low power News - Page 19 of 35 - CNX Software

April 4, 2022April 4, 2022 by Jean-Luc Aufranc (CNXSoft) - 5 Comments

Morse Micro MM6104, MM6108 Wi-Fi HaLow SoCs support up to 32.5 Mbps data rate

Australian company Morse Micro MM6104 and MM6108 Wi-Fi HaLow SoCs should offer some competition to the Newracom NRC chips found in all 802.11ah WiFi HaLow boards and devices released so far. Both MM610x chips have similar features, but the MM6104 SoC supports 1/2/4 MHz channel bandwidth for up to 15 Mbps data rate – just like the Newracom NRC7292 chip – while the more powerful MM6108 can handle a data rate of up to 32.5 Mbps thanks to 1/2/4/8 MHz channel bandwidth. MM6104/MM6108 specifications: Optional 32-bit RISC-V Host Applications Processor (HAP) Single-Chip IEEE802.11ah Wi-Fi HaLow transceiver for low-power, long-reach IoT applications Worldwide Sub-1 GHz frequency bands (850MHz to 950MHz) On-chip power amplifier with support for external PA option MM6104 – 1/2/4 MHz channel bandwidth for up to 15 Mbps data rate (Note: the datasheet reads “single-stream max data rate up to 40 Mbps”, but it appears to be a mistake […]

March 21, 2022March 21, 2022 by Sponsored Post - 3 Comments

Ai-Thinker Ra-08 LoRaWAN module features ASR6601 chip (Sponsored)

Ai-Thinker Ra-08/08H are new LoRaWAN modules based on ASR Microelectronics ASR6601 module featuring a 48MHz ARM Cortex M4 microcontroller and Semtech SX1262 transceiver allowing long-range, low power communication for the Internet of Things. Both LoRaWAN modules share most of the same specifications, but the Ra-08 module operates in the 410-525MHz frequency band, while the Ra-08H module works in the widely used 803MHz to 930MHz band. Ai-Thinker also provides a development kit for each module. Ai-Thinker Ra-08/Rs-08H key features and specifications: Programmable embedded Arm Cortex-M4 MCU with 128 KB of Flash and 16 KB of SRAM LoRa radio Sensitivity – -138 dBm @ SF12/125KHz Tx power – Up to +22dBm Frequencies Ra-08 – 410 MHz to 525 MHz Ra-07H – 803 MHz to 930 MHz Spread spectrum factor – SF5, SF6, SF7, SF8, SF9, SF10, SF11, SF12 LoRa, (G)FSK, BPSK, and (G)MSK modulation Bit rate up to 62.5 Kbps in LoRa […]

March 3, 2022March 3, 2022 by Jean-Luc Aufranc (CNXSoft) - 6 Comments

Ultra-low power printed flexible E-paper displays work with Arduino

Ultra-low-power flexible e-paper display

Ynvisible Interactive will soon release upgrades to their printed flexible E-paper displays that consume 50% less energy per switch and can last 10 longer when switched on and off, with the company claiming to offer the lowest energy-consuming displays in the e-paper industry. Those displays are mostly used in specific industries such as digital signage, smart monitoring labels, authenticity & security, and retail. While we have very little information about the new upgrades, I’ve noticed the company is offering a development kit with several “ultra-low-power, thin and flexible Segment E-Paper Displays”, so let’s have a look. Here are some of the specifications of the displays part of the kit: White Reflectance – 40% Contrast Ratio (Yb/Yd) – 1:3 Angle Dependency – No, lambertian Thickness – 300 μm (0.3 mm) Graphical layout – Segments with 1mm to 100mm dimensions Response time – 100-1000 ms Driving voltage – 1.5 V (direct drive) […]

February 24, 2022 by Jean-Luc Aufranc (CNXSoft) - 5 Comments

Intel launches Alder Lake P-Series and U-Series mobile hybrid processors

Intel-Alder Lake P-Series and U-Series block diagram

Intel first unveiled the most powerful Alder Lake H-Series last year before the launch in January, and also introduced Alder Lake-S desktop IoT processors and Alder Lake U-Series and P-Series mobile IoT SoCs in early January. But now the company has announced the launch of the Alder Lake P-Series (28W) and U-Series (9W and 15 PBP) 12th generation mobile processors designed for “thin-and-light” laptops which should become available around March 2022. The block diagram of the 28W P-Series and 15W U-Series (source: product brief from Intel) shows both offer the same interfaces including eDP 1.4b, HDMI 2.0b, 2x PCIe Gen4, 12x PCIe Gen3, 2x SATA… and the same 50x25x12mm BGA package. But the 9W U-Series comes in a cost-optimized 28.5x19x11mm BGA package that does without SATA interfaces, a lower number of PCIe Gen3 interfaces (10 vs 12), USB 2.0 interfaces (6 vs 10), Thunderbolt 4 interfaces (2 vs 4), and […]

