reComputer AI Industrial R: The World’s First Mini AI Computer Based on Raspberry Pi CM5
Introduce the reComputer AI R Series, an AI Computer that combines Raspberry Pi CM5/Pi 5 with the Hailo-8 NPU for powerful edge AI capabilities. With versatile applications in smart security, retail analytics, and industrial automation, it delivers high-performance AI processing at the edge.
Seeed launched a Raspberry Pi CM5/Pi 5 AI Box with Integrated Hailo NPU
Since last year, when Raspberry Pi released their AI kit and AI camera, we’ve seen numerous cool AI applications pop up. From basic stuff like running MobileNet and YOLO to even attempting local LLMs – it’s amazing what people are doing on Raspberry Pi AI. With the Pi 5 and CM5 release bringing more power to the table, Seeed Studio launched something special – a mini AI PC series based on Raspberry Pi CM5/Raspberry Pi 5 – reComputer AI Industrial R/AI R. Actually, reComputer AI Industrial R is the world’s first CM5-based AI computer!
The reComputer AI R Series represents a significant leap in edge AI capability, built around Raspberry Pi‘s most powerful computing platforms. At its core, this compact device integrates either the Raspberry Pi Compute Module 5 (CM5) or the Raspberry Pi 5, delivering substantial processing power for industrial or commercial applications. What truly sets it apart is the integrated 26 TOPS Hailo-8 NPU – a dedicated AI accelerator whose performance can be scaled according to specific project requirements.
We offer two tailored versions: The industrial-grade CM5 model (reComputer AI Industrial R) withstands demanding environments like factories and smart buildings, while the commercial-grade Pi 5 version (reComputer AI R) delivers accessible AI power for cost-sensitive scenarios. This strategic dual-approach maintains our commitment to both robustness and accessibility in edge AI deployment.
One of the key advantages of integrating Raspberry Pi with an NPU like the Hailo-8 lies in the combined power of real-time performance and privacy. By deploying AI at the edge, sensitive data stays on-device, ensuring privacy without the need to upload information to the cloud. This makes the reComputer AI R Series especially suited for environments where data confidentiality is critical.
Furthermore, with the Hailo-8 NPU, the system can process data with sub-millisecond latency, enabling instant decision-making for a wide range of industrial and commercial applications. Whether it’s object detection, anomaly detection, or real-time analytics, the combination of Raspberry Pi’s reliable computing power and the NPU’s AI acceleration ensures responsive and effective results — making it an ideal solution for demanding edge AI scenarios.
What are the Real-World Applications of a Raspberry Pi AI Box?
Real-World Applications Made Simple
The reComputer AI Industrial R is designed for a wide range of real-world applications. Below, we’ll briefly introduce two common use scenarios where it truly shines.
Smart Security
IP cameras feed live streams through NVR devices to the reComputer AI Box, where the integrated 26 TOPS Hailo NPU processes multiple video feeds simultaneously, detecting suspicious behavior across multiple cameras in real-time. Crucially, the system filters false alarms to trigger context-aware alerts only for critical events, like unauthorized entries into restricted zones, while generating actionable video analytics such as people counting and dwell-time mapping.
All processing occurs locally: Raw footage never leaves the premises, slashing bandwidth demands by 70%+ while ensuring compliance with data privacy regulations. The AI Box further enables cross-camera intelligence—searching for specific attributes (e.g., “locate all persons in red shirts”)—and integrates directly with access controls and alarm systems. By transforming passive surveillance into proactive threat response, security teams gain real-time intrusion detection, evidence snapshots, and automated system lockdowns—all without cloud dependencies.
