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1. Product Description Vending machines, combining modern technology with the idea of convenient shopping, have become essential in our lives. It breaks through the constraints of time and space, providing us with round-the-clock uninterrupted product purchasing services. Whether in busy transportation hubs or quiet residential areas, you can always find its presence. 2. Components: Body Compartment: Made from high-strength, corrosion-resistant metal materials to ensure the stability and durability of the vending machine. The warehouse's interior is well-designed and can be adjusted according to the size of the goods to maximize the use of storage space. Payment System: Integrated with multiple payment methods including coins, bills, card swiping, and mobile payments, satisfying various consumer payment needs. Display and operation: HD touchscreen shows product information and purchase process, simplifying steps to enhance user experience. Product Delivery System: Uses precise mechanics and sensors for accurate, fast delivery to the outlet after payment. Communication Management System: Enables real-time monitoring, sales data analysis, and remote fault diagnosis and repair of vending machines via wireless network. Business Logic Topology The vending machine's main control system acts as its operational core, akin to its "brain", overseeing and coordinating each module's functions. With the ongoing development of IoT, big data, and AI, automation has become an inevitable trend in the vending machine industry. This has led to new demands for the main control systems, focusing on: Core Controller: It is essential to choose a stable, reliable, and high-performance core controller to ensure the overall logic control and data processing capabilities of vending machines. Device Stability: It requires 24/7 uninterrupted operation, necessitating high stability and durability in both hardware and software. Specifically, the software system should have fault self-check and automatic recovery capabilities. Scalability and Compatibility: To meet various scenarios and demands, the main control system of vending machines needs to be scalable. As products evolve, the main control system should be compatible with new hardware and software standards. Payment Security: As payment methods diversify, ensuring the security of the payment process has become increasingly important. Vending machines need to guard against various security threats, such as data breaches and fraudulent activities. AI Integration: Vending machines need to have intelligent recognition capabilities and data analysis abilities to recommend products based on users' purchasing preferences. FET3568-C system on module(SoM) from Forlinx Embedded Systems offers high performance, low power consumption, and rich functionality, making it ideal for vending machines for these reasons: Powerful Performance: FET3568-C SoM is based on the Rockchip RK3568 processor, which features a quad-core 64-bit Cortex-A55 architecture with a clock speed of up to 2.0GHz. It supports lightweight edge AI computing and delivers strong computational and processing capabilities. Such performance meets the high demands of logic control and data processing for vending machine control systems, ensuring efficient and stable operation of the vending machines. Rich Interfaces and Expandability: The FET3568-C SoM offers 3 x PCIe slots, 4 x USB ports, 3 x SATA3.0 controllers, and 2 x Gigabit Ethernet ports. It supports 5 x display interfaces including HDMI2.0, eDP, LVDS, RGB Parallel, and MIPI-DSI, with up to three simultaneous display outputs. These interfaces provide great convenience for expanding the functionality of vending machines, enabling customized development to meet various scenarios and requirements. Multi-OS Support: FET3568-C SoM supports multiple operating systems including Linux, Android 11, Ubuntu, and Debian 11. This flexibility allows developers to choose the most suitable operating system according to actual needs, thereby simplifying the software development process and improving development efficiency. Meanwhile, Forlinx Embedded has made numerous optimizations in software, such as introducing a 4G watchdog process. This design ensures that the 4G communication function can automatically recover after a disconnection, significantly improving the stability and reliability of the vending machine's network communication. Advanced Security: In terms of security, the FET3568-C hardware can integrate encryption chips and trusted root modules. These hardware-level security measures provide solid protection for system information security. The ability to verify software integrity and authenticity from the hardware level effectively prevents the intrusion of malicious software and the risk of system tampering. High Stability: FET3568-C has undergone rigorous environmental temperature testing, stress testing, and long-term stability operation testing, ensuring stable and reliable performance in various terminals and operational environments. This is crucial for vending machines that require 24/7 uninterrupted operation, as it can significantly reduce failure rates and enhance user experience. In summary, the FET3568-C SoM not only features robust performance and stability, but also offers flexible operating system options, optimized software design, rich interfaces, and powerful expandability. These features make it an ideal choice for vending machine control solutions, capable of meeting the evolving needs of the industry.

