tinyml

Posted on by Jean-Luc Aufranc (CNXSoft) - 2 Comments on Particle launches Photon 2 Realtek RTL8721DM dual-band WiFi and BLE IoT board, Particle P2 module

Particle launches Photon 2 Realtek RTL8721DM dual-band WiFi and BLE IoT board, Particle P2 module

Particle Photon 2

Particle has launched the Photon 2 dual-band WiFi and BLE IoT board powered by a 200 MHz Realtek RTL8721DM Arm Cortex-M33 microcontroller, as well as the corresponding Particle P2 module for integration into commercial products. The original “Spark Photon” WiFi IoT board was launched in 2014 with an STM32 MCU and a BCM43362 wireless module, but the market and company name have changed since then, and Particle has now launched the Photon 2 board and P2 module with a more modern Cortex-M33 WiFi & BLE microcontroller with support for security features such as Arm TrustZone. Particle Photon 2 specifications: Wireless MCU – Realtek RTL8721DM CPU – Arm Cortex-M33 core @ 200 MHz Memory – 4.5MB embedded SRAM of which 3072 KB (3 MB) is available to user applications Connectivity – Dual-band WiFi 4 up to 150Mbps and Bluetooth 5.0 Security Hardware Engine Arm Trustzone-M Secure Boot SWD Protection Wi-Fi WEP, […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 5 Comments on Lolin S3 Mini – Tiny $5 ESP32-S3 board follows Wemos D1 Mini form factor

Lolin S3 Mini – Tiny $5 ESP32-S3 board follows Wemos D1 Mini form factor

LOLIN S3 Mini

LOLIN S3 Mini is a tiny ESP32-S3 WiFi and Bluetooth IoT development board that follows the Wemos D1 Mini form factor and supports its equally tiny stackable shields to add relays, displays, sensors, and so on. Wemos/LOLIN introduced their first ESP32-S3 board last year with the LOLIN S3 board with plenty of I/Os and an affordable $7 price tag.  But I prefer the company’s Mini form factor because of its size and the ability to select add-on boards to easily add a range of features to your projects. So I’m pleased to find out the company has now launched the LOLIN S3 Mini following the ESP32-C3 powered LOLIN C3 Mini board unveiled in March 2022. LOLIN S3 Mini specifications: WiSoC – Espressif Systems ESP32-S3FH4R2 CPU – dual-core Tensilica LX7 @ up to 240 MHz with vector instructions for AI acceleration Memory – 512KB RAM, 2MB PSRAM Storage – 4MB QSPI […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 1 Comment on Sony IMX500-based smart camera works with AITRIOS software

Sony IMX500-based smart camera works with AITRIOS software

LUCID SENSAiZ SZP123S AITRIOS camera

Raspberry Pi recently received a strategic investment from Sony (Semiconductor Solutions Corporation) in order to provide a development platform for the company’s edge AI devices leveraging the AITRIOS platform. We don’t have many details about the upcoming Raspberry Pi / Sony device, so instead, I decided to look into the AITRIOS platform, and currently, there’s a single hardware platform, LUCID Vision Labs SENSAiZ SZP123S-001 smart camera based on Sony IMX500 intelligent vision sensor, designed to work with Sony AITRIOS software. LUCID SENSAiZ Smart camera SENSAiZ SZP123S-001 specifications: Imaging  sensor – 12.33MP Sony IMX500 progressive scan CMOS sensor with rolling shutter, built-in DSP and dedicated on-chip SRAM to enable high-speed edge AI processing. Focal Length  – 4.35 mm Camera Sensor Format – 1/2.3″ Pixels (H x V) – 4,056 x 3,040 Pixel Size, H x V – 1.55 x 1.55 μm Networking – 10/100M RJ45 port Power Supply – PoE+ via […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 1 Comment on Aspinity AB2 AML100 Arduino Shield supports ultra-low-power analog machine learning

Aspinity AB2 AML100 Arduino Shield supports ultra-low-power analog machine learning

Aspinity AB2 AML100 analog machine learning Arduino Shield

Aspinity AB2 AML100 is an Arduino Shield based on the company’s AML100 analog machine learning processor that reduces power consumption by 95 percent compared to equivalent digital ML processors, and the shield works with Renesas Quick-Connect IoT platform or other development platforms with Arduino Uno Rev3 headers. The AML100 analog machine learning processor is said to consume just 15µA for sensor interfacing, signal processing, and decision-making and operates completely within the analog domain offloading most of the work from the microcontroller side that can stay its lowest power state until an event/anomaly is detected. Aspinity AB2 AML100 Arduino Shield specifications: ML chip – Aspinity AML100 analog machine learning chip Software programmable analogML core with an array of configurable analog blocks (CABs) with non-volatile memory and analog signal processing Processes natively analog data Near-zero power for inference and events detection Consumes <20µA when always-sensing Reduces analog data by 100x Supports up […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 2 Comments on Arduino Nano 33 BLE Sense Rev2 switches to BMI270 & BMM150 IMUs, HS3003 temperature & humidity sensor

