China service robot industry: Guangdong to further support AI firms
China service robot industry: Guangdong to further support AI firms
By ZHENG CAIXIONG in Guangzhou | China Daily | Updated: 2025-04-11 09:05
South China’s Guangdong province will spare no effort to support artificial intelligence and robotics companies in achieving breakthroughs in technology industrialization, product marketing and service commercialization in the coming months, a senior official said.
The latest move aims to continuously provide high-quality and affordable products and services for local companies as well as households, accelerating the empowerment of thousands of industries with AI and deepening the application of “robot+” scenarios, said Qu Xiaojie, deputy director of the Guangdong Department of Industry and Information Technology.
“Meanwhile, Guangdong, a global innovation center, sincerely welcomes scientists, entrepreneurs and young talent from around the world in the fields of AI and robotics to invest and develop the AI and robotics industry in the province,” he said.
Qu said that his department would ensure coordination of resources, cultivation of enterprises, industrial agglomeration, ecological optimization and promotion of exchanges to support innovation and development by enterprises in the AI and robotics industry in the province, which is also a major production base in the world.
Qu made the remarks at a news conference in Guangzhou, the provincial capital, on Wednesday.
Qu said Guangdong has potential to develop the AI and robotics industry, as the Guangdong-Hong Kong-Macao Greater Bay Area combines the advantages of electromechanical and digital intelligence technology, with a complete AI and robotics industry chain, complete support facilities, fast response, high quality, good service and excellent ecology.
The province, an economic powerhouse of the country, has become a mecca for global talent, technology and capital, he said.
Guangdong has excellent computing chips like the Huawei Ascend and self-developed general-purpose models like Tencent Cloud, according to Qu.
And the eight major models in the AI industry of Guangdong have been preliminarily applied in related fields and achieved significant results, he added.
Wang Jian, general manager of Tencent Cloud Guangdong province, said Tencent Cloud’s AI large model has been implemented in more than 30 industries, including government affairs, retail, finance and industry.
Tencent will continue to lower the technological threshold and focus on scenario implementation, using its “useful, easy-to-use, and reliable” AI capabilities to help Guangdong’s AI and robotics industry enter into an era of global, full-time and all-scenario intelligence, he said.
“And we have now launched Tencent Cloud Intelligent Computing Suite by integrating high-performance computing, storage, networking, acceleration suite, cloud native intelligent scheduling and orchestration capabilities, to help customers manage their economic accounts with computing power,” Wang said.
Hao Shengwei, marketing director of Huawei Ascend Computing Business, said Huawei Ascend has been focusing on key technologies and continues to innovate by combining computing, storage, networking and other capabilities.
“It has continuously improved its hardware and software capabilities, developed many fusion operators, and opened up many basic software and capabilities to partners for them to create their own applications and operators,” he said.
Hao said more than 80 partners have now built their large model application all-in-one machines based on Ascend’s computing power base, which have been applied in more than 200 enterprises.
“Many companies have built their own technology and computing power based on Ascend, and we will continue to make AI truly enter various industries,” he added.
