyperscale data centers. Frore says its manufacturing process combines semiconductor-fabrication precision with the production capacity needed to meet the quality and volume requirements of AI data center deployments.

LiquidJet Diamond product page 

Frore Systems 

The post Diamond spreader tames AI GPU hotspots appeared first on EDN.

Aetina’s AIE-KT78/68 edge AI systems are powered by NVIDIA Jetson Thor platforms featuring the Blackwell GPU architecture for deterministic industrial control. Targeting collaborative robots (cobots), humanoid robots, and autonomous machines, these compact systems run multimodal AI models locally, reducing reliance on cloud processing and associated latency. Supported workloads include generative AI, large language models (LLMs), vision-language models (VLMs), and vision-language-action models (VLAs).

The AIE-KT78 uses the Jetson T5000 system-on-module, with 128 GB of LPDDR5X memory on a 256-bit interface and up to 2,070 FP4 TFLOPS of AI compute performance. The AIE-KT68 features the Jetson T4000 system-on-module, with 64 GB of LPDDR5X memory on the same interface and up to 1,200 FP4 TFLOPS.

Each system provides QSFP28 connectivity with up to 4×25-Gbps bandwidth, dual 10GbE RJ45 ports, and support for up to eight GMSL2 camera inputs to handle data from cameras, LiDAR, radar, and other sensors. A dedicated 1GbE RJ45 EtherCAT port operates as an independent EtherCAT master, synchronizing motors, joints, sensors, and actuators for deterministic control.

Both edge AI platforms run Linux with the full NVIDIA AI software stack.

AIE-KT78/68 product page 

Aetina

The post Systems reduce latency in edge AI automation appeared first on EDN.

Renesas Electronics has launched its first family of 100-V enhancement-mode (E-mode) discrete GaN power transistors. The company says the RTP100E005G1FL, RTP100E2P6G1FL, RTP100E1P8G1FL-DSC and RTP100E1P2G1FL-DSC low-voltage GaN FETs achieve industry-leading hard- and soft-switching figure-of-merit (FOM). They deliver up to 35% lower hard-switching FOM and up to 63% lower soft-switching FOM than comparable GaN devices.

Offered in FCLGA packages that maintain a silicon-compatible footprint, the GaN FETs let designers migrate from silicon MOSFET layouts without significant PCB rework. The RTP100E005G1FL and RTP100E2P6G1FL have typical on-resistance of 5 mΩ and 2.6 mΩ, respectively. The dual-side-cooled RTP100E1P8G1FL-DSC and RTP100E1P2G1FL-DSC have on-resistance of 1.8 mΩ and 1.2 mΩ, respectively. Depending on application requirements and power-conversion architecture, the transistors can achieve up to 40–70% lower switching losses and up to twice the power density at the system level.

The 100-V family targets high-power-density applications, including AI data centers, humanoid robotics, and factory automation. Package options and a wide range of on-resistance values allow the transistors to address different power levels and applications, including synchronous rectification, multiphase buck conversion, and industrial motor drives.

The new low-voltage GaN power transistors are available now, along with corresponding evaluation boards.

Renesas Electronics 

The post 100-V GaN FETs lower switching FOM appeared first on EDN.

METCASE has redesigned its COMBIMET 19-in. rack-mount enclosures to provide greater rigidity and more usable panel space. The aluminum cases are suitable for networking and communications equipment, industrial computers, sound and studio systems, laboratory instruments, and industrial control applications.

The COMBIMET range now offers 68 standard model, size, and color permutations. Improved tabs create stronger, more reliable connections between enclosure components, while enlarged hidden apertures behind the front and rear panels allow more room for displays, controls, switches, connectors, and ventilation. Standard case heights range from 1U to 6U, with depths of 10.43 in., 14.37 in., and 24.00 in.

Enclosures have removable top, base, and rear panels for easy access to electronics. Both the top and base come with or without vents as standard. Units are available in black or light gray. COMBIMET enclosures can also be customized in size, panel design, color, finish, and graphics to meet specific application requirements.

Sales inquiries can be directed to sales@metcaseusa.com.

COMBIMET product page

METCASE

The post Updated rack enclosures offer flexible design options appeared first on EDN.

submitted by /u/WIZNERDCS [link] [comments]

Driving a portable Bluetooth thermal printer from an ESP32-C3 microcontroller, without going through the vendor’s smartphone app. That is what Bas BotBerg does, and the result is that reports on sensor data end up on thermal paper with no phone involved at all. The method is not the usual Bluetooth log capture on Android: the author queries the device directly and reconstructs its communication protocol.

The interesting part is the underlying choice. Instead of relying on the manufacturer’s app, the project uses an application that lists the printer’s Bluetooth Low Energy services and characteristics. That way the work shifts away from the encrypted traffic of a closed app and towards the services the device exposes, which stay visible and queryable.

