In 2023, AI video surveillance technology will usher in significant developments and results, bringing more intelligent and efficient solutions to the security field and other industries. Among them, edge AI development is also very significant. The widespread application of AI in edge computing will enable devices to process data locally instead of relying on cloud servers, allowing for faster response times and stronger privacy protection.
LiteCVR can support device access through the national standard GB28181, RTMP, RTSP/Onvif protocols, as well as Hikvision Ehome, Hikvision SDK, Dahua SDK, Huawei SDK, Uniview SDK, Lecheng SDK, and EZVIZ SDK, and can be distributed externally. Video streams in RTSP, RTMP, FLV, HLS, WebRTC and other formats. The platform is highly open, has strong compatibility, and can support flexible expansion and third-party integration. We also provide a wealth of API interfaces for users in need to freely call, integrate, and secondary develop.
Recently, we have updated the API interface documentation of the LiteCVR video platform. When obtaining stream information, we have added video frame rate, encoding format and other information, as shown below:
Users can obtain video resolution, audio and video encoding format, push bit rate, push start time, frame rate and other information through interface calls, as shown in the figure:
Among them, the frame rate is calculated by counting the number of frames refreshed in one second:
The addition of new functions in LiteCVR helps users quickly and clearly obtain more information about video streams through the interface.
Forecast of future development trends of AI technology:
- Advances in Natural Language Processing (NLP): Continued advances in NLP may lead to more sophisticated language models, enable better conversational AI, and better understand the context of human communication.
- Integration of AI and robotics: Tighter integration of AI and robotics will lead to more complex and autonomous robotic systems, with applications covering manufacturing, logistics, and medical care.
- AI applications in the medical field: AI applications in the medical field are expected to make greater progress, involving medical image analysis, drug development, personalized medicine, and more accurate predictive analysis for disease diagnosis and treatment planning.
- AI applications in climate science: Using AI to analyze climate data, predict environmental changes, and develop solutions to mitigate the effects of climate change will become an important direction for research and practice.