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I've made an ARM based single-board computer that runs Android and Linux, and has the same size as the Raspberry Pi 3! Why? I was bored during my 2-week high-school vacation and wanted to improve my skills, while adding a bit to the open-source community :P I ended up with a H3 Quad-Core Cortex-A7 ARM CPU with a Mali400 MP2 GPU, combined with 512MiB of DDR3 RAM (Can be upgraded to 1GiB, but who has money for that in this economy). The board is capable of WiFi, Bluetooth & Ethernet PHY, with a HDMI 4k port, 32 GB of eMMC, and a uSD slot. I've picked the H3 for its low cost yet powerful capabilities, and it's pretty well supported by the Linux kernel. Plus, I couldn't find any open-source designs with this chip, so I decided to contribute a bit and fill the gap. A 4-layer PCB was used for its lower price and to make the project more challenging, but if these boards are to be mass-produced, I'd bump it up to 6 and use a solid ground plane as the bottom layer's reference plane. The DDR3 and CPU fanout was really a challenge in a 4-layer board. The PCB is open-source on the Github repo with all the custom symbols and footprints (https://github.com/cheyao/icepi-sbc). There's also an online PCB viewer here. submitted by /u/cyao12 [link] [comments]

EDN Design Ideas (DI) published a design of mine in May of 2025 for a passive two-way current mirror topology that, in analogy to optical two-way mirrors, can reflect or transmit. 

That design comprises just two BJTs and one diode. But while its simplicity is nice, its symmetry might not be. That is to say, not precise enough for some applications.

Wow the engineering world with your unique design: Design Ideas Submission Guide

Fortunately, as often happens when the precision of an analog circuit falls short, and the required performance can’t suffer compromise, a fix can consist of adding an RRIO op amp. Then, if we substitute two accurately matched current-sensing resistors and a single MOSFET for the BJTs, the result is the active two-way current mirror (ATWCM) as shown in Figure 1.

Figure 1 The active two-way current sink/source mirror. The input current source is mirrored as a sink current when D1 is forward biased, and transmitted as a source current when D1 is reverse biased.

Figure 2 shows how the ATWCM operates when D1 is forward-biased, placing it in mirror mode.

Figure 2 ATWCM in mirror mode, I1 sink current generates Vr, forcing A1 to coax Q1 to mirror I2 = I1.

The operation of the ATWCM in mirror mode couldn’t be more straightforward. Vr = I1R wired to A1’s noninverting input forces it to drive Q1 to conduct I2 such that I2R = I1R. 

Therefore, if the resistors are equal, A1’s accuracy-limiting parameters (offset voltage, gain-bandwidth, bias and offset currents, etc.) are adequately small, and Q1 does not saturate, I1 = I2 just as precisely as you like.

Okay, so I lied.  Actually, the operation of the ATWCM in transmission mode is even simpler, as Figure 3 shows.

Figure 3 ATWCM in transmission mode. A reverse-biased D1 means I1 has nowhere to go except through the resistors and (saturated and inverted) Q1, where it is transmitted back out as I2.

I1 flowing through the 2R net resistance forces A1 to rail positive, saturating Q1 and providing a path back to the I2 pin. Since Q1 is biased inverted, its body diode will close the circuit from I1 to I2 until A1 takes over. A1 has nothing to do but act as a comparator.

Flip D1 and substitute a PFET for Q1, and of course, a source/sink will result, shown in Figure 4.

Figure 4 Source/sink two-way mirror with a D1 flipped the opposite direction, and Q1 replaced with a PFET. 

Figure 5 shows the circuit in Figure 4 running a symmetrical rail-to-rail tri-wave and square-wave output multivibrator.

Figure 5 Accurately symmetrical tri-wave and square-wave result from inherent A1Q2 two-way mirror symmetry.

Stephen Woodward’s relationship with EDN’s DI column goes back quite a long way. Over 100 submissions have been accepted since his first contribution back in 1974.

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The post Active two-way current mirror appeared first on EDN.

Designers are looking to reduce the cost of drone systems for a wide range of applications but still need to provide accurate positioning data. This however is not as easy is it might appear.

There are several satellite positioning systems, from the U.S.-backed GPS and European Galileo to NavIC in India and Beidou in China, providing data down to the meter. However, these need to be augmented by an inertial measurement unit (IMU) that provides more accurate positioning data that is vital.

Figure 1 An IMU is vital for the precision control of the drone and peripherals like gimbal that keeps the camera steady. Source: Epson

An IMU is typically a sensor that can measure movement in six directions, along with an accelerometer to detect the amount of movement. The data is then used by the developer of an inertial measurement system (IMS) with custom algorithms, often with machine learning, combined with the satellite data and other data from the drone system.

The IMU is vital for the precision control of the drone and peripherals such as the gimbal that keeps the camera steady, providing accurate positioning data and compensating for the vibration of the drone. This stability can be implemented in a number of ways with a variety of sensors, but providing accurate information with low noise and high stability for as long as possible has often meant the sensor is expensive with high power consumption.

This is increasingly important for medium altitude long endurance (MALE) drones. These aircraft are designed for long flights at altitudes of between 10,000 and 30,000 feet, and can stay airborne for extended periods, sometimes over 24 hours. They are commonly used for military surveillance, intelligence gathering, and reconnaissance missions through wide coverage.

These MALE drones need a stable camera system that is reliable and stable in operation and a wide range of temperatures, providing accurate tagging of the position of any data captured.

One way to deliver a highly accurate IMU with lower cost is to use a piezoelectric quartz crystal. This is well established technology where an oscillating field is applied across the crystal and changes in motion are picked up with differential contacts across the crystal.

For a highly stable IMU for a MALE drone, three crystals are used, one for each axis, stimulated at different frequencies in the kilohertz range to avoid crosstalk. The differential output cancels out noise in the crystal and the effect of vibrations.

Precision engineering of piezoelectric crystals for high-stability IMUs

Using a crystal method provides data with low noise, high stability, and low variability. The highly linear response of the piezoelectric crystal enables high-precision measurement of various kinds of movement over a wide range from slow to fast, allowing the IMU to be used in a broad array of applications.