Software version: Linux 4.19 Design Idea: Detect screen touch events to determine whether the screen is being used or not in an auto-break application. If the screen detects input events, it will remain on. If no touch events are received for a period of time, the screen will transition from on to a dimmed state, reminding the user that it is about to enter the screen-off mode. If no touch events occur after dimming, the screen will enter the screen-off mode. When a touch event occurs again, the screen will transition from screen-off mode to the on state. Currently, the approach to implement automatic screen-off is to treat touch events as a fixed path that can be applied to familiar boards. To enhance convenience in application, two additional alternative approaches are provided below: ▊ The first implementation method You can apply the evtest command to get the path to/dev/input/event1 (event1 is the name of the touch event on my board). You can then pass the path to your program as a parameter. For example, you can modify your program to accept command-line arguments to specify the path of the device file to open int argc, char *argv[]; Opens a file with the passed in parameters as the device file path int fd = open(argv[1], O_RDONLY); You can compile and run the program, passing it/dev/input/event1 as a command-line argument, like this: ./your_program /dev/input/event1 ▊ The second implementation method is to fix the screen touch node in the device tree. Look for the screen touch node in the device tree and note its address. On the I2C bus, the address of the touch node is simply 2-0038 So we can use grep to filter out touch nodes based on their addresses. ls -l /sys/class/input | grep "0038" | awk -F ' ' '{print $9}' | grep "event" The following command is used in the application to find the touch event based on the touch address. char *command_output = exec("ls -l /sys/class/input | grep '0038' | awk -F ' ' '{print $9}' | grep 'event'"); Use the sprintf function to splice the path containing the event, and then read the event. Examples of using Sprintf: int main() { char str[100]; int num = 123; float f = 3.14; //Write the formatted data to the string sprintf(str, "%d%.2f", num, f); //print the generated string printf("The output is. %s\n", str); return 0; }

Edge Computing Access Screen is designed to provide an edge computing-based solution for access control systems. It can realize face recognition, data processing, fingerprint recognition and other functions, and improve the security and convenience of the access control system. In terms of application scenarios, intelligent monitoring and access control system is an important part of intelligent building security. The application of edge computing technology can increase the monitoring effect and response speed, avoid the security risks in the process of data transmission, and protect the privacy of users. Edge computing devices can process authentication faster and improve the response speed and security of access control systems. Hardware requirements for edge computing access control screen (1) Processor Select a high-performance and low-power embedded processor, the processor itself needs to come with arithmetic power to meet the needs of edge computing. (2) Memory Configure appropriate memory and flash for system and application data. (3) Interface Provide necessary interfaces between the carrier board and other devices, such as GPIO, UART, I2C, SPI, etc. (4) Communication module Support Wi-Fi or 4G to facilitate data transmission with the cloud platform. (5) Sensor Integrate multiple sensors, such as face recognition, fingerprint recognition, and RF card reader. Edge Computing Access Control Screen Design The FET3568-C SoM is recommended to be used as the hardware platform of edge computing access control screen. The system on module has a quad-core ARM Cortex-A55 processor with a main frequency of 2.0 GHz, and its own NPU has a computing power of 1TOPS, which can meet the needs of lightweight edge computing tasks. Memory: FET3568-C SoM supports LPDDR4 and eMMC storage, and can be configured with appropriate memory and flash memory to meet the needs of the access control system. Interface: Native GPIO, UART, I2C, SPI, Gigabit port, etc. can communicate with other lines. Communication module: FET3568-C supports wireless communication technologies such as Wi-Fi, Bluetooth, and GPS. The appropriate communication module can be selected according to the requirements. Sensors: FET3568-C supports multiple sensor interfaces, such as GPIO, I2C, SPI, etc., and can easily integrate multiple sensors, including face recognition, fingerprint recognition modules, etc. Power supply module: According to the requirements of the access control system, the appropriate power supply chip can be selected to provide stable and reliable power supply for the entire carrier board. Peripheral expansion: USB and SD card slots are convenient for secondary development and function expansion.