Service Robots in China: Innovation, Market Growth, and Global Leadership
Service Robots in China: Innovation, Market Growth, and Global Leadership
1. Market Overview: A Global Powerhouse
China has dominated the global robotics market since 2015, with service robots emerging as a key growth driver. Key statistics:
| Metric | 2023 Data | Projection (2028) | Source |
|---|---|---|---|
| Service Robot Market Size | ¥60 billion ($8.3B) | ¥150 billion | :cite[4]:cite[8] |
| Home Robot Penetration | 10% (urban) | 25% | :cite[4] |
| Export Revenue | ¥1.51B ($208M) | ¥4.2B | :cite[2] |
1.1 Growth Drivers
- Aging Population: 264M Chinese aged 60+ by 2025 needing elderly care robots :cite[4]
- Smart City Initiatives: 500+ cities deploying public service robots :cite[8]
- Manufacturing Evolution: 14.9% CAGR in mobile robots for logistics :cite[8]
2. Technological Breakthroughs
Image: R&D at Shenzhen Robotics Innovation Center (Source: China Daily)
2.1 Core Innovations
- 5G Integration: 1ms latency enables real-time control in hospital delivery robots :cite[8]
- Multi-sensor Fusion: Pudu Robotics’ VSLAM technology achieves 99.2% navigation accuracy :cite[2]
- Edge AI Computing: Cloud Whale’s J4 vacuum processes 15 TOPS locally for rapid decision-making :cite[2]
3. Sector-Specific Applications
3.1 Healthcare Revolution
Image: Disinfection robots at Wuhan Union Hospital (Source: Xinhua)
- 23,000+ hospital delivery robots deployed nationwide :cite[4]
- 40% reduction in nurse workload through AI triage systems :cite[8]
3.2 Retail & Hospitality
- 7,500+ restaurants using PuduTech’s BellaBot servers :cite[2]
- Hilton China’s 98% guest satisfaction rate with concierge robots :cite[4]
4. Global Expansion Strategies
Image: Canton Fair 2025 Service Robot Zone (Source: Sohu) :cite[1]
- 124 international trade delegations at 137th Canton Fair robotics zone :cite[1]
- Localization success: Yarbo snow robots capture 38% of North American market :cite[2]
- EU certification: Keenon Robotics meets 60+ country standards :cite[2]
5. Challenges & Future Outlook
5.1 Key Challenges
- 30% higher R&D costs vs international peers :cite[8]
- Semiconductor supply chain vulnerabilities :cite[7]
5.2 2025-2030 Predictions
- Human-robot collaboration: 70% of new models will feature cobot functions :cite[8]
- AI ethics framework: National standards under development :cite[7]
Conclusion
China’s service robot industry combines massive domestic demand with cutting-edge innovation, positioning the country as the global leader in intelligent automation solutions. With continued government support and industry collaboration, Chinese robotics firms are set to redefine service delivery worldwide.
Chinese robotics industry: Spotlight on AI as future game changer
Spotlight on AI as future game changer
China fostering own vision of development through reliable, efficient application of artificial intelligence tools across industry sectors
Delegates and visitors to the Zhongguancun Forum, a key technology event held in Beijing recently, were in for a surprise when they arrived at the venue late last month.
As they stepped in, they were greeted not by ushers in uniform, but by a coordinated team of robots that mimicked human expressions, answered queries and translated conversations in real time.
In the shadow of a series of bullying (tariffs) imposed by the Trump administration earlier this month, China is doubling down on what may be its most potent counterstrike: AI. From breakthrough chips to frontier models rivaling the West’s best to humanoid robots, China’s AI breakthroughs could stand out to be a potential game changer, industry experts said.
Elsewhere at the venue, a robot with a friendly voice and precise movements guided guests to a coffee corner where a robotic barista brewed fresh beverages. And, once the coffee was ready, another humanoid robot delivered it directly to the guest.
While other robots played chess with visitors or displayed their brush calligraphy skills with serene focus, some robotic dogs darted easily through the crowd of visitors.
This was just one of several events held last month where artificial intelligence took center stage.
In March, China saw a series of major events, including the two sessions, or the annual gatherings of the country’s top legislature and political advisory body; the Zhongguancun Forum; and the China Development Forum in Beijing, as well as the Boao Forum for Asia in Hainan province.
In fact, several AI-related panel discussions at the Boao and Zhongguancun forums saw packed houses, with attendees filling up every seat and some even standing to hear out the participants.
This overwhelming interest in AI mirrors the prominence of the nascent sector across the nation, displaying a vivid picture
Industry experts said China is fostering its own vision for the development of AI through the reliable and efficient application of AI tools across a wide range of industries, a path that differs wisely from that of the United States.
Turing Award winner Joseph Sifakis said at the Zhongguancun Forum that China is crafting its own AI vision, distinct from that of the US.
“China has a solid and extensive industrial base and a unified domestic market. This enables the country to develop more reliable AI solutions that better align with the needs of the real economy, especially in the long-awaited transition to autonomous driving,” he said.