An end-to-end development process allows the design of each crystal to be optimized for the frequencies used for the navigation application along with the differential contacts. These are all optimized with the packaging and assembly to provide the highly linear performance that remains stable over the lifetime of the sensor.

It uses 25 years of experience with wet etch lithography for the sensors across dozens of patents. That produces yields in the high nineties with average bias variations, down to 0.5% variant from unit to unit.

An initial cut angle on the quartz crystal achieves the frequency balance for the wafer, then the wet etch lithography is applied to the wafer to create a four-point suspended cantilever structure that is 2-mm long. Indentations are etched into the structure for the wire bonds to the outside world.

The four-point structure is a double tuning fork with detection tines and two larger drive tines in the centre. The differential output cancels out spurious noise or other signals.

This is simpler to make than micromachined MEMS structures and provides more long-term stability and less variability across the devices.

The differential structure and low crosstalk allow three devices to be mounted closely together without interfering with each other, which helps to reduce the size of the IMU. A low pass filter helps to reduce any risk of crosstalk.

The six-axis crystal sensor is then combined with an accelerometer for the IMU. For the MALE drone gimbal applications, this accelerometer must have a high dynamic range to handle the speed and vibration effects of operation in the air. The linearity advantage of using a piezoelectric crystal provides accuracy for sensing the rotation of the sensor and does not degrade with higher speeds.

Figure 2 Piezoelectric crystals bolster precision and stability in IMUs. Source: Epson

This commercial accelerometer is optimized to provide the higher dynamic range and sits alongside a low power microcontroller and temperature sensors, which are not common in low-cost IMUs currently used by drone makers.

The microcontroller technology has been developed for industrial sensors over many years and reduces the power consumption of peripherals while maintaining high performance.

The microcontroller is used to provide several types of compensation, including temperature and aging, and so provides a simple, stable, and high-quality output for the IMU maker. Quartz also provides very predictable operation across a wide temperature range from -40 ⁰C to +85 ⁰C, so the compensation on the microcontroller is sufficient and more compensation is not required in the IMU, reducing the compute requirements.

All of this is also vital for the calibration procedure. Ensuring that the IMU can be easily calibrated is key to keeping the cost down and comes from the inherent stability of the crystal.

Calibration-safe mounting

The mounting technology is also key for the calibration and stability of the sensor. A part that uses surface mount technology (SMT), such as a reflow oven, for mounting to a board, which is exposed to high temperatures that can disrupt the calibration and alter the lifetime of the part in unexpected ways.

Instead, a module with a connector is used, so the 1-in (25 x 25 x 12 mm) part can be soldered to the printed circuit board (PCB). This avoids the need to use the reflow assembly for surface mount devices where the PCB passes through an oven, which can upset the calibration of the sensor.

Space-grade IMU design

A higher performance variant of the IMU has been developed for space applications. Alongside the quartz crystal sensor, a higher performance accelerometer developed in-house is used in the IMU. The quartz sensor is inherently impervious to radiation in low and medium earth orbits and is coupled with a microcontroller that handles the temperature compensation, a key factor for operating in orbits that vary between the cold of the night and the heat of the sun.

The sensor is mounted in a hermetically sealed ceramic package that is backfilled with helium to provide higher levels of sensitivity and reliability than the earth-bound version. This makes the quartz-based sensor suitable for a wide range of space applications.

Next-generation IMU development

The next generation of etch technology being explored now promises to enable a noise level 10 times lower than today with improved temperature stability. These process improvements enable cleaner edges on the cantilever structure to enhance the overall stability of the sensor.

Achieving precise and reliable drone positioning requires the integration of advanced IMUs with satellite data. The use of piezoelectric quartz crystals in IMUs for drone systems offers significant benefits, including low noise, high stability, and reduced costs, while commercial accelerometers and optimized microcontrollers further enhance performance and minimize power consumption.

Mounting and calibration procedures ensure long-term accuracy and reliability to provide stable and power-efficient control for a broad range of systems. All of this is possible through the end-to-end expertise in developing quartz crystals, and designing and implementing the sensor devices, from the etch technology to the mounting capabilities.

David Gaber is group product manager at Epson.

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• ST Launches AI-Enabled IMU for Activity Tracking and High-Impact Sensing

The post Aiding drone navigation with crystal sensing appeared first on EDN.

Баскетбол. Студентська ліга м. Києва. Стартуємо гучно! kpi ср, 12/24/2025 - 13:04

The South Wales-based compound semiconductor cluster CSconnected has announced MicroLink Devices UK Ltd as an awardee of the CSconnected Supply Chain Development Programme — Call 2...

Another day, another dodgy device. This time, it was the continuity beeper on my second-best DMM. Being bored with just open/short indications, I pondered making something a little more informative.

Perhaps it could have an input stage to amplify the voltage, if any, across current-driven probes, followed by a voltage-controlled tone generator to indicate its magnitude, and thus the probed resistance. Easy! . . . or maybe not, if we want to do it right.

Wow the engineering world with your unique design: Design Ideas Submission Guide

Figure 1 shows the (more or less) final result, which uses a carefully-tweaked amplifying stage feeding a pitch-linear VCO (PLVCO). It also senses when contact has been made, and so draws no power when inactive.

Most importantly, it produces a tone whose musical pitch is linearly related to the sensed resistance: you can hear the difference between fat power traces and long, thin signal ones while probing for continuity or shorts on a PCB without needing to look at a meter.

Figure 1 A power switch, an amplifying stage with some careful offsets, and a pitch-linear VCO driving an output transducer make a good continuity tester. The musical pitch of the tone produced is proportional to the resistance across the probe tips.

This is simpler than it initially looks, so let’s dismantle it. R1 feeds the test probes. If they are open-circuited, p-MOSFET Q1 will be held off, cutting the circuit’s power (ignoring <10 nA leakage).

Any current flowing through the probes will bring Q1.G low to turn it on, powering the main circuit. That also turns Q2 on to couple the probe voltage to A1a.IN+ via R2. Without Q2, A1a’s input protection diodes would draw current when power was switched off.

