Piper Make: First Drag-and-Drop Coding Platform for Raspberry Pi Pico

Piper Make Raspberry Pi Pico

In 2019 we saw Piper’s Computer Kit 2, which was a DIY Raspberry Pi 3 Computer for educational purposes. The kit was for kids to educate them on building their own computers and the basics of programming in electronics. This year the company has come up with another educational platform. Meet Piper Make. The newly launched Raspberry Pi Pico is capable of a wide range of applications but directly working on the development board for exploring these applications could be difficult for beginners. Additionally, prototyping a project or an application before implementing it is an ideal way for starting. Hence. Piper has launched its first drag-and-drop coding platform for the Raspberry Pi Pico which allows hands-on prototyping for the users. Piper Make platform has an interface that supports Chromebooks and other computers, thus making it flexible for users. It is free for users to explore hands-on with the Raspberry Pi […]

Machine Learning on Raspberry Pi Pico, RP2040, and future RPi MCUs

RP2040 Boards Feature Image

Although the Raspberry Pi Pico comes with the RP2040 chip that lacks the performance to implement machine learning inference for its applications. However, we saw a person detection use case through ArduCAM and TensorFlow lite interface. But, the processing performance of the use case was on the slower side. Additionally, a recent Eben Upton presentation also unveiled that due to low power requirements the board compensates the processing efficiency. Hence, it offers low-performance for edge inference and machine learning use cases. Eben Upton’s teaser on improvement in machine learning and the future scope of “Pi Silicon” revealed potential growth and development in edge inference applications. The demand for RP2040 boards has given rise to the market necessity for more boards. This demand can only be fulfilled if more boards with RP2040 chip are available in the market and company “partners such as Adafruit, Pimoroni, Adafruit and Sparkfun are start releasing […]

QuickLogic’s Hearable Reference Design enables Alexa Voice-Initiated Devices

Working with QuickLogic's Smart Hearable Reference Design

Last year we saw QuickFeather board featuring EOS S3 Cortex-M4F MCU with embedded FPGA, which was a crowdfunding project. This year the company has launched its smart hearable reference design based on a similar processor by QuickLogic. The device is dedicated to “Voice-Initiated, Hands-Free, Alexa Built-In Devices with Close-Talk Support.” QuickLogic’s smart hearable reference design is based on the company’s Open Reconfigurable Computing (QORC) which supports a complete open-source set of development options for the MCU and FPGA devices. It is also built on the EOS S3 Voice Processor and the QuickFeather open source development kit. This can enhance the user experience with a longer battery life of the device. The EOS S3 Arm Cortex- M4 processor features Low Power Sound Detection (LPSD) technology along with DSP Concepts’ TalkTo noise suppression and beamforming technology for the directional transmission of signals. It also comes with Alexa Wake Word engine technology, an […]

Fuzix Unix-like operating system ported to Raspberry Pi Pico and ESP8266

Fuzix Raspberry Pi Pico ESP8266

The Raspberry Pi Pico is not compatible with Linux, but now supports another Unix-like operating system known as Fuzix. Alan Cox’s Fuzix is a Unix-like operating system for older devices with less performance capacity. David Given’s two recent posts have brought to the attention about the operating system’s compatibility with ESP8266 MCU and Raspberry Pi Pico. Fuzix operating system has a kernel which is the central core of the system. Also, it has a C compiler and a set of core applications similar to the UNIX filesystem. The Raspberry Pi Pico port comes with many benefits like a well-structured Unix filesystem with its compatibility for SD cards through the SPI interface. Hence, supporting the Fuzix operating system. The full set of Fuzix binaries is available through a serial console to UART0.  Porting Fuzix to ESP8266 The post on “Porting Fuzix to the ESP8266” addresses the MCU’s support for the Fuzix […]