February 18, 2022February 18, 2022 by Jean-Luc Aufranc (CNXSoft) - 5 Comments

Silicon Witchery S1 module combines nRF52811 Bluetooth SoC with Lattice iCE40 FPGA

Sweden-based Silicon Witchery S1 is a tiny module combining Nordic Semi nRF52811 Bluetooth LE SoC with Lattice Semi iCE40 FPGA designed for battery-powered applications leveraging DSP and machine learning (ML) at the edge. The S1 module features just four key components in a tiny 11.5 x 6 mm form factor and targets applications requiring “demanding” algorithms while consuming as little energy as possible. Silicon Witchery S1 module specifications: MCU – Nordic Semi nRF52811 Arm Cortex-M4 MCU @ 64 MHz with Bluetooth 5.2 support including Long Range, Thread support. FPGA – Lattice Semi iCE40 FPGA with 5k LUT and DSP blocks. Storage – 32 Mbit flash storage. Integrated antenna, passives, and crystals. I/Os – 20x castellated holes with 8x FPGA IO include I3C, I2C, SPI, and USB. 2x nRF GPIO pins with ADC and low power wake. SWD pins for debugging Power Supply Lithium battery charging and monitoring. 3x adjustable Vout […]

February 9, 2022August 24, 2022 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

MIPI CSI-2 v4.0 adds features for always-on, low power machine vision applications

While MIPI CSI-2 standard was first introduced in 2005 as a high-speed protocol for the transmission of still and video images from image sensors to application processors, the standard has evolved over the years, and the latest MIPI CSI-2 v4.0 introduces features to better support always-on, low power machine vision applications, high-resolution sensors, and high-dynamic-range automotive image sensors. The main changes for v4.0 include support for a two-wire interface (MIPI I3C) to lower cost and complexity, multi-pixel compression for the latest generation of advanced image sensors, and RAW28 color depth for better image quality and an improved signal-to-noise (SNR) ratio. MIPI CSI-2 v4.0 highlights: Always-On Sentinel Conduit (AOSC) – Enables always-on machine vision systems with ultra-low-power image sensors and video signal processors (VSPs) continuously monitoring their surrounding environments and having the ability to wake up their more powerful host CPUs when specific events happen. Some use cases include laptop/tablet-based face […]

January 24, 2022January 25, 2022 by Jean-Luc Aufranc (CNXSoft) - 6 Comments

Silicon Labs BG24 and MG24 2.4 GHz wireless MCU’s quadruple AI performance at a fraction of the energy

Machine Learning is getting everywhere including into 2.4GHz wireless microcontrollers with SIlicon Labds BG24 Bluetooth and MG24 multi-protocol Cortex-M33 microcontrollers that improve AI/ML performance by 4 times using 1/6th of the energy thanks to a built-in AI accelerator. That makes the new microcontrollers suitable for battery-powered edge AI devices with support for Matter (coming soon) as well as PSA Level 3 Secure Vault protection. Silicon Labs expects the chips to be found in various smart home, medical and industrial applications. BG24 and MG24 share the same block diagram and the same specifications apart from the supported wireless protocols: MCU core – Arm Cortex-M33 @ 78.0 MHz with DSP instruction and floating-point unit Memory – Up to 256 kB RAM data memory Storage – Up to 1536 kB flash program memory Wireless CPU – Arm Cortex-M0+ 2.4 GHz Radio Performance -104.5 dBm sensitivity @ 250 kbps O-QPSK DSSS -104.9 dBm sensitivity […]

January 21, 2022February 25, 2024 by Jean-Luc Aufranc (CNXSoft) - No Comments

$499 BrainChip AKD1000 PCIe board enables AI inference and training at the edge

BrainChip has announced the availability of the Akida AKD1000 (mini) PCIe boards based on the company’s neuromorphic processor of the same name and relying on spiking neural networks (SNN) which to deliver real-time inference in a way that is much more efficient than “traditional” AI chips based on CNN (convolutional neural network) technology. The mini PCIe card was previously found in development kits based on Raspberry Pi or an Intel (x86) mini PC to let partners, large enterprises, and OEMs evaluate the Akida AKD1000 chip. The news is today is simply that the card can easily be purchased in single units or quantities for integration into third-party products. BrainChip AKD1000 PCIe card specifications: AI accelerator – Akida AKD1000 with Arm Cortex-M4 real-time core @ 300MHz System Memory – 256Mbit x 16 bytes LPDDR4 SDRAM @ 2400MT/s Storage – Quad SPI 128Mb NOR flash @ 12.5MHz Host interface – 5GT/s PCI […]