R1 is shown as 43k for an indication span of 0 to ~24 Ω, or 24 semitones. Other values will change the range, so, for example, 4k3 will indicate up to 2.4 Ω with 0.1-Ω semitones. Adding a switch gave both ranges. (The actual span is up to ~30 Ω—or 3.0 Ω—but accuracy suffers.) Any other values can be used for different scales; the probe current will, of course, change.

A1a amplifies the probe voltage by 1001-ish, determined by R3 and R4. We are working right down to 0 V, which can be tricky. R5 offsets A2a.IN- by ~5 mV, which is more than the MCP6002’s quoted maximum input offset of 3.5 mV. R2 and R6–8 help to add a slightly greater bias to A1a.IN+ that both null out any offset and set the operating point. This scheme may avert the need for a negative rail in other applications.

Tuning the tones

The A1b section is yet another variant on my basic pitch-linear VCO, the reset pulse being generated by Q4/C3/R13. (For more informative details of the circuit’s general operation, see the original Design Idea.) The ’scope traces in Figure 2 should clarify matters.

Figure 2. Waveforms within the circuit to show its operation while probing different resistances.

This type of PLVCO works best with a control voltage centered between the supply rails and swinging by ±20% about that datum, giving a bipolar range of ~±1 octave. Here, we need unipolar operation, starting around that -20% lowest-frequency point.

Therefore, 0 Ω on the input must give ~0.3 Vcc to generate a ~250 Hz tone; 12 Ω, 0.5 Vcc (for ~500 Hz); and 24 Ω, ~0.7 Vcc (~1 kHz). Anything above ~0.8 Vcc will be out of range—and progressively less accurate—and must be ignored.

The output is now a tone whose pitch corresponds to the resistance across the probes, scaled as one semitone per ohm and spanning two octaves for a 24 Ω range (if R1 is 43k).

The modified exponential ramp on C2 is now sliced by A2b, using a suitable fraction of the control voltage as a reference, to give a “square” wave at its output—truly square at one point only, but it sounds OK, and this approach keeps the circuit simple. A2a inverts A2b’s output, so they form a simple balanced (or bridge-tied load) driver for an earpiece. (There are problems here, but they can wait.)

R9 and R10 reduce A1a’s output a little as high resistances at the input cause it to saturate, which would otherwise stop A1b’s oscillation. This scheme means that out-of-range resistances still produce an audio output, which is maxed out at ~1.6 kHz, or ~30 Ω. Depending on Q1’s threshold voltage, several tens of kΩs across the probes are enough to switch it on—a tad outside our indication range.

Loud is allowed

Now for that earpiece, and those potential problems. Figure 1’s circuit worked well enough with an old but sensitive ~250-Ω balanced-armature mic/’phone but was fairly hopeless when trying to drive (mostly ~32 Ω) earphones or speakers.

For decent volume, try Figure 4, which is beyond crude, but functional. Note the separate battery, whose use avoids excessive drain on the main one while isolating the main circuit from the speaker’s highish currents.

Again, no power is drawn when the unit is inactive. (Reused batteries—strictly, cells—from disposed-of vapes are often still half-full, and great for this sort of thing! And free.) A2a is now spare . . .

Figure 3 A simple, if rather nasty, way of driving a loudspeaker.

Setting-up is necessary, because offsets are unpredictable, but simple. With a 12-Ω resistance across the probes, adjust R7 to give Vcc/2 at A1b.5. Done!

Comments on the components

The MCP6002 dual op-amp is cheap and adequate. (The ’6022 has a much lower offset but a far higher price, as well as drawing more current. “Zero-offset” devices are yet more expensive, and trimmer R7 would probably still be needed.)

Q3, and especially Q1, must have a low RDS(on) and VGS(th); my usual standby ZVP3306As failed on both counts, though ZVN3306As worked well for Q2/4/5. (You probably have your own favorite MOSFETs and low-voltage RRIO op-amps.) To alter the frequency range, change C2. Nothing else is critical.

As noted above, R1 sets the unit’s sensitivity and can be scaled to suit without affecting anything else. With 43k, the probe current is ~70 µA, which should avoid any possible damage to components on a board-under-test.

(Some ICs’ protection diodes are rated at a hopefully-conservative 100 µA, though most should handle at least 10 mA.) R2 helps guard against external voltage insults, as well as being part of the biasing network.

And that newly-spare half of A2? We can use it to make an active clamp (thanks, Bob Dobkin) to limit the swing from A1a rather than just attenuating it. R1 must be increased—51k instead of 43k—because we no longer need extra gain.

Figure 4 shows the circuit. When A2a’s inverting input tries to rise higher than its non-inverting one—the reference point—D1 clamps it to that reference voltage.

Figure 4. An active clamp is a better way of limiting the maximum control voltage fed to the PLVCO.

The slight frequency changes with supply voltage can be ignored; a 20°C temperature rise gave an upward shift of about a semitone. Shame: with some careful tuning, this could otherwise also have done duty as a tuning fork.

“Pitch-perfect” would be an overstatement, but just like the original PLVCO, this can be used to play tunes! A length of suitable resistance wire stretched between a couple of drawing pins should be a good start . . . now, where’s that half-dead wire-wound pot? Trying to pick out a seasonal “Jingle Bells” could keep me amused for hours (and leave the neighbors enraged for weeks).

 —Nick Cornford built his first crystal set at 10, and since then has designed professional audio equipment, many datacomm products, and technical security kit. He has at last retired. Mostly. Sort of.

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The post Tuneful track-tracing appeared first on EDN.

Hello everyone, last week I posted my AM radio in a 4layer pcb design. I got loads of good suggestions as well as people saying that 4layers was overkill. Here is the two layer design! And thanks for all the suggestions I may upgrade this design using transistors to amplify the rf signal. Schematics First layer GND with 9V island Second layer GND Original Post submitted by /u/S4vDs [link] [comments]

Інженерні тижні «KPISchool» для учнів 9–11 класів у КПІ ім. Ігоря Сікорського kpi вт, 12/23/2025 - 13:36

Japan-based power electronics manufacturer Fuji Electric Co Ltd and automotive parts maker Robert Bosch GmbH of Reutlingen, Germany have agreed to collaborate on silicon carbide (SiC) power semiconductor modules for electric vehicles (EVs) that feature package compatibility...

