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39 Experiments with Raspberry Pi and Arduino This book is about Raspberry Pi 3 and Arduino camera projects. The book explains in simple terms and with tested and working example projects, how to configure and use a Raspberry Pi camera and USB based webcam in camera-based projects using a Raspberry Pi. Example projects are given to capture images, create timelapse photography, record video, use the camera and Raspberry Pi in security and surveillance applications, post images to Twitter, record wildlife, stream live video to YouTube, use a night camera, send pictures to smartphones, face and eye detection, colour and shape recognition, number plate recognition, barcode recognition and many more. Installation and use of popular image processing libraries and software including OpenCV, SimpleCV, and OpenALPR are explained in detail using a Raspberry Pi. The book also explains in detail how to use a camera on an Arduino development board to capture images and then save them on a microSD card. All projects given in this book have been fully tested and are working. Program listings for all Raspberry Pi and Arduino projects used in this book are available for download on the Elektor website.

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This camera module adopts a SmartSens SC3336 sensor chip with 3 MP resolution. It features high sensitivity, high SNR, and low light performance and it is capable of a more delicate and vivid night vision imaging effect, and can better adapt to ambient light changes. Also, it is compatible with Luckfox Pico series boards. Specifications Sensor Sensor: SC3336 CMOS size: 1/2.8" Pixels: 3 MP Static resolution: 2304x1296 Maximum video frame rate: 30fps Shutter: Rolling shutter Lens Focal length: 3.95 mm Aperture: F2.0 FOV: 98.3° (diagonal) Distortion: <33% Focusing: Manual focus Downloads Wiki

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Raspberry Pi 5 provides two four-lane MIPI connectors, each of which can support either a camera or a display. These connectors use the same 22-way, 0.5 mm-pitch “mini” FPC format as the Compute Module Development Kit, and require adapter cables to connect to the 15-way, 1 mm-pitch “standard” format connectors on current Raspbery Pi camera and display products.These mini-to-standard adapter cables for cameras and displays (note that a camera cable should not be used with a display, and vice versa) are available in 200 mm, 300 mm and 500 mm lengths.

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Raspberry Pi 5 provides two four-lane MIPI connectors, each of which can support either a camera or a display. These connectors use the same 22-way, 0.5 mm-pitch “mini” FPC format as the Compute Module Development Kit, and require adapter cables to connect to the 15-way, 1 mm-pitch “standard” format connectors on current Raspbery Pi camera and display products.These mini-to-standard adapter cables for cameras and displays (note that a camera cable should not be used with a display, and vice versa) are available in 200 mm, 300 mm and 500 mm lengths.

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Raspberry Pi 5 provides two four-lane MIPI connectors, each of which can support either a camera or a display. These connectors use the same 22-way, 0.5 mm-pitch “mini” FPC format as the Compute Module Development Kit, and require adapter cables to connect to the 15-way, 1 mm-pitch “standard” format connectors on current Raspbery Pi camera and display products.These mini-to-standard adapter cables for cameras and displays (note that a camera cable should not be used with a display, and vice versa) are available in 200 mm, 300 mm and 500 mm lengths.

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OV7740 is a AI Camera powered by Kendryte K210, an edge computing system-on-chip(SoC) with a dual-core 64bit RISC-V CPU and state-of-art neural network processor. Features Dual-Core 64-bit RISC-V RV64IMAFDC (RV64GC) CPU / 400Mhz(Normal) Dual Independent Double Precision FPU 8MiB 64bit width On-Chip SRAM Neural Network Processor(KPU) / 0.8Tops Field-Programmable IO Array (FPIOA) AES, SHA256 Accelerator Direct Memory Access Controller (DMAC) Micropython Support Firmware encryption support On-board Hardware: Flash: 16M Camera :OV7740 2x Buttons Status Indicator LED External storage: TF card/Micro SD Interface: HY2.0/compatible GROVE Applications Face recognition/detection Object detection/classification Obtain the size and coordinates of the target in real-time Obtain the type of detected target in real-time Shape recognition Video recorder Included 1x UNIT-V(include 20cm 4P cable and USB-C cable)

