This collection features the best of Elektor Magazine's articles on embedded systems and artificial intelligence. From hands-on programming guides to innovative AI experiments, these pieces offer valuable insights and practical knowledge for engineers, developers, and enthusiasts exploring the evolving intersection of hardware design, software innovation, and intelligent technology. Contents Programming PICs from the Ground UpAssembler routine to output a sine wave Object-Oriented ProgrammingA Short Primer Using C++ Programming an FPGA Tracking Down Microcontroller Buffer Overflows with 0xDEADBEEF Too Quick to Code and Too Slow to Test? Understanding the Neurons in Neural NetworksEmbedded Neurons MAUI Programming for PC, Tablet, and SmartphoneThe New Framework in Theory and Practice USB Killer DetectorBetter Safe Than Sorry Understanding the Neurons in Neural NetworksArtificial Neurons A Bare-Metal Programming Guide Part 1: For STM32 and Other Controllers Part 2: Accurate Timing, the UART, and Debugging Part 3: CMSIS Headers, Automatic Testing, and a Web Server Introduction to TinyMLBig Is Not Always Better Microprocessors for Embedded SystemsPeculiar Parts, the Series FPGAs for BeginnersThe Path From MCU to FPGA Programming AI in Electronics DevelopmentAn Update After Only One Year AI in the Electronics LabGoogle Bard and Flux Copilot Put to the Test ESP32 and ChatGPTOn the Way to a Self-Programming System… Audio DSP FX Processor Board Part 1: Features and Design Part 2: Creating Applications Rust + EmbeddedA Development Power Duo A Smart Object CounterImage Recognition Made Easy with Edge Impulse Universal Garden LoggerA Step Towards AI Gardening A VHDL ClockMade with ChatGPT TensorFlow Lite on Small MicrocontrollersA (Very) Beginner’s Point of View Mosquito DetectionUsing Open Datasets and Arduino Nicla Vision Artificial Intelligence Timeline Intro to AI AlgorithmsPrompt: Which Algorithms Implement Each AI Tool? Bringing AI to the Edgewith ESP32-P4 The Growing Role of Edge AIA Trend Shaping the Future

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LuckFox Pico Mini is a compact Linux micro development board based on the Rockchip RV1103 chip, providing a simple and efficient development platform for developers. It supports a variety of interfaces, including MIPI CSI, GPIO, UART, SPI, I²C, USB, etc., which is convenient for quick development and debugging. Features Single-core ARM Cortex-A7 32-bit core with integrated NEON and FPU Built-in Rockchip self-developed 4th generation NPU, features high computing precision and supports int, int8, and int16 hybrid quantization. The computing power of int8 is 0.5 TOPS, and up to 1.0 TOPS with int4 Built-in self-developed third-generation ISP3.2, supports 4-Megapixel, with multiple image enhancement and correction algorithms such as HDR, WDR, multi-level noise reduction, etc. Features powerful encoding performance, supports intelligent encoding mode and adaptive stream saving according to the scene, saves more than 50% bit rate of the conventional CBR mode so that the images from camera are high-definition with smaller size, double the storage space Built-in RISC-V MCU supports low power consumption and fast start-up, supports 250 ms fast picture capture and loading Al model library at the same time to realize face recognition "in one second" Built-in 16-bit DRAM DDR2, which is capable of sustaining demanding memory bandwidths Integrated with built-in POR, audio codec and MAC PHY Specifications Processor ARM Cortex-A7, single-core 32-bit CPU, 1.2 GHz, with NEON and FPU NPU Rockchip 4th-gen NPU, supports int4, int8, int16; up to 1.0 TOPS (int4) ISP Third-gen ISP3.2, up to 4 MP input at 30fps, HDR, WDR, noise reduction RAM 64 MB DDR2 Storage 128 MB SPI NAND Flash USB USB 2.0 Host/Device via Type-C Camera Interface MIPI CSI 2-lane GPIO Pins 17 GPIO pins Power Consumption Low power, RISC-V MCU for fast startup Dimensions 28 x 21 mm Downloads Wiki

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The LuckFox Pico Ultra is a compact single-board computer (SBC) powered by the Rockchip RV1106G3 chipset, designed for AI processing, multimedia, and low-power embedded applications. It comes equipped with a built-in 1 TOPS NPU, making it ideal for edge AI workloads. With 256 MB RAM, 8 GB onboard eMMC storage, integrated WiFi, and support for the LuckFox PoE module, the board delivers both performance and versatility across a wide range of use cases. Running Linux, the LuckFox Pico Ultra supports a variety of interfaces – including MIPI CSI, RGB LCD, GPIO, UART, SPI, I²C, and USB – providing a simple and efficient development platform for applications in smart home, industrial control, and IoT. Specifications Chip Rockchip RV1106G3 Processor Cortex-A7 1.2 GHz Neural Network Processor (NPU) 1 TOPS, supports int4, int8, int16 Image Processor (ISP) Max input 5M @30fps Memory 256 MB DDR3L WiFi + Bluetooth 2.4GHz WiFi-6 Bluetooth 5.2/BLE Camera Interface MIPI CSI 2-lane DPI Interface RGB666 PoE Interface IEEE 802.3af PoE Speaker interface MX1.25 mm USB USB 2.0 Host/Device GPIO 30 GPIO pins Ethernet 10/100M Ethernet controller and embedded PHY Default Storage Medium eMMC (8 GB) Included 1x LuckFox Pico Ultra W 1x LuckFox PoE module 1x IPX 2.4G 2 db antenna 1x USB-A to USB-C cable 1x Screws pack Downloads Wiki