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

Ceramic resonators and filters occupy a practical middle ground in frequency control and signal conditioning, offering designers cost-effective alternatives to quartz crystals and LC networks. Built on piezoelectric ceramics, these devices provide stable oscillation and selective filtering across a wide range of applications—from timing circuits in consumer electronics to noise suppression in RF designs.

Their appeal lies in balancing performance with simplicity: easy integration, modest accuracy, and reliable operation where ultimate precision is not required.

Getting started with ceramic resonators

Ceramic resonators offer an attractive alternative to quartz crystals for stabilizing oscillation frequencies in many applications. Compared with quartz devices, their ease of mass production, low cost, mechanical ruggedness, and compact size often outweigh the reduced precision in frequency control.

In addition, ceramic resonators are better suited to handle fluctuations in external circuitry or supply voltage. By relying on mechanical resonance, they deliver stable oscillation without adjustment. These characteristics also enable faster rise times and performance that remains independent of drive-level considerations.

Recall that ceramic resonators utilize the mechanical resonance of piezoelectric ceramics. Quartz crystals remain the most familiar resonating devices, while RC and LC circuits are widely used to produce electrical resonance in oscillating circuits. Unlike RC or LC networks, ceramic resonators rely on mechanical resonance, making them largely unaffected by external circuitry or supply-voltage fluctuations.

As a result, highly stable oscillation circuits can be achieved without adjustment. Figure below shows two types of commonly available ceramic resonators.

Figure 1 A mix of common 2-pin and 3-pin ceramic resonators demonstrates their typical package styles. Source: Author

Ceramic resonators are available in both 2-pin and 3-pin versions. The 2-pin type requires external load capacitors for proper oscillation, whereas the 3-pin type incorporates these capacitors internally, simplifying circuit design and reducing component count. Both versions provide stable frequency control, with the choice guided by board space, cost, and design convenience.

Figure 2 Here are the standard circuit symbols for 2-pin and 3-pin ceramic resonators. Source: Author

Getting into basic oscillating circuits, these can generally be grouped into three categories: positive feedback, negative resistance elements, and delay of transfer time or phase. For ceramic resonators, quartz crystal resonators and LC oscillators, positive feedback is the preferred circuit approach.

And the most common oscillator circuit for a ceramic resonator is the Colpitts configuration. Circuit design details vary with the application and the IC employed. Increasingly, oscillation circuits are implemented with digital ICs, often using an inverter gate. A typical practical example (455 kHz) with a CMOS inverter is shown below.

Figure 3 A practical oscillator circuit employing a CMOS inverter and ceramic resonator shows its typical configuration. Source: Author

In the above schematic, IC1A functions as an inverting amplifier for the oscillating circuit, while IC1B shapes the waveform and buffers the output. The feedback resistor R1 provides negative feedback around the inverter, ensuring oscillation starts when power is applied.

If R1 is too large and the input inverter’s insulation resistance is low, oscillation may stop due to loss of loop gain. Excessive R1 can also introduce noise from other circuits, while being too small a value reduces loop gain.

The load capacitors C1 and C2 provide a 180° phase lag. Their values must be chosen carefully based on application, integrated circuit, and frequency. Undervalued capacitors increase loop gain at high frequencies, raising the risk of spurious oscillation. Since oscillation frequency is influenced by loading capacitance, caution is required when tight frequency tolerance is needed.

Note that the damping resistor R2, sometimes omitted, loosens the coupling between the inverter and feedback circuit, reducing the load on the inverter output. It also stabilizes the feedback phase and limits high-frequency gain, helping prevent spurious oscillation.

Having introduced the basics of ceramic resonators (just another surface scratch), we now shift focus to ceramic filters. The deeper fundamentals of resonator operation can be addressed later or explored through further discussion; for now, the emphasis turns to filter applications.

Ceramic filters and their practical applications

A filter is an electrical component designed to pass or block specific frequencies. Filters are classified by their structures and the materials used. A ceramic filter employs piezoelectric ceramics as both an electromechanical transducer and a mechanical resonator, combining electrical and mechanical systems within a single device to achieve its characteristic response.

Like other filters, ceramic filters possess unique traits that distinguish them from alternatives and make them valuable for targeted applications. They are typically realized in bandpass configurations or as duplexers, but not as broadband low-pass or high-pass filters, since ceramic resonators are inherently narrowband.

In practice, ceramic filters are widely used in IF and RF bandpass applications for radio receivers and transmitters. These RF and IF ceramic filters are low-cost, easy to implement, and well-suited for many designs where the precision and performance of a crystal filter are unnecessary.

Figure 4 A mix of ceramic filters presents examples of their available packages. Source: Author

A quick theory talk: A 455-kHz ceramic filter is essentially a bandpass filter with a sharp frequency response centered at 455 kHz. In theory, attenuation at the center frequency is 0 dB, though in practice insertion loss is typically 2–6 dB. As the input frequency shifts away from 455 kHz, attenuation rises steeply.

Depending on the filter grade, the effective passband spans from about 455 kHz ± 2 kHz for narrow designs and up to ±15 kHz for wider types (in theory often cited as ±10 kHz). Signals outside this range are strongly suppressed, with stopband attenuation reaching 40 dB or more at ±100 kHz.

On a related note, ceramic discriminators function by converting frequency variations into voltage signals, which are then processed into audio detection method widely used in FM receivers. FM wave detection is achieved through circuits where the relationship between frequency and output voltage is linear. Common FM detection methods include ratio detection, Foster-Seeley detection, quadrature detection, and differential peak detection.

Now I recall the CDB450C24, a ceramic discriminator designed for FM detection at 450 kHz. Employing piezoelectric ceramics, it provides a stable center frequency and linear frequency-to-voltage conversion, making it well-suited for quadrature detection circuits such as those built with the nostalgic Toshiba TA31136F FM IF detector IC for cordless phones. Compact and cost‑effective, the CDB450C24 exemplifies the role of ceramic discriminators in reliable FM audio detection.