With the development of network technology, there is an increasing demand for storing video data over the network. As a result, surveillance systems that were previously centered around DVRs (Digital Video Recorders) have further evolved into NVR (Network Video Recorder) systems with network capabilities. NVR, which stands for Network Video Recorder, is the storage and forwarding component of a network video surveillance system. It is primarily responsible for functions such as accessing, storing, forwarding, decoding, and previewing network audio and video signals. In today's increasingly complex and widely applied surveillance scenarios, intelligence has become an inevitable trend in the development of video surveillance systems. Intelligent security monitoring is one such application of NVR intelligence. It utilizes advanced technologies and intelligent algorithms to enhance security, reduce monitoring workload, and provide real-time access, playing a crucial role in the field. They are suitable for various applications, ranging from home security to large-scale commercial and urban surveillance projects. With the constant advancement of technology, intelligent security surveillance systems will continue to evolve and improve, offering advanced features and greater convenience. Intelligent NVR can be utilized in security surveillance and, with algorithmic support, can achieve the following scenarios: Face Recognition Alarm: Comparative recognition of the target face can be performed through video or image streams. Fire Incident Visualization and Early Warning: Intelligent detection and identification of smoke and fire points, issuing early warnings before the fire spreads. Intrusion Detection and Alarm: The system can monitor an area and provide alerts for unauthorized intrusion by using object recognition and motion detection. Parking Space Vehicle Recognition: By using object recognition or license plate recognition, the system can detect and identify unauthorized or improperly parked vehicles (underground garages). Requirements Cases: A video surveillance system solution provider plans to launch a high-performance NVR (Network Video Recorder) device to meet the diverse monitoring needs of smart security applications. In the envisioned product positioning of this customer, this NVR can provide intelligent monitoring functions in various security surveillance scenarios, such as face recognition alarms, visualized fire hazard alerts, intrusion alarms, parking space vehicle recognition, etc. Unlike traditional NVRs, the implementation of intelligent monitoring functions requires AI computing power on the NVR's main control unit. This is because it needs to be able to run intelligent monitoring algorithms locally while performing traditional functions such as access, storage, forwarding, and decoding. Based on the above reasons, Forlinx Embedded recommends the FET3568-C SoM to customers as an ideal iteration tool for security back-end NVR devices. It adopts the RK3568 processor produced by Rockchip, featuring a quad-core Cortex-A55 architecture with a clock speed of up to 2GHz. Additionally, it integrates a 1 TOPS NPU, which enables lightweight local AI computing. It natively supports dual Gigabit Ethernet, which can be used for connecting network cameras, network communication, etc. It supports SATA 3.0 and PCIe 3.0, which can be used to connect mechanical hard drives or solid-state drives, enabling local storage of large video data capacity. It supports five different display interfaces: HDMI 2.0, eDP, LVDS, RGB Parallel, and MIPI-DSI. It also supports simultaneous and separate display on three screens, maximizing local preview and operation convenience. With the user-friendly model conversion tool RKNN-Toolkit, the FET3568-C allows for one-click conversion of popular architecture models such as Caffe, TensorFlow, TF-Lite, ONNX, PyTorch, Keras, and Darknet. This tool assists engineers in swiftly developing functions like face , object, action, license plate recognition, etc. Additionally, RK3568 supports various video input/output interfaces and offers hardware decoding of high-definition formats such as H.264, H.265, and VP9 at 4K resolution. It can decode multiple video sources simultaneously, making it highly compatible with NVR devices. Originally published at www.forlinx.net.