Identifying the writable services and sending the first payloads

The next step is to separate the services marked as writable from all the others. On those, the author starts sending data and observes how the printer responds. It is a process of trial and error, but every response narrows the field. The discovery phase is therefore done in Python with the Bleak library, which makes it possible to iterate and adapt the code in seconds.

• Query the device and read the list of Bluetooth Low Energy services.
• Isolate the characteristics marked as writable.
• Send test payloads and observe how the printer reacts.
• Adapt the Python code with the Bleak library at every attempt.
• Map commands and endpoints once you understand what triggers them.

The first milestone comes when the printer’s motor starts and feeds the paper. That movement confirms that the command identified is the right one and that the approach is the correct one. From there the work becomes more orderly: payloads are noted down, the endpoints to send them to are noted down, and the protocol map takes shape.

Moving the payloads into the C++ firmware on the ESP32-C3

Once the data to send and the endpoints to send it to have been mapped in Python, the same payloads move into the C++ code on the ESP32-C3. The microcontroller then becomes the printer’s only counterpart. The Adafruit GFX library is also used to produce icons and to format the output more easily, so the report is not just raw text but has a readable structure.

For anyone who wants to rebuild the project, the starting board is compact and has the radio built in: the ESP32-C3 module in SuperMini format covers both the Bluetooth Low Energy side and sensor control. The rest of the work is in the firmware, not the hardware.

Anyone who has already taken apart a portable thermal printer knows that the critical point is not the mechanics. The critical point is the protocol, and that is exactly what the project tackles. The method used is an alternative to Bluetooth log capture on Android, and in some ways more direct: you talk to the device instead of spying on an app. Bas BotBerg’s project page on Hackaday.io collects the work done on this Bluetooth thermal printer.

The case is a good reference for anyone who needs to control, from a microcontroller, peripherals that the manufacturer makes accessible only through proprietary applications. The sequence is always the same: list the services, find the writable ones, send data, observe the responses, map the payloads. The device changes, not the method.

Source: https://hackaday.io/contests

Related products

• Mini ESP32-C3 module

The post Driving a Bluetooth Thermal Printer with the ESP32-C3 appeared first on Open Electronics.

VisIC Technologies Ltd of Ness Ziona, Israel — a fabless supplier of power conversion devices based on gallium nitride (GaN) transistors — and mobility technology company AVL are advancing their collaboration with the integration of VisIC’s D3GaN power module technology into AVL’s vehicle demonstrator...

This silly simple circuit cancels out potentially serious digital potentiometer zero- and full-scale errors.

Everybody (well, most everybody) knows that digipots tend to be more accurate when used as variable voltage dividers (i.e., in potentiometer mode) and not so much when used as variable resistors (in rheostat mode). In pot mode, many error-promoting effects like resistance element tolerances and temperature coefficients cancel out (well, mostly). But even when pots are used as actual pots, some small non-idealities might still sneak by. One (okay, two) of these are zero- and full-scale ratio errors.

Figure 1 shows a simple Dpot output buffer that should work fine when the error terms are small.

Figure 1 Dpot U1 runs in straightforward voltage-division potentiometer mode with unity-gain buffer A1 providing isolation from output loading. So everything should be nicely ideal with Vsigout = Vsigin(Rwa/Rba).

Unfortunately, sometimes the errors are not so small. For example, if U1 were an 8-bit (1/256) resolution MAX5451, then typical values for full-scale and zero-scale errors are listed in its datasheet as 8lsb = 3.1%, which makes the actual achieved accuracy look more like only 5 bits instead of the claimed 8.

Vsigout = Vsigin((Rwa/Rba)(1 – Fullscale) + (Rwb/Rba)(Zeroscale))
Fullscale = Zeroscale = 0.031 (typical)
Vsigout = Vsigin(Rwa/Rba) +/-3%

In any precision-critical application, those 3% offsets are likely to be unacceptable. Fortunately, Figure 2 suggests how a simple 3-resistor error-nulling fix is possible.

Figure 2 If R1 = R2 x (scale error) then the errors disappear and Vsigout = Vsigin(Rwa/Rba).

Here’s how it works. Note that, for best performance, R2 and R3 should equal each other to ~0.1% and R1 should be adjusted equal to R1 = ScaleErrorPercentage x R2. An easy way to accomplish this is as follows:

1. Adjust U1 to its maximum UP setting. Then Rwa = Rba.
2. Set SigIn = V+ – 100mV or so. The exact voltage isn’t critical; we’re just insuring that A1 won’t saturate.
3. Connect a sensitive voltmeter between SigIn and SigOut.
4. Adjust R1 to null the meter reading and force Vsigout = Vsigin.

Done.

In some applications, error cancellation might be good enough with R1 equal to a fixed value calculated from the datasheet figures, instead of needing post-assembly calibration. 31 kΩ, for example, would align with the MAX5451’s data.

Which might niftily null some non-negligible production costs.

