Elecrow develops and manufactures electronics products for the maker market, and in recent years entered the STEM education market with products such as CrowPi2 Raspberry Pi 4 education laptop that I reviewed last year. The laptop integrates plenty of electronics modules, and students can learn Scratch visual programming as well as Python programming with the educational software running on the laptop. The company has now launched Crowbits magnetic electronic blocks for STEM education, and compatible with Arduino, ESP32, Raspberry Pi, and Micro:bit boards. There are over 80 programmable electronic magnetic modules and Lego bricks, with three different sizes ( large, middle, and small modules) of different colors with blue used for power control and logic control, green for output, yellow for input, and orange for advanced programming. Out of the 80+ modules, around 30 can be used without programming at all. Elecrow provides 5 kits to let users learn basic electronics and programming knowledge, namely the Hello Kit designed for […]
The BBC Doctor Who HiFive Inventor Coding Kit was announced at the end of November 2020 with the goal of teaching IoT to young kids. But one day, I noticed the postman left a package on the ground right next to my house’s gate for some reason. I had no idea what it could be until I read it was from SiFive on the package. So here I am about to review BBC Doctor Who HiFive Inventor Coding Kit! The package actually included two small packages with one being an “expansion board”… HiFive Inventor Coding Kit Unboxing We’ve already written about the specs in the announcement post, but here they are again for those who forgot it’s based on SiFive FE310 RISC-V microcontroller and ESP32 for WiFi and Bluetooth. Let’s open the thinner “expansion board” package first. It’s actually the HiFive Inventor board – aka the mainboard – that comes with a getting started guide as well as a USB-C […]
In what should be one of the first RISC-V education platforms, the BBC, Tynker, and SiFive have just announced the BBC Doctor Who “HiFive Inventor” Coding Kit that comes with an MCU board with WiFi & Bluetooth and guided lessons for kids that teach them to code for the IoT. The HiFive Inventor board is based on a SiFive FE310 RISC-V microcontroller ( the same chip as found in the HiFive1 board) and an ESP32 Solo module for WiFi 4 and Bluetooth 4.x/5.x connectivity. Just like the BBC Micro:bit, HiFive Inventor provides a kids-friendly edge connector with I/O, an LED matrix, sensors, and more. The kit includes the HiFive Inventor hardware platform, a battery holder for three AA batteries (not included), the HiFive Speakers, an illuminated USB cable for power and programming, and alligator clips to connect the speaker or other add-ons to the HiFive Inventor board. HiFive Inventor board looks to be based on the earlier SiFive Learn Inventor, […]
The original BBC micro:bit educational board was launched in July 2015 with a Nordic nRF51822 Arm Cortex-M0 MCU @ 16 MHz providing Bluetooth LE connectivity, a few I/Os, some buttons, and a LED matrix acting as a small display. The British company has now launched a new update with BBC micro:bit v2 with the same form factor, but equipped with a more powerful Nordic Semi nRF52833 Bluetooth 5.1 Arm Cortex-M4 MCU clocked at 64 MHz and adding a microphone and a speaker. BBC micro:bit v2 specifications: Wireless MCU – Nordic Semi nRF52833 Arm Cortex-M4 MCU clocked at 64 MHz with 128 KB RAM, 512 KB flash, Bluetooth 5.1 LE connectivity “Display” – 25x red LED indicator lights in a 5×5 matrix USB – 1x micro USB port for power and programming via NXP Kinetis KL27Z Cortex-M0+ microcontroller Audio – Built-in MEMS microphone and speaker Expansion 25 pins on edge connector with 4 dedicated GPIO, PWM, I2C, SPI etc… 5x rings […]
At first glance, Kittenbot Meowbit gaming console looks like a kid’s toy, but it’s bit more than that as its STM32 MCU can be programmed with MakeCode arcade, Scratch3.0 based Kittenblock, or MicroPython, and features the same edge connector as found in BBC Micro:bit board, and as such is compatible with several Micro:bit accessories. Kittenbot Meowbit specifications: MCU – STMicro STM32F401RET6 Arm Cortex M4 micro-controller Storage 2MB SPI flash to store Unicode character table (default) SD card slot to store programs or extend wireless modules Display – 160 x 128 full-color TFT LCD Sensor – Light sensor, temperature sensor, MP6050 gyroscope USB – 1x micro USB port for power and programming Expansion – 40-pin BBC Micro:bit “goldfinger” connector Misc – Charging/work LED, 2x user LED, power switch, reset button, DFU mode button, 4x direction buttons, A/B buttons, buzzer, multiplayer connector (15) Power Supply – 5V via USB, or 3.7~4.2V via a Lithium battery pack; output current: 500mA (max); operating voltage: […]
So today, I decided to have a look a 96Boards website to see if there was anything new from the community, and I came accross “X in a Box B901“, an “☒CHIP is designed to interface with the 96 Boards, such as the Dragonboard 410c. This provides an interface to support the ☒CHIP ecosystem, adding support for many additional sensors etc…” I had no idea what it was all about, so obviously I had to investigate. Xinabox (X in a Box) is an ecosystem of modular electronics boards used for developing, making products and learning. There are now over 70 modular xChip” with cores/CPUs, sensors, power, communication, output, and storage. They are interconnected together without wires, soldering, breadboards, and adapters are provided for Raspberry Pi, 96Boards, and other development boards. xChips can be sorted into 8 categories: Cores – MCU/CPI cores based on Microchip ATMega328P, SAMD21, ESP8266, or ESP32 with or without a LoRa radio Bridges – Used to connect […]
Machine learning used to be executed in the cloud, then the inference part moved to the edge, and we’ve even seen micro-controllers able to do image recognition with GAP8 RISC-V micro-controller. But I’ve recently come across a white paper entitled “Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things” that shows how it’s possible to perform such tasks with very little resources. Here’s the abstract: This paper develops a novel tree-based algorithm, called Bonsai, for efficient prediction on IoT devices – such as those based on the Arduino Uno board having an 8 bit ATmega328P microcontroller operating at 16 MHz with no native floating point support, 2 KB RAM and 32 KB read-only flash. Bonsai maintains prediction accuracy while minimizing model size and prediction costs by: (a) developing a tree model which learns a single, shallow, sparse tree with powerful nodes; (b) sparsely projecting all data into a low-dimensional space in which the tree is learnt; and […]
We’ve already covered plenty of LoRa boards or solutions designed for nodes or gateways such as TTGO T-Beam ESP32 + LoRa board, RAK Wireless RAK811 GPS Lora tracker board, MatchX Matchbox LoRa gateway, and many others,, but Pi Supply offers yet more options with LoRa node and gateway add-on boards designed to work with Raspberry Pi, Arduino, and BBC Micro:bit boards. Pi Supply LoRa Gateway HAT for Raspberry Pi The IoT LoRa Gateway HAT is based on RAK Wireless RAK833 mPCIe LoRa gateway concentrator module and connects to Raspberry Pi 3 B/B+ board via the 40-pin header. There are two hardware version using 868 MHz or 915 MHz frequencies, but as we’ve seen in previous reviews those are configurable for other frequencies such as AS923 or IN865. Pi Supply IoT LoRa Node pHAT for Raspberry Pi LoRa Node pHAT is designed for node specifically, and with a smaller form factor making it suitable not only for Raspberry Pi 3 boards, […]
Privacy & Cookies Policy
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.