TeamGRIT offers
real-time data processing and
robotic remote control solutions.
Ultra-Low Latency
Data Transmission
Stable Real-Time Transmission Speed below 200ms
TeamGRIT has achieved ultra-low latency data transmission below 200ms through its proprietary RSSP (Real-time Simple Streaming Protocol). This represents a groundbreaking speed improvement compared to existing technologies, offering innovative solutions in various fields that require real-time performance.
Real-Time Control and Scalability with
Ultra-Low Latency Data
By ensuring seamless and stable data transmission, we deliver reliable services even in environments where real-time performance is critical. Our solution also enables bidirectional transmission of control signals, facilitating the development of real-time remote control and feedback systems. With broad compatibility across various sensors and devices, it offers high scalability and can be applied across multiple industries.
Remote Robot Control and
Real-Time Data Transmission
With remote robot control, precise operation is achieved through real-time exchange of robot movements and sensor data. Additionally, advanced video streaming technology ensures uninterrupted transmission of high-definition video, making it ideal for applications such as video surveillance and broadcasting. Real-time data collection and control from various IoT devices enable wide-ranging use cases, including smart factories and smart cities.
Plugin Based on
a Single Protocol
Eliminating the Complexity of Existing Protocols
Previously, engineers needed to understand various protocols such as WebRTC, RTSP, and MQTT. However, TeamGRIT's RSSP protocol unifies these functionalities into a single solution, significantly enhancing development and operational efficiency.
Integrated Robot and
IoT Control
By unifying various robot control systems, such as CAN and ROS, into a single protocol, we enhance both system development and operational efficiency. Additionally, the RSSP protocol enables seamless integration of IoT devices, eliminating the complexity of managing multiple protocols. This creates an optimized environment for smart system operations and allows for easy application across diverse industries.
Efficient
Media Streaming
By transmitting real-time video and audio data through a single protocol, a stable and seamless media streaming system can be implemented. This ensures efficient data transmission across various fields, including surveillance, broadcasting, and remote meetings, without requiring multiple protocols. The system is simple to apply and easily deployable.
Bidirectional Transmission of
Multimodal Data
Support for Various Data Types
Real-time bidirectional transmission of various data types such as video, images, text, and audio, enriching the user experience.
Real-Time Multi-Data
Transmission and Interaction
It enables the seamless transmission of various data formats, including video, images, text, and audio and more. Real-time bidirectional communication supports both data transfer and the exchange of control signals and feedback, ensuring smooth interaction. Customizable services allow real-time data delivery tailored to specific needs. With a codec-independent design, the system flexibly integrates the latest codecs for efficient, high-quality data transmission.
Real-Time Fusion of
Heterogeneous Sensor Data
with AI Models
Enhancing AI Analytical Capabilities
Real-time collection of various sensor data is integrated with AI models to maximize AI analytical capabilities.
Real-time Data Processing and
Decision Making through AI Integration
Real-time processing of various sensor data enables immediate situational assessment and response. Integration with AI models, including vision-based systems, enhances analysis accuracy and refinement. This data-driven approach supports efficient decision-making, helping to establish an optimal operational environment.
Autonomous Systems and Smart Automation
through AI Integration
Integrating sensor data from LIDAR, cameras, and other sources with AI models enhances the safety of autonomous driving systems. Combining robot sensor data with AI also improves task performance and autonomy. In smart factories, AI-driven sensor data optimization boosts production efficiency and reduces defect rates, demonstrating its versatility across various industries.