Sifakis noted that China’s strong industrial foundation, in particular, gives it an edge while industries such as self-driving vehicles, smart cities, smart factories and intelligent farms present more opportunities. “If developed well, (all these) will give China a dominant position in industrial AI,” he said.
Kai-Fu Lee, a prominent AI expert and chairman and CEO of investment company Sinovation Ventures, said China has reached its “DeepSeek moment”. He predicted that 2025 would mark a breakout year for AI applications and large-scale model deployment in China.
Lee recalled that about nine months ago, he had expressed frustration over China’s lack of a “ChatGPT moment”, as promising Chinese AI models at the time failed to stand out and spark nationwide adoption.
“However, DeepSeek has changed that landscape. Its success has awakened the Chinese market, ushering in a new AI era for the country,” he said.
According to Lee, DeepSeek’s rise proves that “closed-source AI has no future”, and only open-source development will drive greater progress.
“As AI scaling laws shift from the pretraining stage to the inference stage, AI applications will accelerate exponentially this year,” he said.
Scaling laws describe how the performance of AI systems improves as the size of the training data, model parameters or computational resources increase.
Kuang Ziping, founding partner of Qiming Venture Partners, a toptier Chinese venture capital firm, echoed that sentiment.
While the first generation of AI saw fragmented innovation, the second generation — dubbed “AI 2.0” — will be built on infrastructure, scalability and real-world application, he said.
“There’s still a huge gap in foundational infrastructure investment,” Kuang said. “But the application layer is poised for explosive growth.”
From smart education and autonomous driving to embodied intelligence and hardware, he said the sectors that successfully integrate AI will define the future.
Zhu Xiaohu, managing partner at GSR Ventures, emphasized that generative AI must prioritize one principle above all — application is king.
Startups, he said, must embrace open-source ecosystems and rapidly iterate their products in vertical industries. The most effective businesses, he predicted, will not rely on AI alone, but on “AI plus human” hybrid models that combine intelligence with nuanced delivery capabilities.
As excitement around AI innovation builds in China, it also collides with geopolitical headwinds, especially after the nation, a major trading partner of the US, was hit with several rounds of so-called reciprocal tariffs since April, in addition to a 20 percent tariff imposed earlier this year.
Last month, the US also added dozens of additional Chinese entities, including the Beijing Academy of Artificial Intelligence and tech firm Inspur Group, to its export restrictions list.
But, the world is big enough for hundreds of countries, including the US and China, to codevelop AI, and Washington’s sanctions on high-tech sectors will only steel Beijing’s resolve to drive homegrown innovations, said industry experts and company executives.
During a panel discussion at Boao Forum for Asia, Zeng Yi, a member of the United Nations’ high-level advisory body on AI and a researcher at the Chinese Academy of Sciences’ Institute of Automation, said: “The future of AI is not decided by a handful of countries, but by nearly 200 countries and regions. The world is big enough to embrace both the US and China to codevelop AI.”
Zheng Yongnian, dean of the School of Public Policy at the Chinese University of Hong Kong (Shenzhen), criticized as “unwise “the inclusion of Chinese companies in restrictive measures aimed at hindering China’s AI progress.
“China possesses significant advantages in application scenarios, with the government actively promoting the AI Plus strategy to expedite technological implementation. US sanctions on technologies have, paradoxically, spurred China to intensify investments in these areas and foster indigenous innovation,” Zheng said.
“If China’s AI technologies continue to evolve at the current pace, the US might find itself relying on China’s original innovations in certain sectors within 10 to 15 years,” he added.
Carl Fey, a professor of strategy at BI Norwegian Business School, said that while US tech restrictions may cause short-term pain for China, they will ultimately compel the latter to fortify its technological base and sharpen its global competitiveness.
Fey warned that measures like tariffs and export bans not only slow global tech progress, but also backfire by accelerating domestic innovation.
A group of experts cited Deep-Seek as a case in point — a low-cost, open-source AI model that is transforming the industry landscape. DeepSeek’s accessible architecture enables rapid deployment, and widespread use may reshape the AI future globally, a vision where AI, like water or electricity, becomes a basic utility available to everyone.
