RPI 4 Model B IoT Trainer Kit

 RPI 4 loT Development Trainer Kit essential development features a plug - and - play design that makes it easy for connections and helps Students, hobbyists, enthusiasts and professionals to focus more on Program/application development. RPI 4 loT Trainer Kit equipped with onboard IO's, communication interfaces & peripherals. It is really easy to design, experiment with, and test circuits without soldering. It's used in many educational institutions and R&D LAB across the world..

ORDER CODE: RDL922

Board Features:

• Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz
• 4GB LPDDR4 SDRAM
• 2.4GHz and 5.0GHz IEEE 802.11b/g/n/ac wireless LAN, Bluetooth 5.0, BLE
• True Gigabit Ethernet
• 2x USB 3.0 ports, 2x USB 2.0 Ports
• Fully backwards compatible 40-pin GPIO header
• 2x Micro HDMI ports supporting up to 4K 60Hz video resolution
• 2-lane MIPI DSI/CSI ports for camera and display
• 4-pole stereo audio and composite video port
• MicroSD card slot for loading operating system and data storage
• Onboard 5.1V, 3A power via USB-C or GPIO
• On Board Programming.
• Plug & Play Interface Connectivity.
• Professional EMI/RFI Complaint PCB Layout Design
• Modular Block design makes Easy access & quick Prototyping
• FRC connectivity features minimize the connection Error.
• ROHS Compliant High Quality Grade PCB with wooden Enclosure.
• Open-source Hardware RPI 0 single-core 32-bit up to 240 MHz, Flash 16 MB.
• Supported most of the open-source platforms for Custom Programming
• The device offers multiple industrial protocols like MODBUS RTU, MODBUS TCP, JSON, MQTT and FTP and supports secure communication SSL.
• Supported most of the cloud platforms including Microsoft Azure & AWS etc
• OTA Firmware upgrade supported
• On Board Programming.
• Supported communication over USB, WiFi, Bluetooth, and Modbus RTU and RS232
• Supported DC 12V Power Supply.
• 1 * 8 interfacing LED’s.
• 1 * 4 Menu keypad.
• 4 * 4 Matrix Keypad.
• RS232, RS485, USB communication port.
• 7 Segment Multiplexed Display.
• 16*2 LCD & OLED Display
• On Board Wi-Fi/Bluetooth Connectivity
• 3.3 to 5V Level Converter.
• Power Supply 3.3V and 5V
• SD CARD Interface.
• RTC & EEPROM Interface.
• DC Motor/ Stepper Motor Driver.
• Relay, Buzzer.
• High Quality Grade PCB with wooden Enclosure.

Applications

• Genetic Low - power IoT Sensor Hub.
• Genetic Low - power IoT Dataloggers.
• Cameras for Video Streaming.
• Over-the-top (OTT) devices.
• Speech Recognition.
• Image Recognition.
• Mesh Network.
• Home Automation.
• Smart Building.
• Industrial Automation.
• Smart Agriculture.
• Audio Applications.
• Health Care Applications.
• Wi-Fi Enabled Toys.
• Wearable Electronics.
• Retail & Catering Applications.

Scope of Learning Experiments

• LED blinking.
• 8 bit LED Left shift, Right shift and counting operation.
• Keypad interrupt interface.
• 6*2 LCD interface.
• Matrix Keypad Interface.
• Traffic light signal interface.
• 8 bit DIP switch interface.
• L298 Driver for DC Motor and Stepper motor interface.
• Communication using UART, I2C & SPI.
• Buzzer, Relay interface.
• RS485, RS232 serial communication.
• RPI4 IO interfacing with different sensor.
• RTC DS1307I2C protocol interface.
• AT24C04 EEPROM I2C protocol interface.
• Wi-Fi Communication.
• Interfacing SD card and handling file system.
• Interfacing sensor with & Data parsing using RESTful & Json protocol.
• FTP Implementation.
• Interfacing sensor with RPI 4 and MQTT protocol implementation.
• Exploring MQTT features subscribe & publish methods.
• MQTT SSL certificate implementation - RPI 4.
• Interfacing RS485 salve using MODBUS protocol.
• Interfacing BLE & Data parsing using RESTful / Json / MQTT protocol.
• Text to speech implementation.
• Device control through speech recognition & alexa integration.
• Appliance control through cloud platform using MQTT protocol.
• Environment data like temp & humidity capturing using cloud platform.
• Modbus RTU communication and accessing data from Industrial PLC.
• Wireless TCP / IP socket connection implementation using node and server architecture.
• BioMedical sensor kit integration and connecting IoT cloud platform for prediction.
• Implementation of RPI 4 WEB server application.