Raspberry Pi 4 Model B Board & Starter Kit, BCM2711 1.5GHz, 2GB/4GB/8GB, WiFi/BT 5.0, GbE

Overview

This Raspberry Pi 4B board and starter kit is based on the 2019 Raspberry Pi 4 Model B platform, featuring a 1.5GHz 64-bit quad-core CPU and Broadcom BCM2711 SoC. It provides multiple RAM options (2GB/4GB/8GB) and a wide set of interfaces for robotics, AI/vision learning, and general DIY computing projects.

Key Features

• Broadcom BCM2711 four-core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz
• RAM options: 2GB / 4GB / 8GB
• GPU: Broadcom VideoCore VI @ 500MHz
• Wireless: 802.11AC wireless, 2.4GHz/5GHz dual-band WiFi; Bluetooth 5.0
• USB: USB2.0*2 and USB3.0*2
• Display: Micro HDMI*2 (supports 4K60)
• Power: Type-C (5V 3A)
• Wired network: True Gigabit Ethernet (up to the network port)
• 40 GPIO pins; CSI camera port; DSI display port
• PoE: powered via additional HAT Ethernet (PoE)

Interface/Function Labels Shown

• USB management chip; power management chip
• Audio interface
• USB 2.0; USB 3.0
• Gigabit Ethernet ports
• Camera interface
• Micro HDMI
• Type-C power supply
• DSI display connector
• Dual-band WiFi / Bluetooth 5.0
• The network PoE interface card

RAM Option Guidance (Text Shown)

• 2GB: Suitable for users who need to configure a graphical user interface or surf the internet. If watching videos as a PC, deploy a mini network server.
• 4GB (Most people's choices): Suitable for users doing more complex computer multitasking, such as dual-screen 4K video playback, AI visual depth learning, etc.
• 8GB: Suitable for users who wish to use a 64 bit system and run complex programs, with 8GB RAM can better leverage CPU performance and memory advantages.

The CPU performance of Raspberry Pi 2G/4G/8G is consistent, with only differences in RAM. The 4B-2G version of Raspberry Pi can achieve an overall computational performance of over three times that of 3B+. When RAM is sufficient, the impact of memory on computational speed is relatively small.

Specifications

Applications

• Smart robots and Raspberry Pi robotics learning projects
• DIY tablet-style computing and general embedded development
• Computer vision/OpenCV learning and AI course exercises (as listed in the course materials below)

Tutorials & Course Materials

For questions about choosing a RAM version or preparing a learning setup, contact support@rcdrone.top or visit https://rcdrone.top/.

AI Visual Advanced Development Materials (Updated September 2023)

• 1. Introduction of OpenCV.pdf
• 2. OpenCV image read and display.pdf
• 3. OpenCV image write.pdf
• 4. OpenCV image quality.pdf
• 5. OpenCV pixel operation.pdf
• 6. Picture Zoom.pdf
• 7. Picture Cut.pdf
• 8. Picture Shift.pdf
• 9. Picture Mirroring.pdf
• 10. Affine Map.pdf
• 11. Picture Rotation.pdf
• 12. Perspective Transformation.pdf
• 13. Grayscale processing.pdf
• 14. Image Binarization.pdf
• 15. Edge detection.pdf
• 16. Drawing line segment.pdf
• 17. Drawing rectangle circle.pdf
• 18. Drawing text picture.pdf
• 19. Histogram of color pictures.pdf
• 20. Histogram equalization.pdf
• 21. Image restoration.pdf
• 22. Brightness enhancement.pdf
• 23. Skin whitening.pdf
• 24. Gaussian mean filtering.pdf
• 25. Median filtering.pdf
• 26. Install TensorFlow.pdf
• 27. QR code.pdf
• 28. Human posture estimation.pdf
• 29. Target detection.pdf
• 30. Mediapipe development.pdf
• 31. yolov4-tiny_en.pdf

