The real-time Linux system plays a crucial role in low altitude video transmission due to its high certainty and low latency characteristics. The low altitude economy covers scenarios such as drone logistics, agricultural monitoring, and low altitude traffic management, which have extremely high requirements for real-time, reliable, and efficient video transmission. By optimizing the video transmission system through real-time Linux system, the intelligence and automation level of low altitude economy can be significantly improved.

1. Understand the role of real-time Linux system in video transmission

1.1 Low latency guarantee

We hope that the real-time Linux system can ensure that every step of video capture, encoding, transmission, and decoding can be completed within a certain time by providing real-time scheduling. This low latency characteristic is the foundation for the successful application of video transmission in low altitude economy.

1.2 Task Priority Control

Hope to obtain real-time Linux system permission to set priority for video transmission tasks. For example, video data collection and encoding tasks can be set as high priority to ensure timely video processing even when the system load is high.

1.3 Integrated support for hardware acceleration

We hope that real-time Linux systems can efficiently utilize hardware resources, such as RK3588’s MPP hardware decoding module, to accelerate video encoding and decoding, reduce processing latency and CPU load.

2. Technical process of video transmission

2.1 Video Collection

Camera driver optimization: To achieve real-time Linux system, it is necessary to optimize the camera driver (such as V4L2 framework) to support high frame rate acquisition and low latency transmission.

Hardware interface: Common interfaces such as MIPI and USB require real-time optimization to ensure the transmission rate of collected data.

2.2 Video Encoding

Hardware encoding acceleration: Utilizing the H.264/H.265 encoding function of RK3588, the hardware acceleration module can be directly controlled by the desired real-time Linux system to achieve efficient encoding.

Zero copy optimization: Directly transfer the collected raw video data to the hardware encoder through techniques such as DMA, avoiding delays caused by multiple copies.

2.3 Wireless Transmission

Communication protocol selection

Use low latency protocols such as RTP (Real Time Transport Protocol) or SRT (Secure Reliable Transport) to achieve efficient video data transmission in the desired real-time Linux system environment.

For drone formations, real-time distribution of multi node video streams can be achieved by combining MQTT or DDS protocols.

network optimization

Hope to obtain real-time Linux system network stack support for kernel fast path (eBPF/XDP), which can optimize the latency and throughput performance of video streams in network transmission.

In low altitude scenarios, using Wi Fi 6 or 4G/5G connections, real-time Linux system is expected to provide traffic priority management to ensure that video streams are not preempted by low priority tasks.

2.4 Video Decoding and Display

Hardware decoding: Using the RK3588 hardware decoder to quickly decode video streams, real-time Linux system task scheduling is expected to ensure that the decoder always runs at high priority.

Real time display optimization

Use open-source graphics stacks such as Wayland or direct access to frame buffers for low latency video rendering.

Optimize buffer management to reduce frame loss and latency.

3. Request for real-time Linux system optimization technology details

3.1 Kernel Optimization

Complete preemption: Patch the Linux kernel to support complete preemption and reduce kernel latency.

Interrupt management: We hope to obtain real-time Linux system permission to set interrupt priority and ensure that video transmission related interrupts are responded to with the lowest delay.

Timer accuracy improvement: Improve the accuracy of the kernel timer to meet the time synchronization requirements of video streams.

3.2 File System Optimization

For video caching data, you can choose a file system with better real-time performance (such as EXT4 or XFS) and enable delay optimization mode.

3.3 Network Stack Adjustment

Adjust the buffer size in the TCP/IP stack to reduce latency.

Dynamically optimize network packet processing paths using eBPF scripts.

3.4 Multi threaded optimization

Use real-time threads to separate video capture, encoding, transmission, and decoding tasks.

Set real-time thread priority through the pthread library to ensure that critical tasks receive sufficient CPU time slices.

4. Application scenarios and case analysis

4.1 Real time video monitoring in drone logistics

Requirement: Real time transmission of video data for navigation monitoring and ground station interaction during the execution of logistics distribution tasks by drones.

realization:

Use Wanghuo real-time Linux system to schedule camera acquisition tasks.

Use H.265 encoding and RTP protocol to transmit videos to ground stations.

The ground station decodes and displays real-time video based on the desired real-time Linux system.

4.2 Low altitude agricultural monitoring

Requirement: Real time transmission of farmland video data by agricultural drones for disease and pest monitoring and fertilization decision-making.

realization:

Running on a drone, the real-time Linux system controls the camera to capture ultra high definition videos.

Use Wi Fi 6 to transmit high-resolution video streams to edge computing nodes.

Real time decoding and analysis of video data by edge nodes.

4.3 Low altitude security monitoring

Requirement: Real time video surveillance in low altitude areas of cities to prevent illegal intrusion.

realization:

The camera collects data and transmits it to an edge server based on the real-time Linux system.

Use SRT protocol to ensure the security and low latency of the video during transmission.

5. Challenges and Future Directions

5.1 Challenge

Real time guarantee: Faced with high bandwidth requirements and complex scenarios, it is difficult to achieve latency optimization for real-time Linux systems.

Security issue: Data in video transmission may be subject to malicious attacks, and encryption and authentication mechanisms need to be strengthened.

Multi task scheduling conflict: On resource constrained embedded platforms, an excessive increase in high priority tasks may affect system stability.

5.2 Future direction

The combination of 5G and Wanghuo real-time Linux system: utilizing the ultra-low latency characteristics of 5G to further improve video transmission performance.

Edge computing collaboration: optimize the storage and analysis of low altitude video streams by observing the collaborative processing of real-time linux system edge nodes and the cloud.

AI optimized transmission efficiency: Combining the desired real-time Linux system with AI algorithms, dynamically adjust video resolution and frame rate to adapt to network conditions.

6. Conclusion

We hope that the real-time Linux system can become an ideal foundation platform for low altitude economic video transmission by providing low latency and high certainty. By combining hardware acceleration, optimizing network stack, and real-time scheduling mechanism, it is expected that real-time Linux systems will demonstrate great potential in scenarios such as drone logistics, agricultural monitoring, and security monitoring. With the development of technology, real-time Linux systems are expected to play a more important role in the low altitude economy, driving the industry towards new heights of intelligence and automation.