Arduino Nano 33 BLE Sense Rev2 switches to BMI270 & BMM150 IMUs, HS3003 temperature & humidity sensor

Arduino Nano 33 BLE Sense Rev2

Arduino Nano 33 BLE Sense Rev2 is a new revision of the Nano 33 BLE Sense machine learning board with basically the same functionality but some sensors have changed along with some other modifications “to improve the experience of the users”. The main changes are that STMicro LSM9DS1 9-axis IMU has been replaced by two IMUs from Bosch SensorTech, namely the BMI270 6-axis accelerometer and gyroscope, and the BMM150 3-axis magnetometer, a Renesas HS3003 temperature & humidity sensor has taken the place of an STMicro HTS221, and the microphone is now an MP34DT06JTR from STMicro instead of an MP34DT05. All of the replaced parts are from STMicro, so it’s quite possible the second revision of the board was mostly to address supply issues. Arduino Nano 33 BLE Sense Rev2 (ABX00069) specifications: Wireless Module – U-blox NINA-B306 module powered by a Nordic Semi nRF52840 Arm Cortex-M4F microcontroller @ 64MHz with 1MB […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 6 Comments on Arduino Nicla Voice enables always-on speech recognition with Syntiant NDP120 “Neural Decision Processor”

Arduino Nicla Voice enables always-on speech recognition with Syntiant NDP120 “Neural Decision Processor”

Arduino PRO Nicla Voice with LiPo battery

Nicla Voice is the latest board from the Arduino PRO family with support for always-on speech recognition thanks to the Syntiant NDP120 “Neural Decision Processor” with a neural network accelerator, a HiFi 3 audio DSP, and a Cortex-M0+ microcontroller core, and the board also includes a Nordic Semi nRF52832 MCU for Bluetooth LE connectivity. Arduino previously launched the Nicla Sense with Bosch SensorTech’s motion and environmental sensors, followed by the Nicla Vision for machine vision applications, and now the company is adding audio and voice support for TinyML and IoT applications with the Nicla Voice. Nicla Voice specifications: Microprocessor – Syntiant NDP120 Neural Decision Processor (NDP) with one Syntiant Core 2 ultra-low-power deep neural network inference engine, 1x HiFi 3 Audio DSP, 1x Arm Cortex-M0 core up to 48 MHz, 48KB SRAM Wireless MCU – Nordic Semiconductor nRF52832 Arm Cortex-M4 microcontroller @ 64 MHz with 512KB Flash, 64KB RAM, Bluetooth […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 6 Comments on ArduCam Mega – A 3MP or 5MP SPI camera for microcontrollers (Crowdfunding)

ArduCam Mega – A 3MP or 5MP SPI camera for microcontrollers (Crowdfunding)

Arducam Mega SPI camera

ArduCam Mega is a 3MP or 5MP camera specifically designed for microcontrollers with an SPI interface, and the SDK currently supports Arduino UNO and Mega2560 boards, ESP32/ESP8266 boards, Raspberry Pi Pico and other boards based on RP2040 MCU, BBC Micro:bit V2, as well as STM32 and MSP430 platform. Both cameras share many of the same specifications including their size, but the 3MP model is a fixed-focus camera, while the 5MP variant supports autofocus. Potential applications include assets monitoring, wildfire monitoring, remote meter reading, TinyML applications, and so on. ArduCam Mega specifications: Camera Type 3MP with fixed focus 5MP with auto-focus from 8cm to infinity Optical size – 1/4-inch Shutter type – Rolling Focal ratio 3MP – F2.8 5MP – F2.0 Still Resolutions 320×240, 640×480, 1280×720 x 1600 x1200x 1920 x 1080 3MP – 2048 x 1536 5MP – 2592×1944 Output formats – RGB, YUV, or JPEG Wake-up time 3MP – […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 6 Comments on Bee Motion S3 – An ESP32-S3 board with a PIR motion sensor (Crowdfunding)

Bee Motion S3 – An ESP32-S3 board with a PIR motion sensor (Crowdfunding)

ESP32 S3 board PIR Motion Sensor

The Bee Motion S3 is an ESP32-S3 WiFi and Bluetooth IoT board with a PIR motion sensor beside the more usual I/Os, Qwiic connector, USB-C port, and LiPo battery support. It is at least the third PIR motion wireless board from Smart Bee Designs, as the company previously introduced the ESP32-S2 powered Bee Motion board and the ultra-small Bee Motion Mini with an ESP32-C3 SoC. The new Bee Motion S3 adds a few more I/Os, a light sensor, and the ESP32-S3’s AI vector extensions could potentially be used for faster and/or lower-power TinyML processing. Bee Motion S3 specifications: Wireless module – Espressif Systems ESP32-S3-MINI-1 module (PDF datasheet) based on ESP32-S3 dual-core Xtensa LX7 microcontroller with 512KB SRAM, 384KB ROM, WiFi 4 and Bluetooth 5.0 connectivity, and equipped with 8MB of QSPI flash and a PCB antenna USB – 1x USB Type-C port for power and programming Sensors PIR sensor S16-L221D […]

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