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THSER102 is a plug-and-play cable extension kit for Raspberry Pi Camera Modules. The kit is compatible with Raspberry Pi Camera Module 3, in addition to Camera V2 (version 2.1), HQ/Global Shutter Camera, and defined modes of the Raspberry Pi Camera Module V1.3. The THSER102 extends the cable length for >10 meters between the Raspberry Pi Camera Module and the Computer with a standard LAN Cable. There is no need for software or coding. THSER102 works as if the Raspberry Pi Camera were directly connected to the computer. The THSER102 also supports advanced applications. HAT on HAT support allows to use another HAT board on top of THSER102 Rx Board. 3ch GPIO Extension allows extending GPIO communication between the camera location and the computer. Features Supporting all Raspberry Pi Camera Modules including Camera Module 3 >10-meter Cable Extension Plug and Play No software configuration is needed. Camera works as if THSER102 not exists. Advanced Applications Supported HAT on HAT 3ch GPIO Extension Included 1x Tx Board 1x Rx Board 1x LAN Cable (2 m) 2x Flat Flex Cables 1x Pin Header 6x Mounting Screws for Rx Board 3x Longer Spacers for Rx Board 4x Mounting screws for Tx Board (for Camera V2 only) 4x Shorter Spacers for Tx Board (for Camera V2 only) 4x Mounting Nuts for Tx Board (for Camera V2 only) Downloads Datasheet

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Is your house haunted? Or, rather, are you convinced that your house is haunted but have never been able to prove it since you've never had a camera that integrated with your Raspberry Pi Zero but was still small enough that the ghosts wouldn't notice it? Luckily, the spy camera for Raspberry Pi Zero is smaller than a thumbnail with a high enough resolution to see people, ghosts, or whatever it is you're looking for. It's about the size of a cell phone camera – the module being just 8.6 x 8.6 mm – with only a 2' cable, so you can create an extra compact and sneaky little spy cam. It has a 160-degree focal angle for a very wide/distorted fisheye effect that's great for security systems or watching a big swath of the living room or roadway. Like the Raspberry Pi camera board, it attaches to your Raspberry Pi Zero v1.3 or Zero W by way of the small socket on the board's edge closest to the 'PWR in' port. This interface uses the dedicated CSI interface, which was designed especially for interfacing to cameras. The CSI bus is capable of extremely high data rates, and it exclusively carries pixel data. The camera is connected to the BCM2835 processor on the RPi via the CSI bus, a higher bandwidth link which carries pixel data from the camera back to the processor. This bus travels along the ribbon cable that attaches the camera board to the Pi. The ribbon cables are compatible with both the RPi Zero v1.3 and RPi Zero W. The sensor itself has a native resolution of 5 megapixels and has a fixed focus lens onboard. It has similar specs as the original RPi camera, but is not as high-res as the new RPi camera v2! Specifications Camera Module Dimensions: 8.6 x 8.6 mm Lens Diameter: 10 mm Total Length: 60 mm Lens Focal Angle: 160 degrees Weight: 1.9 g