Figure 5 TA31136F IC application circuit shows the practical role of the CDB450C24. Source: Toshiba

As a loosely connected observation, the choice of 450 kHz for ceramic discriminators reflected receiver design practices of the time. AM radios had long standardized on 455 kHz as their intermediate frequency (IF), while FM receivers typically used 10.7 MHz for selectivity.

To achieve cost-effective FM detection, however, many designs employed a secondary IF stage around 450 kHz, where ceramic discriminators could provide stable, narrowband frequency-to-voltage conversion.

This dual-IF approach balanced the high-frequency selectivity of 10.7 MHz with the practical detection capabilities of 450 kHz, making ceramic discriminators like the CDB450C24 a natural fit for FM audio demodulation.

Thus, ceramic filters remain vital for compact, reliable frequency selection, valued for their stability and low cost. Multipole ceramic filters extend this role by combining multiple resonators to sharpen selectivity and steepen attenuation slopes, their real purpose being to separate closely spaced channels and suppress adjacent interference.

Together, they illustrate how ceramic technology continues to balance simplicity with performance across consumer and professional communication systems.

Closing thoughts

Time for a quick pause—but before you step away, consider how ceramic resonators and filters continue to anchor reliable frequency control and signal shaping across modern designs. Their balance of simplicity, cost-effectiveness, and performance makes them a quiet force behind countless applications.

Share your own experiences with these components and keep an eye out for more exploration into the fundamentals that drive today’s electronics.

T. K. Hareendran is a self-taught electronics enthusiast with a strong passion for innovative circuit design and hands-on technology. He develops both experimental and practical electronic projects, documenting and sharing his work to support fellow tinkerers and learners. Beyond the workbench, he dedicates time to technical writing and hardware evaluations to contribute meaningfully to the maker community.

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The post Exploring ceramic resonators and filters appeared first on EDN.

By Andrew Burnett, Interim Chief Technology Officer, Milestone Systems

As we move into 2026, several technology trends that were once mostly confined to research labs and conference keynotes are now stepping into the daily reality of the security industry. What is new today is not the idea of AI itself, but the emergence of Agentic AI – intelligent systems capable of taking autonomous actions across operational workflows. Rather than asking what they might one day do, we are now seeing what they actually do in the field.

In 2026, three technologies will particularly drive this transformation: Agentic AI, Digital Twins and Wearables with Augmented Reality (AR). Each represents an evolution not just in capability, but a step toward fully intelligent, interconnected and immersive security ecosystems.

As India accelerates its adoption of smart city frameworks and digital surveillance infrastructure through national programs like the Smart Cities Mission (https://smartcities.data.gov.in/)and the Digital India initiative (https://www.digitalindia.gov.in/), technologies such as Agentic AI, Digital Twins, and AR-enabled wearables are no longer futuristic concepts—they are becoming essential to the daily functioning of security operations across Indian enterprises, public infrastructure, and government systems.

1. Agentic AI — From Hype-Cycle to Operational Workflows 

Agentic AI, first notable for its capabilities in areas like code generation, is now expanding beyond coding to orchestrate operational workflows across security systems. The shift for 2026 is from capability demonstrations to task-focused agents embedded in operational flows. Rather than one-off proof of concept, we are seeing agents that orchestrate across systems: they ingest video, correlate access logs, detect deviations and then trigger follow-up actions – all without a human translating between disparate interfaces.

According to Indian reports:

1. The AI for Viksit Bharat study states that Financial services companies’ front, middle and back offices are expected to be transformed by machine learning and agentic AI.
2. The Ministry of Electronics & IT, India’s AI Revolution, notes that AI-driven technologies, such as autonomous agents, are helping SMBs scale efficiently, personalise customer experiences, and optimise operations.

Practical examples include autonomous investigation agents that not only take an alarm, gather the last 30 minutes of multimodal evidence (video, access, sensor telemetry), but also propose and initiate immediate mitigation action for an operator to approve. The value is twofold: speed (reducing mean time to insight) and bandwidth (freeing operators to focus on decisions, not data-gathering).

This momentum is mirrored in global investment patterns. According to recent industry projections, Agentic AI is set to dominate IT budget expansion over the next five years, representing more than 26% of worldwide IT spending and surpassing US$1.3 trillion by 2029. This reflects a decisive shift: organisations are no longer experimenting with AI for select projects – they are operationalising it at scale.

Organisations should stop asking “what might agentic AI do” and start identifying the repeatable security workflows they want automated; for example, incident triage, patrol optimisation, evidence packaging; then measure agent performance against those KPIs. The winners in 2026 will be platforms that expose safe, auditable agent APIs and vendors who integrate them into end-to-end operational playbooks.

2. Digital Twins – Moving from Models to Mission-Critical Decisions

Digital twins — the highly sophisticated virtual models that stay synchronised with real-world systems — are also reaching a point of true practicality. The concept is not new. For years, industries like manufacturing and logistics have used digital twins to monitor assets and environments. What’s new is the granularity and scale now possible in security.

According to the Ministry of Communications in India, AI-driven Digital Twins integrate real-time, cross-sectoral data from various sources in a privacy-preserving manner, ensuring a unified and dynamic planning process ensuring integrated planning and fostering a collaborative ecosystem. Digital Twins enable continuous real-time monitoring and predictive analytics. AI enhances data-driven decision-making by simulating multiple scenarios, optimising resource allocation, and improving infrastructure resilience under various conditions.

Organisations such as NVIDIA are utilising digital twins for data centres, integrating cameras, fire alarms, access control and environmental sensors to create a unified, real-time view of operations. Instead of static replicas, we are talking about interactive environments where you can safely test and optimise system behaviour. The value of digital twins goes beyond visualisation and simulation, empowering organisations to monitor, optimise, and actively manage the desired state of multiple subsystems in real-time.

Imagine running a virtual fire-drill scenario that shows pedestrian flow if a corridor is blocked, or simulating lockout strategies to maintain egress while containing a threat. These are not academic exercises — they directly inform SOPs, layout choices and where to place resilient communications or edge compute. For complex estates (airports, ports, multi-tenant high-rises), a unified digital twin reduces configuration drift, accelerates forensic reconstruction and enables predictive maintenance for critical devices.

