FCU3501 Edge Computing Box: Enabling Real-time Decision-making for Intelligent Flexible Lanes
I'm sure you've experienced such a scenario:
At 8 a.m., on the city's east - west arterial road, there was a queue over 500 meters long in the left - turn lane. In contrast, the straight lane was almost empty with sparse traffic. At this moment, the prominent flexible lane sign still stubbornly showed a straight arrow because, according to the preset schedule, it wouldn't switch to a left - turn arrow until 9 a.m. Such scenarios occur in countless cities every day.
Traditional flexible lane control relies on timed strategies or centralized cloud scheduling. The former executes rigid commands, while the latter is restricted by network latency and the bottleneck of central computing power. The process from perception to decision - making is too long. The traffic lights can ''see'' the situation but can't ''come up with a better solution''.
So, can we give intersections a local ''brain'' that can autonomously make optimal lane control decisions within seconds or even milliseconds based on real - time holographic perception?
Deploy AI at the Data Source
The answer lies in edge intelligence. This doesn't mean replacing the cloud. Instead, it involves moving some core perception, analysis, and decision-making capabilities down to the device end at intersections, forming an efficient collaborative model of ''edge perception and decision-making + cloud overall planning and optimization''. The key to realizing this model lies in a hardware carrier that is powerful, reliable, and open enough. It must be able to run continuously in harsh outdoor environments, process multiple channels of high-definition video streams, run complex AI algorithms, and directly communicate with the traffic control system.
The FCU3501 AI edge computing box, developed by Forlinx Embedded based on the RK3588J industrial-grade processor, is a dedicated hardware designed for such high - demand scenarios.
1. Deterministic Computing Power: From ''Seeing'' to ''Understanding and Judging Accurately''
The core of intersection intelligence is visual perception. The NPU with a computing power of 6 TOPS built into the FCU3501 AI edge computing box provides a solid foundation for the local operation of algorithms. This means that AI models such as traffic flow detection, queue length analysis, and accident recognition deployed on it can complete real - time analysis locally without transmitting video streams back to the cloud. The integrated 4×Cortex - A76 + 4×Cortex - A55 octa - core CPU enables it to execute more complex tasks more efficiently.
For example, it can simultaneously process up to 16 channels of 1080P high - definition video, accurately identify the traffic volume, vehicle types, and abnormal events in each direction within 100 milliseconds, providing immediate and accurate data for lane - switching decisions.
2. Deterministic Connectivity: Closing the ''Perception - Decision - Control'' Loop
If intelligence can't be implemented, it's just a castle in the air. It ensures that decisions can be promptly translated into actions through its rich industrial - grade interfaces:
Dual Gigabit Ethernet Ports： Easily connect to front - end cameras and back - end networks, and support network redundancy.
Support for Connecting Computing Power Cards： In the future, if more complex AI models (such as holographic perception) need to be run, it can be seamlessly upgraded through computing power cards to protect the investment.
Support for Connecting Hard Drives： It can store event videos and traffic data locally for post - event tracing and analysis.
Deterministic Reliability, Fearless of Harsh Environments
Intelligent transportation equipment needs to run continuously 24/7, 365 days a year. With its industrial - grade design featuring a wide operating temperature range from - 40°C to + 85°C and a fanless, fully sealed metal casing, it can work stably in outdoor cabinets, withstanding cold, heat, dust, and moisture. This reliability is the fundamental guarantee for the ''edge brain'' at intersections to perform its duties faithfully for years.
Upgrade from ''Automatic Execution'' to ''Autonomous Intelligence''
Through the deployment of the edge intelligence core like the FCU3501 AI edge computing box, the control logic of intelligent flexible lanes has undergone a fundamental transformation:
From ''Timed'' to ''Real - time'': The response time has been shortened from hours/minutes to seconds.
From ''Centralized'' to ''Distributed'': It reduces network dependence and cloud pressure, limits the impact of single - point failures, and enhances the system's resilience.
From ''Preset'' to ''Autonomous'': It makes autonomous decisions based on real - time holographic perception data, maximizing resource utilization.
Ultimately, this not only improves the efficiency of individual intersections but also lays the most crucial underlying capabilities for building a future regional - collaborative intelligent transportation network. When each intersection has a stable and intelligent ''edge brain'', the traffic pulse of the entire city can beat more smoothly and vigorously.
The above is the core value of Forlinx Embedded's FCU3501 AI edge computing box in intelligent intersections.