Stephen Woodward‘s relationship with EDN’s DI column goes back quite a long way. Over 200 submissions have been accepted since his first contribution back in 1974.  They have included best Design Idea of the year in 1974 and 2001.

Related Content

• DPOT push up/down
• Finger-friendly DPOT pushbuttons do ups, downs, and dittos
• Double DPOT programming: Parallel gang-up, singleton, or none
• Digital potentiometer simulates log taper to accurately set gain
• Push to increase, decrease a digital potentiometer
• Synthesize precision bipolar Dpot rheostats

The post Nifty nulling of non-negligible dpot “scale” errors appeared first on EDN.

🚀 Збудуй свою МРІЮ — зроби перший крок у світ інженерії! kpi ср, 10/14/2026 - 14:58

Specialty analog foundry Tower Semiconductor Ltd of Migdal Haemek, Israel and high-performance semiconductor, Internet of Things (IoT) system and cloud connectivity service provider Semtech Corp of Camarillo, CA, USA have agreed to expand their 20-year partnership. Semtech will invest in securing dedicated silicon germanium (SiGe) capacity at Tower in support of its strong design wins and demand for AI data-center optical interconnect components...

The BH1750 sensor converts light intensity into a digital value and makes it available on the I2C bus. Its measurement range goes from 1 to 65,535 lux. On the GY-302 breakout the sensor comes ready to use with Arduino, ESP32 and other boards. AdriRobot tried it with an Arduino UNO and writes about it on his blog.

What the BH1750 sensor measures

The lux is the unit of measurement for illuminance: it corresponds to one lumen per square metre. It therefore describes the light falling on a surface, evaluated as the human eye perceives it. For reference, light reflected by a full Moon is about 1 lx, a bright office is about 400 lx, and sunlight ranges between 32,000 and 100,000 lx.

Measurement modes and resolution

The BH1750 works in six modes, divided into two groups: continuous measurement and single measurement. In continuous mode the sensor detects light without stopping. In single mode it takes one measurement and then shuts down, so it must be reconfigured before the next reading. The library used in the article does this automatically.

Each mode offers three levels of precision:

• low resolution: 4 lx precision and 16 ms measurement time;
• high resolution: 1 lx and 120 ms;
• high resolution 2: 0.5 lx and 120 ms.

By default the library selects continuous high resolution. In low and high resolution modes the maximum value is 54,612.5 lx, while in high resolution 2 it stops at 27,306.25 lx. In practice the sensor returns a 16-bit integer, which the library converts into lux by dividing it by 1.2. A result of -1 means no valid data arrived, while -2 signals an unconfigured device.

You can also change the time interval in which the sensor counts light, through the MTreg register. The value ranges from 32 to 254 and the default is 69.

The GY-302 module: power, pinout and address

On the GY-302 the sensor is joined by a 3.3 V LDO regulator, marked 662K, and its capacitors. The module therefore accepts Arduino’s 5 V on the VCC pin. The regulator supplies up to 250 mA and withstands a maximum of 6.5 V at its input. On the SCL and SDA lines there are also two 4.7 kΩ pull-up resistors. The breakout is sold as a light intensity sensor.

The connector has five pins: VCC, GND, SCL, SDA and ADDR. The last one is used to choose the I2C address and comes into play when several BH1750 sensors share the same bus. With ADDR at a low level the address is 0x23, with ADDR high it becomes 0x5C. On the module tested the pin is tied to ground through a 4.7 kΩ resistor, so the sensor responds at 0x23.

• measurement range: from 1 to 65,535 lux;
• supply voltage: from 3 to 5 V;
• operating temperature: from -40 to +85 °C;
• dimensions: 18.5 × 13.9 × 2.5 mm, connectors excluded.

Connecting it to an Arduino UNO and an OLED display

For the first test you only need an Arduino UNO board, the GY-302 module and a few male-to-female jumper wires. VCC and GND go to the power supply, while SDA and SCL connect to Arduino’s I2C pins. Before uploading the sketch it is worth running the IDE’s i2c_scanner example: if the wiring is correct, the serial monitor reports a device at address 0x23.

The reading uses Christopher Laws’ BH1750 library, which is installed from the Library Manager together with the Wire library, already included in the IDE. The sketch reads the value every second and also writes it to the serial monitor.

The project is then completed with a 0.96-inch OLED display, 128×64 pixels, SSD1306 driver and I2C interface. The display responds at address 0x3C, so it shares the same bus as the sensor. The Adafruit SSD1306 and Adafruit GFX libraries are needed, and the lux meter shows the lux directly on the screen.

Anyone who wants to see the BH1750 at work in a larger project can read the ESP32 weather station with a live web dashboard, which pairs it with a DHT22 and a BMP280.

Source: the original AdriRobot article also contains the complete schematic, the sketches and the test video.

Related products

• Light intensity sensor
• OLED Display I2C 0.96” – VCC/GND/SCL/SDA

The post BH1750 Sensor: Measuring Lux with Arduino and the GY-302 appeared first on Open Electronics.