Looking ahead, the widespread adoption of digital twins is poised to reshape the security industry’s approach to risk management and operational planning. With a unified, real-time view of complex environments, digital twins enable proactive decision-making, allowing security teams to anticipate threats, optimise resource allocation and continuously refine standard operating procedures. Over time, this capability will shift the industry from reactive incident response to predictive and preventative security strategies, where investment in training, infrastructure and technology is guided through simulated outcomes rather than historical events.

3. From Gadgets to Game-Changers: Wearables + AR in Action

AR and wearables have had a turbulent history, but their resurgence in 2026 will be different — and AI is the reason. AI transforms wearables from simple capture devices into intelligent companions. It elevates AR from a visual overlay to a real-time, context-aware guidance layer. They shift frontline tools from passive to proactive devices that see, listen, and interpret the environment, delivering timely insights and support through voice, visual or hybrid interfaces.

Government of India, Ministry of Electronics and Information Technology states: India is now prepping for cutting-edge technologies, including 5G, AI, blockchain, augmented reality & virtual reality, machine learning & deep learning, robots, natural language processing, etc.

The momentum behind AR is also reflected in the market. Globally, the AR sector is projected to surge from US$35.8 billion in 2024 to US$233.3 billion by 2030, a compound annual growth rate of 37%. Today, software and services account for the vast majority of AR revenue, highlighting that enterprises are increasingly leveraging AR for operational applications such as training, remote assistance, simulation and real-time decision support.

Crucially, these systems speak natural language. A guard can ask, “When was this area last patrolled?” and receive concise, evidence-backed answers or ask the system to replay the last suspicious approach and mark it for later review. This moves wearables from passive recorders to active decision-support tools, increasing situational awareness while keeping hands and attention free.

While widespread adoption may still be a few years away, the trajectory is clear. The future of security work will be increasingly wearable – through smart glasses, headsets or other wrist-mounted devices – and powered by conversational, intelligent systems that deliver insights and decision support in real-time.

Conclusion — integrate, simulate, augment

Across these trends, the theme is consistent: AI is the enabler that makes previously hyped technologies operationally useful.

For CISOs, facility heads and operations leaders, the practical playbook for 2026 is simple and strategic: prioritise integration (open, auditable APIs), explore simulation capabilities (digital twins that map to SOPs), and pilot wearable augmentation where it reduces time-to-decision. Success is best measured through operational KPIs — response time, false-positive reduction and decision confidence — rather than novelty.

In simple terms, India’s security landscape is evolving quickly, and technologies like Agentic AI, Digital Twins and AR wearables are moving from early trials to real-world use. With national programmes such as Smart Cities Mission and Digital India accelerating modernisation, security leaders are prioritising AI for faster responses, digital twins for better planning, and wearables for stronger situational awareness on the ground. These tools are no longer experimental—they are becoming central to creating safer, more resilient security operations across the country.

After years of excitement and experimentation, we are entering a new era — one where emerging technology no longer feels like prototypes, but like partners.

We are now firmly in an era where these technologies move from promise to practice.

The post From Hype to Reality: The Three Forces defining Security in 2026 appeared first on ELE Times.

I tested my KY-013 thermistor, which I bought as part of a sensor kit. At first, I thought it was defective, because when I tested it the input always returned 0 bits of resolution. I tested two other sensors from the KY family that came in the same kit, and the same thing happened. Then I had the idea of swapping the ground pin with the signal pin — and boom! It worked. Apparently, in the production of the modules I bought, the signal and ground pins were swapped (that’s what you get when buying from a questionable supplier). The supplier didn’t provide a datasheet for any of the components, nor information about what each one did. So I had to rely on some help from ChatGPT. I managed to identify all the components and created documentation in Notion with images and names so I wouldn’t get lost again. Document your projects, folks. I’m using Notion to centralize information related to real-time systems, electronics, ESP32, and Arduino, mixing all of that into a broader firmware study. I also took the opportunity to test whether the voltage returned by the circuit matched the actual measured voltage. For this, I used my DT-830Y multimeter. The measured value was around 1.51 V, while the value shown on the serial monitor was 1.1 V, which resulted in a considerable error. So I added a correction factor to the voltage calculation. Below is how the function ended up. This correction factor is not precise; I would need to run the project more times to compute a more accurate arithmetic mean. The error is around ±1.5 °C for temperature and about 0.5 V for voltage, which is reasonably low. Now I’m going to stop focusing on the KY-013 and start testing other sensors, creating code bases like this one. If anyone has ideas for portfolio projects using the KY-013, I’m all ears. Conclusions: I won’t buy from questionable suppliers anymore. Is using a correction factor for voltage a hack, or the art of engineering? submitted by /u/Patient-Bill4955 [link] [comments]

“Plus” tacked onto a product name typically translates into a product-generation extension with little (if any) tangible enhancement. Beats has notably bucked that trend.

I’ve decided that I really like transparent devices:

Not only do they look cool (at least in my opinion; yours might differ), since I can see inside them, I’m able to do “pseudo teardowns” without needing to actually take them apart (inevitably destroying them in the process). Therein my interest in the May 2023-unveiled “Plus” spin of Apple subsidiary Beats’ original Studio Buds earbuds, introduced two years earlier:

Frosty beats solid black

As you can see, these are translucent; it’d be a stretch to also call them transparent. Still, I can discern a semblance of what’s inside both the earbuds and their companion storage-and-charging case. And in combination with Beats’ spec-improvement claims:

along with a thorough and otherwise informative teardown video I found of first-gen units:

I think I’ve got a pretty good idea of what’s inside these.

Cool (again, IMHO) looks and an editorial-coverage angle aside, why’d I buy them? After all, I already owned a first-generation Studio Buds set (at left in the following shots, as usual accompanied by a 0.75″ (19.1 mm) diameter U.S. penny for size comparison purposes, and which you’ll also see in other photos in this piece):

Reviewers’ assertions of significant improvements in active noise cancellation (ANC) and battery life with the second-generation version were admittedly tempting:

and like their forebears (and unlike Apple’s own branded earbuds, that is unless you hack’ em), they’re multi-platform compatible versus Apple ecosystem-only, key for this Android guy:

That all said, I confess that what sealed the deal for me was the 10%-off-$84.95 promo price I came across on Woot back in mid-August. Stack that up against the $169.99 MSRP and you can see why I bit on the bait…I actually sprung for two sets, in fact.