Jiang Xiaojuan, a professor at the University of Chinese Academy of Social Sciences, said that Deep-Seek is breaking monopolies and ushering in a new era of vigorous competition, converting technical know-how into industrial might.
“In a competitive market, these challenges will naturally be resolved by the forces of the market itself,” Jiang said.
Gao Xuefeng, founder and CEO of AI data infrastructure company Fabarta, said that after DeepSeek’s breakthrough, many Chinese companies no longer hesitate to invest in AI.
“Every few months, new technological advancements emerge. Companies can’t afford to wait; they must integrate AI into their business and industry now,” Gao said, adding that every sector in China can be re-imagined through AI in the coming years.
Amid rising AI enthusiasm, Wang Zhongyuan, head of the Beijing Academy of Artificial Intelligence, a leading nonprofit AI institute, said that DeepSeek has indeed delivered impressive results, proving that China can train large-scale AI models parallel to ChatGPT 4 despite limited computing power.
Regarding artificial general intelligence, in which an AI system can match or exceed the cognitive abilities of humans in any real-world task, Wang said that the industry is still far from achieving such capabilities. “I think we are still at least five to 10 years, or even longer, from reaching that level,” he added.
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Top 9 Features of DJI Dock 3
Rise to Any Challenge
DJI EnterpriseFebruary 27, 2025
DJI is excited to introduce DJI Dock 3, our first “Drone in a Box” solution with vehicle mounting support, enabling 24/7 remote operations in any environment. Designed to meet the needs of users across public safety, emergency response, construction and inspection organizations, Dock 3 takes remote drone deployment to the next level.
Inside the dock, the Matrice 4D Series comes equipped with the same high-performance cameras as the DJI Matrice 4 Series—but with enhanced flight performance and IP-rated protection for reliable operation in harsh conditions. Additionally, the M4D and M4TD are compatible with the DJI RC Plus 2 Enterprise, allowing for standalone use and greater operational flexibility.
Contact us if you want to inquire about purchasing or to apply to become a DJI Dock Dealer or DJI Ecosystem Partner.
DJI Dock 3
1. Built for Extreme Environments
The DJI Dock 3 is designed to endure challenging conditions, ensuring uninterrupted performance in even the harshest environments. It can handle extreme heat with resistance up to 50°C (122°F) and remains operational in temperatures as low as -20°C (-4°F) while offering a preheating function for conditions as frigid as -30°C (-22°F).
Its weatherproof design features IP56 protection for the dock and IP55 protection for the Matrice 4D Series drones,[1] making them both dust- and water-resistant. Additionally, the Matrice 4D Series is equipped with low-noise, anti-icing propellers, ensuring reliable flights even during freezing rain or in winds up to 12 m/s (27 mph). This unparalleled reliability makes the Dock 3 an essential solution for industries such as renewable energy, maritime surveillance, and mining operations, delivering dependable performance in all-weather scenarios year-round.
DJI Dock 3 in Freezing Environment
2. Dual-Drone Rotation for Continuous Operations
DJI Dock 3 enables continuous drone operations through its innovative dual-dock deployment system.[2] With two docks installed at a single location, drones can rotate between missions, eliminating downtime and ensuring continuous functionality.
Intelligent task management ensures safe transitions between drones with a specially designed takeover pattern that prevents collisions and maintains operational efficiency. Additionally, the system is complemented by cloud-based management through DJI FlightHub 2, allowing remote mission scheduling and monitoring, which reduces the need for on-site personnel.
This advanced functionality makes the DJI Dock 3 an invaluable solution for industries like security, energy utilities, and large-scale agriculture that require constant aerial monitoring.
3. Mobile Vehicle-Mounted Deployment
The DJI Dock 3 is DJI’s first dock designed to support mobile vehicle-mounted deployment,[3] making it ideal for temporary use in dynamic scenarios like search and rescue missions, disaster relief operations, or long-distance inspections. Optimized for vehicle-mounted deployments, the Dock 3 supports horizontal calibration or cloud-based calibrations using DJI FlightHub 2 to remotely program aerial missions. This remarkable flexibility redefines the possibilities for drone applications in unpredictable environments.