Free New AI Advanced Tutorial (Topics Shown)

• Open Source CV environment construction: 1. Preparation; 2. Install OpenCV
• A. Getting started with OpenCV: 1. Introduction of OpenCV; 2. OpenCV image read and display; 3. OpenCV image write; 4. OpenCV image quality; 5. OpenCV pixel operation
• B. OpenCV Geometric transformation: 1. Picture Zoom; 2. Picture Cut; 3. Picture Shift; 4. Picture Mirroring; 5. Affine Map; 6. Picture Rotation; 7. Perspective Transformation
• C. OpenCV picture processing and drawing text line segments: 1. Grayscale processing; 2. Image Binarization; 3. Edge detection; 4. Drawing line segment; 5. Drawing rectangle circle; 6. Drawing text picture
• D. OpenCV image beautification: 1. Histogram of color pictures; 2. Histogram equalization; 3. Image restoration; 4. Brightness enhancement; 5. Skin whitening; 6. Gaussian mean filtering; 7. Median filtering
• E. OpenCV machine learning: 1. KNN recognition of handwritten numbers; 2. CNN recognition of handwritten numbers; 3. SVM recognition of handwritten numbers

ROS Advanced Course for Raspberry Pi (Outline Shown)

• 1. Introduction of ROS
• 2. Project file structure
• 3. Common Commands and Tools
• 4. Publisher
• 5. Subscriber
• 6. Customized topic messages and usage
• 7. Client
• 8. Server
• 9. Customizing service messages and usage
• 10. TF publishing and monitoring

Mass Course Materials (Items Shown)

• Basic Course:
  • 1. Log into Raspberry Pi system.pdf
  • 2. Change password and root account.pdf
  • 3. Remote transfer file.pdf
  • 4. Backup image file.pdf
  • 5. Fixing Raspberry Pi IP.pdf
  • 6. Set screen keep on.pdf
  • 7. Get Pi temperature.pdf
  • 8. Connect WIFI.pdf
  • 9. Modify Pi time.pdf
  • 10. Set the boot self-starting program.pdf
  • Attachment script.zip
• Expand Course:
  • 1. Serial port communicates with external devices.pdf
  • 2. Serial port login Pi.pdf
  • 3. Configured as a router.pdf
  • 4. Install Jupyter Lab.pdf
  • 5. Install Jupyter Widgets.pdf
  • 6. More Detail for Widgets.pdf
  • 7. Install OpenCV.pdf
  • 8. Install Tensorflow.pdf
  • File.zip
  • opencv missing configuration files.zip
  • opencv.zip
  • opencv_contrib.zip
• Programming Course:
  • C language
  • Python language
  • 1. Development environment.pdf
  • 2. Print Hello World.pdf
  • 3. Pin output level.pdf
  • 4. Read pin level.pdf
  • 5. PWM output.pdf
  • C_code.zip
  • Python_code.zip

Notes

• Heat sink paste example labels shown: CPU, RAM, USB management chip, Network card (not attached).
• A “Packing list” header is shown, but no itemized packing contents are provided.

Details

From smart cars to walking robots, the Raspberry Pi platform is widely used for hands-on robotics projects.

Choose 2GB, 4GB, or 8GB RAM depending on whether you’re building a light desktop, media setup, or heavier multitasking projects.

AI/vision learning resources pair well with the Pi 4B’s hardware interfaces for camera and OpenCV-style projects.

Build ROS-based robotics skills with course modules covering tools, topics, nodes, and project structure.

Raspberry Pi 4 Model B uses the Broadcom BCM2711 platform and adds modern connectivity like USB 3.0 and dual micro HDMI.

The same CPU performance is shared across versions—RAM primarily affects how comfortably larger apps and multitasking run.

Ports and headers are clearly laid out for displays, cameras, networking, and expansion via the 40-pin GPIO.

Thermal pads or paste can be applied to key chips when building enclosed or higher-load Raspberry Pi projects.