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The reComputer J3010 is a compact and powerful edge AI device powered by the NVIDIA Jetson Orin Nano SoM, delivering an impressive 20 TOPS AI performance – up to 40 times faster than the Jetson Nano. Pre-installed with Jetpack 5.1.1, it features a 128 GB SSD, 4x USB 3.2 ports, HDMI, Gigabit Ethernet, and a versatile carrier board with M.2 Key E for WiFi, M.2 Key M for SSD, RTC, CAN, and a 40-pin GPIO header. Applications AI Video Analytics Machine Vision Robotics Specifications Jetson Orin Nano System-on-Module AI Performance reComputer J3010, Orin Nano 4 GB (20 TOPS) GPU 512-core NVIDIA Ampere architecture GPU with 16 Tensor Cores (Orin Nano 4 GB) CPU 6-core Arm Cortex-A78AE v8.2 64-bit CPU 1.5 MB L2 + 4 MB L3 Memory 4 GB 64-bit LPDDR5 34 GB/s (Orin Nano 4 GB) Video Encoder 1080p30 supported by 1-2 CPU cores Video Decoder 1x 4K60 (H.265) | 2x 4K30 (H.265) | 5x 1080p60 (H.265) | 11x 1080p30 (H.265) Carrier Board Storage M.2 Key M PCIe (M.2 NVMe 2280 SSD 128 GB included) Networking Ethernet 1x RJ-45 Gigabit Ethernet (10/100/1000M) M.2 Key E 1x M.2 Key E (pre-installed 1x Wi-Fi/Bluetooth combo module) I/O USB 4x USB 3.2 Type-A (10 Gbps)1x USB 2.0 Type-C (Device Mode) CSI Camera 2x CSI (2-lane 15-pin) Display 1x HDMI 2.1 Fan 1x 4-pin Fan Connector (5 V PWM) CAN 1x CAN Multifunctional Port 1x 40-Pin Expansion header 1x 12-Pin Control and UART header RTC RTC 2-pin, supports CR1220 (not included) Power Supply 9-19 V DC Mechanical Dimensions 130 x 120 x 58.5 mm (with Case) Installation Desktop, wall-mounting Operating Temperature −10°C~60°C Included 1x reComputer J3010 (system installed) 1x Power adapter (12 V / 5 A) Downloads reComputer J301x Datasheet NVIDIA Jetson Devices and carrier boards comparisions reComputer J401 schematic design file reComputer J3010 3D file

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The reComputer J1020 v2 is a compact edge AI device powered by the NVIDIA Jetson Nano 4 GB production module, delivering 0.5 TFLOPs of AI performance. It features a robust aluminum case with a passive heatsink and comes pre-installed with JetPack 4.6.1. The device includes 16 GB of onboard eMMC storage and offers 2x SCI, 4x USB 3.0, M.2 Key M, HDMI, and DP. Applications Computer Vision Machine Learning Autonomous Mobile Robot (AMR) Specifications Jetson Nano 4 GB System-on-Module AI Performance Jetson Nano 4 GB (0.5 TOPS) GPU NVIDIA Maxwel architecture with 128 NVIDIA CUDA cores CPU Quad-core ARM Cortex-A57 MPCore processor Memory 4 GB 64-bit LPDDR4 25.6 GB/s Video Encoder 1x 4K30 | 2x 1080p60 | 4x 1080p30 | 4x 720p60 | 9x 720p30 (H.265 & H.264) Video Decoder 1x 4K60 | 2x 4K30 | 4x 1080p60 | 8x 1080p30 | 9x 720p60 (H.265 & H.264) Carrier Board Storage 1x M.2 Key M PCIe Networking Ethernet 1x RJ-45 Gigabit Ethernet (10/100/1000M) I/O USB 4x USB 3.0 Type-A1x Micro-USB port for device mode CSI Camera 2x CSI (2-lane 15-pin) Display 1x HDMI Type A; 1x DP Fan 1x 4-pin Fan Connector (5 V PWM) CAN 1x CAN Multifunctional Port 1x 40-Pin Expansion header 1x 12-Pin Control and UART header Power Supply DC 12 V/2 A Mechanical Dimensions 130 x 120 x 50 mm (with Case) Installation Desktop, wall-mounting Operating Temperature −10°C~60°C Included reComputer J1020 v2 (system installed) 12 V/2 A power adapter (with 5 interchangeable adapter plugs) Downloads reComputer J1020 v2 datasheet reComputer J1020 v2 3D file Seeed NVIDIA Jetson Product Catalog NVIDIA Jetson Device and Carrier Boards Comparison

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The starter kit for Jetson Nano is one of the best kits for beginners to get started with Jetson Nano. This kit includes 32 GB MicroSD card, 20 W adapter, 2-pin jumper, camera, and micro-USB cable. Features 32 GB High-performance MicroSD card 5 V 4 A power supply with 2.1 mm DC barrel connector 2-pin jumper Raspberry Pi camera module V2 Micro-B To Type-A USB cable with DATA enabled

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