Dual-Drone Rotation and Mobile Vehicle-Mounted Deployment
4. Fixed Deployment with Extended Reach
The DJI Dock 3, paired with the D-RTK 3 Relay Fixed Deployment Version [4], offers enhanced transmission capabilities for operations up to 25 km. It ensures stable video and satellite connectivity, improving takeoff and landing reliability, even in complex environments like high-rise areas or remote sites.
Mounting the D-RTK 3 Relay Fixed Deployment Version on rooftops or near communication towers maximizes signal quality [5], while in factories, mines, or agricultural areas, it ensures full coverage—especially in locations where human access is limited or unsafe.
Fixed Deployment of DJI Dock 3 on the Roof
5. Matrice 4D Series Compatibility & Standalone Use
The DJI Dock 3 is fully integrated with the Matrice 4D and Matrice 4TD drones to deliver precision performance. Designed for water and dust resistance, these drones offer extended flight times and seamless compatibility with DJI RC Plus 2 Enterprise for standalone operations.
- Camera Capabilities: With the same high-performance cameras as the DJI Matrice 4 Series, these drones offer wide-angle, medium telephoto, and telephoto lenses up to 48MP.
- Flight Efficiency & Advanced Obstable Sensing: With 47 minutes [6] of hover time and up to 54 minutes [7] of flight, the drones maximize efficiency. LiDAR and millimeter-wave radar enable precise obstacle detection, even for thin objects like power lines.
- Standalone Use with Airborne Relay Function: Paired with the DJI RC Plus 2 Enterprise, the Matrice 4D/4TD supports an airborne relay function.[8] One drone flies high as a relay, extending the range of another. It auto-aligns for smooth video transmission, even without 4G or in obstructed areas.
With its cutting-edge imaging, extended range, and advanced sensing, the Matrice 4D and 4TD redefine drone operations in construction, energy, emergency response, and public safety—whether deployed with DJI Dock 3 or used in standalone missions.
Matrice 4D Series Paired with the DJI RC Plus 2 Enterprise (Standalone Use)
6. Advanced Intelligent Features with DJI FlightHub 2
FlightHub 2 enhances drone management with smarter and more efficient tools. The new Intelligent Recognition allows drones to detect and capture images or videos of subjects, vehicles, vessels, and infrared temperature anomalies, sending real-time notifications to operators. The feature Smart Tracking can quickly track these elements for efficient follow-up review.
Intelligent Change Detection helps periodically analyze changes in an area, making it invaluable for environmental protection, disaster relief and structural monitoring. Additionally, the Virtual Cockpit provides a remote control interface with “Mouse Look” for fast and precise camera adjustments. These advanced features streamline operations, reduce workload, and enhance accuracy.
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DJI FlightHub 2
7. Security and Compliance
DJI prioritizes the highest standards of data security and flight safety in its remote drone systems.
- Data Security: DJI FlightHub 2 is ISO 27001 certified by BSI, ensuring its design, development, and services meet high information security standards.
- Custom Permission Management: DJI offers an on-premise version of FlightHub 2, keeping customer data secure in an offline environment.
- Flight Safety: DJI Dock 3 features a built-in flight termination system (FTS) with an independent control link, meeting MOC2511 requirements. It also supports third-party safety integrations, like parachutes.
- C6-Label (Europe): DJI’s FTS module ensures the Matrice 4D Series stays within its operational volume, preventing threats to airspace and ground safety. The FTS can be triggered manually or automatically if the drone breaches its geofencing boundary.
8. Comprehensive Accessories for Enhanced Operations
Expand functionality with a wide range of DJI accessories.
For both Dock 3 Remote Operation and Matrice 4D Series Standalone Operation
- Gimbal-Following Spotlight: Provides optimal illumination for nighttime missions.
- Real-Time Voice Speaker: Enables live broadcasts up to 300 meters for public safety.[9]
- Integrated Broadcasting and Lighting:The spotlight and speaker can function independently or together, addressing various operational scenarios.