Retail Analytics
Store cameras stream live footage directly into the reComputer AI Box, where edge processing transforms raw video into actionable analytics before uploading refined data to the cloud platform. This integrated workflow enables comprehensive retail intelligence: The system maps customer flow patterns—tracking entry/exit paths and peak-hour densities to reveal behaviors like 70% of customers turning right upon entry—while generating interactive heatmaps that visualize product engagement hot zones. Simultaneously, it calculates conversion metrics (e.g., 45% purchase rates at specific displays), monitors queue dynamics with real-time staff alerts when lines exceed five people, profiles visitor demographics (such as identifying families as 60% of weekend shoppers), and enhances security through automated loss prevention by flagging suspicious loitering in blind spots. All analytics occur at the edge, ensuring bandwidth efficiency and immediate responsiveness without cloud dependency.
How is the AI Performance of reComputer AI Industrial R (CM5+Hailo8)?
We have provided several basic examples to verify its AI capabilities. A simple USB camera was connected, with video transmitted directly to the box, which is capable of processing all data in real-time. It runs YOLOv8, one of the most popular object detection models. Supporting plug – and – play functionality, it can recognize common objects, such as those demonstrated in our previous live stream(Making Next Gadget | See It Live: Raspberry Pi CM5 AI Box Launch + Hands-On Tutorial Updates!): human recognition, pose recognition, and cat recognition, with a recognition frame rate of approximately 23 FPS.
The Moment AI Became Tangible
During our live demonstration, a simple USB camera streamed footage of “Didi” — Seeed’s office cat — directly into the reComputer AI Box running YOLOv8 object detection. As shown in the video, the system not only detected and identified “Didi” as labeled “Cat” but also tracked Didi’s movements with near-zero latency (Immediate detection feedback), outputting results at around 30 FPS (Frames Per Second). At 30 FPS, our eyes perceive motion almost as smooth and real-time.
Benchmark Insights: The Real-World Performance of reComputer AI R in Power, Efficiency & Multi-Camera Loads
The NPU Effect: 234x Performance Leap
In visual AI, frame rate is more than just a technical specification—it’s a key indicator of system performance. For AI systems, this frame rate shows how many frames the system can process and produce per second, factoring in pre-processing, inference, and post-processing.
- Raspberry Pi 5: 0.62 FPS
- Pi5/CM5 + halio8: 145 FPS
This significant acceleration comes from the Hailo NPU.
If Raspberry Pi’s legacy is ultra-low power consumption, making it the preferred choice for IoT applications, adding AI and having it perform heavier tasks doesn’t break that promise. – a dedicated CNN processor fundamentally different from general-purpose GPUs. While solutions like Google Coral cap at 4 TOPS, Hailo’s architecture delivers up to 26 TOPS, transforming previously impossible real-time applications into simplified deployments.
Scaling Up: Multi-Stream Efficiency
But real-world deployments rarely use single cameras. While a high frame rate is essential for real-time performance, it’s not a fixed number. Various factors, such as camera resolution, pixel count, and batch size, can all impact the system’s performance.
This means that achieving optimal performance in visual AI depends not only on hardware acceleration but also on balancing these variables to maintain smooth, real-time results, proving its viability for warehouse monitoring, retail analytics, and factory safety systems.
The Power Paradox: Higher Performance, Lower Consumption
If Raspberry Pi’s legacy is ultra-low power consumption, making it the preferred choice for IoT applications, adding AI and having it perform heavier tasks doesn’t break that promise.
| Configuration | FPS | Power |
| Raspberry Pi 5 | 0.519 | 10.12W |
| Raspberry Pi 5+ AI Kit | 93.42 | 8.45W |
Why lower power? The NPU offloads compute-intensive tasks from the CPU. Less CPU utilization → lower power draw → higher sustained performance. This synergy makes the Pi 5 + NPU combination not just powerful, but efficiently powerful.
How is this reComputer AI R series Designed and Developed?
How can we efficiently integrate a Raspberry Pi, Hailo NPU, SSD, 4G, LoRa, and more into a palm-sized device, while balancing the heat dissipation of the notoriously high-heating Raspberry Pi 5 series? This posed a significant challenge for our R&D efforts.
After relentless efforts and problem-solving, our team conducted multiple rounds of optimizations on PCB wiring and airflow paths, and picked out the best solution from countless thermal designs. The result is this proud Raspberry Pi AI box that now sits neatly on the desk.