An expanded tip suite

Here’s an official unboxing video:

Followed by my own still shots of the process:

Beats added a fourth tip-size option—extra-small—this time around, and the software utility now supports a “fit test” mode to help determine which tip option is optimum for your ears:

Assuring failsafe firmware upgrades

Upon pairing them with my Google Pixel 7 smartphone, I was immediately alerted to an available firmware update:

However, although the earbuds themselves were still nearly fully charged, lengthy time spent in the box (on the shelf at the retailer warehouse) had nearly drained the cells in the case. I needed to recharge the latter before I was allowed to proceed (wise move, Beats!):

With the case (and the buds within it) now fully charged, the update completed successfully:

Battery variability

The first- and second-generation cases differ in weight by 1 gram (48 vs 49), according to my kitchen scale:

With the second-generation earbuds set incrementing the total by another gram (58 vs 60):

In both cases, I suspect, the weight increment is associated with increased battery capacity. The aforementioned teardown video indicates that the cells in the first-generation case have a capacity of 400 mAh (1.52 Wh @ 3.8V). The frosty translucence in the second-generation design almost (but doesn’t quite) enable me to discern the battery cell markings inside:

But Apple conveniently stamped the capacity on the back this time: 600 mAh, matching the 50% increase statistic in Beats’ promotional verbiage:

The “button” cells in the earbuds themselves supposedly have a 16% higher capacity than those in the first-generation predecessors. Given that the originals, again per the teardown video, had the model name M1254S2, translating to a 3.7V operating voltage and 60 mAh capacity, I’m guessing that these are the same-dimension 70-mAh M1254S3 successors.

Microphone upgrades

As for inherent output sound quality, I can discern no difference between the two generations:

A result with which Soundguys’ objective (vs my subjective) analysis concurs:

That said, I can happily confirm that the ability to discern music details in high ambient noise environments, not to mention to conduct discernible phone conversations (at both ends of the connection), is notably enhanced with the second-generation design. Beats claims that all three microphones are 3x larger this time around, a key factor in the improvement. Here (at bottom left in each case) are the first- and second-generation feedforward microphone port pairs:

Along with the ANC feedback mics alongside the two generations’ speaker ports:

The main “call” mics are alongside the touch-control switch in the “button” assembly still exposed when the buds are inserted in the wearer’s ears:

I’m guessing an integrated audio DSP upgrade was also a notable factor in the claimed “up to 1.6x” improved ANC (along with up to 2x enhanced transparency). The first-gen Studio Buds leveraged a Cirrus Logic CS47L66 (along with a MediaTek MT2821A to implement Bluetooth functionality); reader guesses as to what’s in use this time are welcome in the comments!

The outcome of these mic and algorithm upgrades? Over to Soundguys again for the results!

Venting is relieving

The final update is a bit of an enigma, at least to me. Beats has added what it claims are three acoustic vents to the design. Here’s an excerpt from a fuller writeup on the topic:

You’ve probably noticed how some wearables feel more comfortable than others. That’s where acoustic vents come in. They help equalize pressure, reducing that uncomfortable “plugged ear” sensation you might experience with earbuds or other in-ear devices. By doing this, they make your listening experience not only better but also more natural.

The thing is, though, Beats’ own associated image only shows two added vents:

And that’s all I can find, too:

So…

In closing, for your further translucency-blurring visual-inspection purposes, here are some additional standalone images of the right-side earbud, this time standalone and from various positional perspectives:

including another one minus the tip:

and of both the top and bottom of the case:

“Plus” mid-life updates to products are typically little more than new colorway options, or (for smartphones) bigger-sized displays and batteries, but otherwise identical hardware allocations. It’s nice to see Beats do a more substantive “Plus” upgrade with their latest Studio Buds. And the $75-and-change promo price was also very nice. Reader thoughts are as-always welcomed in the comments!

—Brian Dipert is the Principal at Sierra Media and a former technical editor at EDN Magazine, where he still regularly contributes as a freelancer.

Related Content

• Apple’s Beats Powerbeats Pro: a repair attempt blow-by-blow
• Apple’s Beats Powerbeats Pro: No repair…a teardown, though!
• What’s inside: Beats Powerbeats2
• Apple set to acquire Beats headphone producer for $3.2 billion

The post Beats’ Studio Buds Plus: Tangible improvements, not just marketing fluff appeared first on EDN.

I built a compact wireless power bank as a personal project to explore power management, protection, and layout tradeoffs in a small enclosure. The system is based on a single-cell Li-Po with a dedicated PCM for overcurrent/overvoltage protection, a USB-C charging module for fast recharge, and a boost converter to supply the wireless charging module. A physical slide switch fully isolates the boost and wireless charger when off, so there’s no standby drain from the battery. One of the main challenges was balancing size, thermal behavior, and efficiency. Wireless charging is obviously less efficient than wired, and this version does get warm under higher load, so the focus here was more on validating the architecture and enclosure layout rather than optimizing efficiency. Thermal and efficiency improvements would be a priority in a future revision. The enclosure is sized tightly around the electronics and uses a transparent lid mainly for inspection and layout verification during use. I documented the full wiring and build process in an Instructables write-up for anyone interested in the details: https://www.instructables.com/LucidCharge-a-Slim-Transparent-Wireless-Power-Bank/ Happy to hear thoughts or suggestions on power architecture, thermal handling, or protection choices. submitted by /u/Mammoth-Grade-7629 [link] [comments]

У КПІ ім. Ігоря Сікорського відкрилася інноваційна AI-лабораторія — DRL AI Space kpi пн, 12/22/2025 - 14:37

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

ams OSRAM GmbH of Premstaetten, Austria, and Munich, Germany has launched a convertible bond tender and invites current bondholders to submit offers to sell up to €300m in principal amount of the outstanding €760m convertible bonds due 2027...