- Obstable Sensing Module: Rotating LiDAR and millimeter-wave radar for precise obstacle avoidance, detecting 12mm wires at up to 15 m/s.
- DJI Cellular Dongle 2: Ensures reliable 4G network video transmission.[10]
- DJI Power Solutions: DJI Power 1000 for fast and efficient charging.
Only for Dock 3 Remote Operation
- D-RTK 3 Relay Relay Fixed Deployment Version: Offers centimeter-level high-precision positioning and signal relay for extended video transmission.
Only for Matrice 4D Series Standalone Operation
- DJI RC Plus 2 Enterprise Controller: When pairing Matrice 4D Series for standalone use, High-brightness screen, IP54 protection, and 4G connectivity for stable video transmission.
These accessories enhance both the automated and standalone operations, ensuring seamless performance, extended range, and uninterrupted missions.
D-RTK3 Relay Fixed Deployment Version & Integrated Broadcasting and Lighting
9. Open Ecosystem, Expanding Possibilities
The open ecosystem fosters innovation for tech developers and highly specialized industries.
The Intelligent Algorithm Developer [2] provides model training tools and third-party developer certification for custom applications. With PSDK and E-Port Lite encryption, payload integration remains secure and reliable, while the open-source Mobile SDK 5 (MSDK) simplifies app development through production-ready code.
DJI FlightHub 2 enables direct cloud integration, allowing connectivity with third-party platforms.[11] Additionally, the MQTT-based Cloud API grants access to drone hardware, video, and image data. For added versatility, enterprises can integrate custom payloads such as parachutes, advanced sensors, or extra gimbals using the E-Port or rear PSDK port.
Versatility and Applications
With its robust build, intelligent automation, and adaptability, the DJI Dock 3 is nothing short of revolutionary. It offers a versatile, efficient solution for enterprises, reduces operational costs, and delivers seamless aerial coverage under virtually any conditions.
- Public Safety: Emergency response, disaster monitoring, and crowd management.
- Agriculture: Optimize crop management, irrigation planning, and pest control with automated flight paths.
- Energy Sector: Conduct remote inspections of solar farms, wind turbines or oil pipelines with intelligent analysis.
- Maritime & Water Conservancy: Monitor coastal areas, reservoirs, and waterways for environmental assessments and safety.
- Construction:
- Perform site surveys, progress monitoring, and high-precision 3D mapping for efficient project planning.
- Conduct structural inspections of buildings, bridges, and infrastructure, ensuring safety and quality control.
- Roads & Bridges: Perform structural inspections, traffic monitoring and maintenance planning
Ready to revolutionize your remote drone operations? Contact us or your local authorized dealer to schedule a demo and explore purchasing options.
DJI Dock 3 in Solar Farm
Notes:
1. DJI Dock 3 is IP56 rated, and the DJI Matrice 4D/4TD is IP55 rated. Both were tested under controlled laboratory conditions, with the dock’s distribution cabinet door closed and screws tightened. The IP rating is not permanently effective and may decrease due to product wear and tear.
2. Need to upgrade to the latest firmware.
3. Vehicle mounting must comply with local regulations. Pay attention to road safety and height restrictions while driving.
4. Sold separately.
5. The functionalities of building-side deployment and communication tower deployment rely on the service area of the satellite positioning system, currently only supporting most regions in the Asia Pacific, as detailed in the Installation and Setup Manual. The specific applicability should be determined based on the results displayed on the DJI Pilot 2 app during dock site evaluation. During communication tower deployment, the dynamic power variation of communication base stations may cause signal interference, potentially affecting drone takeoff in rare cases. If such issues occur, please try restarting the aircraft and reissuing the flight task.
6. Measured with the DJI Matrice 4D series drones hovering in a windless environment at 20 meters above sea level and from 100% battery level until 0%. Results may vary depending on the environment, actual use, and firmware version. Results may vary depending on the environment, actual use, and firmware version.