Compact Design, Industrial Durability
Size & Build
- Dimensions: 130mm*93mm*55.5mm
- CPU: Raspberry Pi Compute Module 5
- AI Processor: Hailo-8
- RAM: 8GB/16GB
- eMMC Storage: 32GB
- Interface: Ethernet, 2x USB 3.2, 1x USB 2.0, 2x HDMI 2.0
- Wireless: Wi-Fi 2.4/5.0 GHz, BLE 5.0, 4G Cellular: 4G LTE
- Operating Temperature: -20 ~ 65°C
Expansion capabilities are engineered for real-world deployments: An M.2 slot supports high-speed NVMe SSD storage, while a mini PCIe slot accommodates connectivity modules like 4G or LoRa. For vision-based applications – a primary use case highlighted in our demonstrations – it features USB 3.0 ports and Gigabit Ethernet, providing flexible support for both USB and IP cameras right out of the box.
This powerful AI box, built on the Raspberry Pi CM5, combines a Hailo-8 AI accelerator. Designed for edge AI applications, it delivers real-time inferencing with low latency, making it an ideal choice for demanding tasks like video analytics, industrial automation, and more.
Thermal Innovation
Despite its compact size, about the size of a soda can, this AI box offers outstanding heat dissipation, ensuring stable performance even under heavy loads. It supports a wide operating temperature range from -20°C to 65°C, making it suitable for challenging environments, whether it’s outdoors or in industrial settings.
To ensure reliable and efficient performance, especially under heavy workloads, reComputer AI Industrial R features a sophisticated thermal management system that combines multiple heat dissipation solutions. These solutions were meticulously designed and evaluated using advanced simulations, considering key factors such as:
- Radiator structure and copper tube layout optimization
- PCB device layout optimization
- Airflow path optimization
Each solution was thoroughly tested for temperature distribution and cooling efficiency, ultimately leading to the selection of the most effective thermal solution. One of the key highlights of this design is the efficient component placement. The Raspberry Pi CM5 and Hailo AI accelerator, which generate the most heat, are strategically positioned at the top of the PCB. This minimizes the thermal path to the radiator, significantly improving heat conduction and overall cooling efficiency.
Additionally, the optimized radiator design integrates an active cooling fan placed in a position that maximizes airflow to the heat-generating components. With fins located at strategic areas and high airflow zones on both sides of the PCB, heat dissipation is significantly enhanced, ensuring that the system operates at peak performance without overheating.
Get Started with reComputer AI R Series
The reComputer AI R Series brings the power of cutting-edge AI processing to edge computing, offering a robust, scalable, and efficient solution for a wide range of applications. Whether you’re deploying real-time AI for industrial automation, smart surveillance/retail/building, or autonomous systems, this series is designed to meet the performance demands of today’s intelligent edge solutions.
With features like high-performance AI acceleration, efficient heat dissipation, and flexible connectivity options, the reComputer AI R Series makes it easier than ever to integrate powerful AI into your projects. Its compact form factor, combined with optimized thermal and power management, ensures that the device can run reliably in diverse environments.
Ready to maximize your AI applications? The reComputer AI R Series handles the heavy lifting, letting you focus on innovation. Start building today!
In the next blog, Seeed Studio will showcase more about the integration of reComputer AI Industrial R with software ecosystems and provide additional demo videos highlighting its features and functions. Stay tuned for more in-depth insights and updates on the reComputer AI R series!
Learn more about reComputer AI R series:
Making Next Gadget | See It Live: Raspberry Pi CM5 AI Box Launch + Hands-On Tutorial Updates!
Making Next Gadget | From Pixels to Meaning: How Does Raspberry Pi CM5 AI Box ‘See’ and Interpret?
Making Next Gadget: Master AI with Raspberry Pi, Power Smart Retail Solutions – YouTube
Making Next Gadget: AI Boosted RPi for Real World Applications
Learn more about how to use your AI kit with Raspberry Pi:
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