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The Arduino Pro Portenta Vision Shield brings industry-rated features to your Portenta. This hardware add-on will let you run embedded computer vision applications, connect wirelessly or via Ethernet to the Arduino Cloud or your own infrastructure, and activate your system upon the detection of sound events. Features 324x324 pixels camera sensor: use one of the cores in Portenta to run image recognition algorithms using the OpenMV for Arduino editor 100 Mbps Ethernet connector: get your Portenta H7 connected to the wired Internet 2 onboard microphones for directional sound detection: capture and analyse sound in real-time JTAG connector: perform low-level debugging of your Portenta board or special firmware updates using an external programmer SD-Card connector: store your captured data in the card, or read configuration files The Vision Shield has been designed to fit on top of the Arduino Portenta family. The Portenta boards feature multicore 32-bit ARM Cortex processors running at hundreds of megahertz, with megabytes of program memory and RAM. Portenta boards come with WiFi and Bluetooth. Embedded Computer Vision Made Easy Arduino has teamed up with OpenMV to offer you a free license to the OpenMV IDE, an easy way into computer vision using MicroPython as a programming paradigm. Download the OpenMV for Arduino Editor from our professional tutorials site and browse through the examples we have prepared for you inside the OpenMV IDE. Companies across the whole world are already building their commercial products based on this simple-yet-powerful approach to detect, filter, and classify images, QR codes, and others. Debugging With Professional Tools Connect your Portenta H7 to a professional debugger through the JTAG connector. Use professional software tools like the ones from Lauterbach or Segger on top of your board to debug your code step by step. The Vision Shield exposes the required pins for you to plug in your external JTAG. Camera Himax HM-01B0 camera module Resolution 320 x 320 active pixel resolution with support for QVGA Image sensor High sensitivity 3.6μ BrightSense pixel technology Microphone 2 x MP34DT05 Length 66 mm Width 25 mm Weight 11 gr For more information, check out the tutorials provided by Arduino here.

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The Arduino Pro Portenta Vision Shield LoRa brings industry-rated features to your Portenta. This hardware add-on will let you run embedded computer vision applications, connect wirelessly via LoRa to the Arduino Cloud or your own infrastructure, and activate your system upon the detection of sound events. The shield comes with: a 320x320 pixels camera sensor: use one of the cores in Portenta to run image recognition algorithms using the OpenMV for Arduino editor long range 868/915 MHz LoRa wireless connectivity: get your Portenta H7 connected to the Internet of Things with low power consumption two on-board microphones for directional sound detection: capture and analyse sound in real-time JTAG connector: perform low-level debugging of your Portenta board or special firmware updates using an external programmer SD-Card connector: store your captured data in the card, or read configuration files The Vision Shield LoRa has been designed to work with the Arduino Portenta H7. The Portenta boards feature multicore 32-bit ARM Cortex processors running at hundreds of megahertz, with megabytes of program memory and RAM. Portenta boards come with WiFi and Bluetooth. Specifications Camera Himax HM-01B0 camera module (manufacturer site) Resolution 320 x 320 active pixel resolution with support for QVGA Image sensor High sensitivity 3.6μ BrightSense pixel technology Microphone 2x MP34DT05 (datasheet) Connectivity 868/915MHz ABZ-093 LoRa Module with ARM Cortex-M0+ (datasheet) Dimensions 66 x 25 mm Weight 8 g Downloads Datasheet Schematics

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The uArm Swift Pro is a high quality robotic arm that can be used in a wide range of applications. The uArm Swift Pro was developed and optimized for use in education, which means that many packages are already available for open source platforms such as ROS. The uArm Swift Pro has a position repeatability of 0.2 mm and is also equipped with a stepper motor and a 12-bit encoder. These are just a few reasons that make the uArm Swift Pro an excellent choice for educational use. Another great feature is the 3D printing kit that converts the uArm Swift Pro into a 3D printer in less than 1 minute. The uArm supports the following development platforms/systems: UFACTORY SDK Arduino Python ROS GRABCAD OpenMV Smartphone App The smartphone app for iOS is already available in the App Store and enables easy control and monitoring of the robotic arm. The app for Android is in development and will be available soon. An example of the Machine Vision The following GIF shows the uArm in combination with the OpenMV Machine Vision Cam M7 and the facial recognition applications that can be implemented in MicroPython. Specifications Degrees of Freedom: 4 Repeatability: Up to 0.2 mm Payload: 500 g Working Range: 50-320 mm Positioning Speed: 100 m/s Position Feedback: 12-bit Encoder Dimensions: 150 x 140 x 281mm Weight: 2.2 kg Included UFactory uArm Swift Pro Body Bluetooth & Vacuum Gripper Downloads Datasheet

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