CN0549 CBM development kit monitors assets through vibration analysis

CN0549 CBM Development Kit interfaced with SMA Connector

Condition Based Monitoring (CBM) has become quite popular in the manufacturing sector due to its advantages. It is a type of pre-analysis monitoring that includes the use of sensors to evaluate the status of an asset over time while it is in operation. Hence, the data collected is used to establish trends, predict failure, and measure the life of an asset. Analog Devices has launched CN0549, a condition-based monitoring development kit. The monitoring functionality signifies the consideration for hardware applications involving vibration. The applications include industrial as well as IoT devices. Hence, the CN0549 CBM development board combines the resources for a dynamic domain of users. Discussing further, condition-based monitoring (CBM) through vibration sensing requires the capturing of full-bandwidth data to ensure that all harmonics, aliasing, and other mechanical interactions are taken care of in both, the time and frequency domain. The data collection by using the sensors and data […]

Person Detection on Raspberry Pi Pico with ArduCAM and TensorFlow Lite

ArduCAM with Raspberry Pi Pico

ArduCAM is popular for camera-based applications with various boards ranging from Arduino to Raspberry Pi. We also saw the company’s tiny coin-sized Raspberry Pi compatible module 5 years ago. Now, it also supports the newly launched Raspberry Pi Pico for real-time video applications. Raspberry Pi Pico is compatible with the ArduCAM Mini 2MP Plus camera featuring an OV2640 2MP CMOS image sensor that supports automatic image control functions including Automatic Exposure Control (AEC) and Automatic Gain Control(AGC). The camera also comes with an onboard JPEG encoder for image compression. The company has provided a Github repository with two demo applications: a video streaming application and an example for basic person detection with the probability percentage of detection. There is also an option of directly using the UF2 files for flashing with Raspberry Pi Pico, if you don’t want to build the demo from the source code yourself. The application runs […]

Raspberry Pi Pico Gets supports for Rust, RT-Thread OS and FreeRTOS

Raspberry Pi Pico Rust RT-Thread FreeRTOS

In January end, we saw the launch of Raspberry Pi Pico equipped with an RP2040 dual-core Cortex-M0+ microcontroller working up to 133 MHz with official support for MicroPython and C. In this feature, we will be discussing the Raspberry Pi Pico’s flexible software support compatible with RP2040 MCU, apart from the MicroPython, C/C++, and upcoming Arduino IDE software support. We will specifically be focusing on Rust, RT-Thread OS, and FreeRTOS support for Raspberry Pi Pico. Rust Code Running on Raspberry Pi Pico Rust language is considered fast, reliable, and secure when it comes to IoT gateways. It also opens up the option for writing extremely low-level code, such as operating system kernels or microcontroller applications.  Porting Rust with RP2040 for working with Raspberry Pi Pico was seen in Jonathan Pallant’s Twitter Feed. The RP2040 comes with an external QSPI flash. The internal mask-ROM reads the programs from the external flash […]

Renesas RZ/G2L MPUs Feature Cortex-A55 & Cortex-M33 Cores for AI Applications

Block Diagram of RZ-G2L

Renesas Electronics Corporation announced RZ/G2L MPUs, allowing enhanced processing for an extensive variety of AI applications. The RZ/G2L group of 64-bit MPUs includes three new MPU models featuring Arm Cortex-A55, and an optional Cortex-M33 core. These are RZ/G2L, RZ/G2LC, and RZ/G2UL MPUs. The Cortex-A55 CPU core typically delivers approximately 20 percent improved processing performance compared with the previous Cortex-A53 core, and according to Renesas, is around six times faster in “essential processing for AI applications”. The company already has four mid to high-end design level MPUs including RZ/G2E, RZ/G2N, RZ/G2M, and RZ/G2H, with combinations of Cortex-A53 and Cortex-A57 cores. The new RZ/G2L group of three MPUs forms the entry-level design with Cortex-A55. Hence, the seven MPU models together provide scalability from entry-level to high-end design. Common Key Features in RZ/G2L, RZ/G2LC, and RZ/G2UL MPUs Up to 2x Cortex-A55 cores Cortex-M33 core Camera interface (MIPI-CSI) Display interface (Parallel-IF) USB2.0 interface 2ch, […]

ASUS Tinker board - Raspberry Pi alternative