India is slowly gaining ground as an important electronics exporter to the world. With electronics exports reaching $31 billion in eight months of this financial year and Apple alone exporting iPhones worth nearly $14 billion, more than 45 per cent of the total exports value of electronic items, the future for the electronics industry looks bright despite the harsh market conditions amid geopolitical tensions.

Last month itself, Apple India’s company filing posted a record high domestic sale of $9 billion in FY25, with one in every five iPhones made globally during FY25 being manufactured/assembled in India. The company’s manufacturing in India contributed 12 per cent of Apple’s global production value.

India had only two mobile phone manufacturing units in 2014-15, which has now increased to around 300 units. Mobile phone production has grown from Rs 18,000 crore to Rs 5.45 lakh crore, while exports have surged from Rs 1,500 crore to nearly Rs 2 lakh crore.

Electronics production has increased sharply from about Rs 1.9 lakh crore in 2014-15 to around Rs 11.3 lakh crore in 2024–25. Electronics exports have also risen from Rs 38,000 crore to more than Rs 3.27 lakh crore during the same period, as per the government data.

Meanwhile, the Modified Electronics Manufacturing Clusters (EMC 2.0), located in 10 states with projected investments of Rs 1,46,846 crore, are estimated to generate about 1.80 lakh jobs.

Union Minister of State for Electronics and IT Jitin Prasada said in a written reply to a question in Lok Sabha this week that so far, 11 EMC and 2 CFC (common facility centre) projects have been approved. These cover an area of 4,399.68 acres with a project cost of Rs 5,226.49 crore, including Central financial assistance of Rs 2,492.74 crore, the minister informed.

An investment commitment of Rs 1,13,000 crore has already been received from 123 land allottees (manufacturers) in the approved EMCs. Out of this, nine units have started production and grounded an investment of Rs 12,569.69 crore with employment generation of 13,680 jobs, said the minister.

The post Indian Electronic Exports Gain Momentum Globally appeared first on ELE Times.

Milestone Systems released an advanced vision language model (VLM) specialising in traffic understanding and powered by NVIDIA Cosmos Reason. The VLM powers two new products: a Video Summarisation tool for XProtect Video Management Software and a VLM as a Service for third-party integrations.

Video Summarisation for XProtect allows users to search summaries from visual data and automates reporting.

Today’s video systems capture vast amounts of data, and reviewing footage remains time-consuming and largely manual. With Milestone Systems’ new Video Summarisation tool – a generative AI-powered plug-in for the XProtect Smart Client – users and operators can now rely on a specialised product that automates operator workflows, saves valuable time, and reduces false alarm fatigue significantly. ​Early reports show video summarisation could reduce operator false alarm fatigue by up to 30%.

The Video Summarisation tool analyses camera footage and describes what’s happening. Users simply send a snippet of video and a prompt describing their request, and the model will generate a text summary in seconds. ​

Key capabilities:

• Convert video segments into structured text summaries inside XProtect Smart Client​
• Search summaries based on video content, rather than timestamps or manual tagging​
• Bookmark and filter summaries to streamline review workflows​
• Integrate seamlessly with existing XProtect event and rule logic to trigger automated summaries based on specific alarms or alerts
• Focus attention on valid events​ by filtering out irrelevant motion or noise
• Access customised, sovereign VLMs per region, starting with the US and EU. More regions to follow.

The Video Summarisation is free to download and takes only a few minutes to install directly in the XProtect Smart Client. And users only pay when prompted by the VLM.

VLM as a Service for developers: Add production-ready video intelligence to any application

With Milestone’s Hafnia VLM as a Service (VLMaaS), developers, integrators and partners get API access to production-ready video intelligence built on NVIDIA’s latest technology and fine-tuned on responsibly sourced data.

The VLMaaS helps developers create AI-powered solutions quickly without needing to set up, fine-tune or manage their own AI systems – it enhances any existing solutions with generative AI, regardless of the level of analytics currently in place. This makes it fast and simple to add advanced video intelligence features to applications, whether it’s testing a minimum viable product (MVP) or scaling a platform.

With VLMaaS, the development of AI and analytics can be accelerated significantly – up to 70 times less effort than doing the work to fine-tune a VLM model to do the same.

Key capabilities:

• Access a high-accuracy vision language model, fine-tune on traffic-optimised data and build on NVIDIA Cosmos Reason
• Follow prompt-based instructions for traffic-related operations
• API-first delivery – simple integration via HTTPS​
• Fine-tuned models for the US and EU markets, with more regions to follow​
• Designed to build standalone solutions or integrate with the Milestone product portfolio
• 100% responsibly sourced training data with auditable data lineage, GDPR- and EU AI Act-compliant, used for the fine-tuning of the model

Pricing for the VLMaaS is pay-per-use (based on API calls) – no large upfront investments or custom training costs.

Andrew Burnett, Acting Chief Technology Officer, Milestone Systems, said:
“With the Vision Language Model as a Service and Video Summarisation for XProtect, we’re tackling some of the most challenging bottlenecks: video overload and time-consuming manual work. Operators get immediate insight directly within XProtect; builders get API‑first access to production‑ready intelligence without bespoke training or heavy infrastructure.

Because this model is specialised for real-world traffic video and fine-tuned on responsibly sourced data, customers can trust the results, deploy with confidence, and enhance all existing solutions in place. It’s the fastest, most advanced and impactful path to turning video into actionable outcomes.”

XProtect customers like the cities of Genoa, Italy, and Dubuque, Iowa, US, are excited to use these new capabilities, leading the way in adopting advanced video intelligence solutions to enhance traffic management.

Built on responsible AI, Powered by Real-World Data

The two new offerings are powered by Milestone’s Hafnia VLM, which has been fine-tuned on 75,000 hours of responsibly sourced, real-world video data from either Europe or the US, using NVIDIA Cosmos Curator for data preparation and running either on cloud infrastructure or regional data centres. Leveraging NVIDIA Cosmos Reason VLM and Milestone’s data for fine-tuning makes it one of the most advanced video AI platforms in the industry.

The post Milestone Launches Vision Language Model (VLM) appeared first on ELE Times.