7. Measured in a controlled test environment. Specific test conditions are as follows: flying forward at a constant speed of 12 m/s in a windless laboratory environment at 20 meters above sea level, in photo mode (without photo-taking operation during flight), with Obstacle Avoidance Action set to Off, and from 100% battery level until 0%. Results may vary depending on the environment, actual use, and firmware version.
8. There should be no obstructions between the remote controller and the relay aircraft, and between the relay aircraft and the operational aircraft. Strong electromagnetic interference may affect the video transmission distance.
9. This data was measured in an experimental environment with an ambient temperature of 25° C (77° F) and is for reference only. Actual conditions may vary slightly due to differences in software versions, audio sources, specific environments, and other factors. The final effect is subject to actual use.
10. Sold separately. This service is not available in some countries and regions. Please consult your local dealer for details.
11. Please consult your dealer first to ensure that the payload is compatible with DJI FlightHub 2.
Tags: BVLOS, DJI Dock 3
Top Features of the Matrice 4 Series
The Age of Intelligent Flight
Introducing the DJI Matrice 4 Series, a new compact and intelligent multi-sensor small flagship drone series for enterprise industries.
The DJI Matrice 4 Series advances enterprise aerial operations with innovative AI, improved safety features, and high precision. This small flagship multi-sensor compact drone series offers two models, the Matrice 4T and Matrice 4E, each tailored to meet the needs of varying industries. Whether you’re in public safety, surveying, or construction, the Matrice 4 Series is designed to streamline your workflow and deliver professional-grade results. A new era in intelligent aerial operations begins now.
Below, we’ll explore the top features of the Matrice 4 Series, highlighting how these drones redefine aerial operations and provide significant advantages across industries.
The New Matrice 4 Series
Powerful Multi-Sensor Systems
The Matrice 4T and 4E models feature advanced multi-sensor systems for exceptional visual and data-collection capabilities. The Matrice 4T includes versatile cameras—wide-angle, medium telephoto, telephoto, and an infrared thermal camera for high-resolution thermal readings—plus a laser range finder measuring up to 1,800 meters, making it ideal for search and rescue. The Matrice 4E includes all tele cameras and laser range finder of the M3T, but features a mechanical shutter on the wide-angle camera that excels in rapid mapping with 0.5-second interval shooting, making it efficient for surveying.
| Feature | Matrice 4T | Matrice 4E |
| Wide-Angle Camera | 1/1.3 CMOS
48 MP Effective Pixels f/1.7 Format Equivalent: 24 mm |
4/3 CMOS
20 MP Effective Pixels f/2.8-f/11 Format Equivalent: 24 mm Mechanical Shutter |
| Medium Tele Camera | 1/1.3 CMOS
48 MP Effective Pixels f/2.8 Format Equivalent: 70 mm |
|
| Tele Camera | 1/1.5 CMOS
48 MP Effective Pixels f/2.8 Format Equivalent: 168 mm |
|
| Laser Range Finder | Measurement Range: 1800 m (1 Hz); Oblique Incidence Range (1:5 Oblique Distance): 600 m (1 Hz)
Blind Zone: 1 m; Range Accuracy (m): ± (0.2 + 0.0015 × D) |
|
| Infrared Thermal Camera | Resolution 640 × 512
f/1.0 Equivalent Focal Length: 53 mm Uncooled VOx Microbolometer Supports High-Res Mode |
N/A |
| NIR Auxiliary Light | FOV: 6°
Illumination Distance: 100 m |
N/A |
Matrice 4T and Matrice 4E
Intelligent AI-Powered Operations
The DJI Matrice 4 Series showcases intelligent operations with AI, featuring a built-in model for detecting vehicles, vessels, and subjects during search and rescue or routine flights, and supports switching to other models, enabling the expansion of AI application scenarios. DJI now also provides the necessary model training tools and third-party developer certification process to access onboard computing capability, helping expand new drone AI application fields. Its laser range finder provides real-time measurements for tasks like marking inspection targets or calculating wildfire areas, easily shared via DJI Pilot QR code or DJI FlightHub 2. DJI Pilot 2 enhances patrols and rescues by highlighting camera frame centers and observed areas on maps.
Efficient flight modes, including cruise control and Smart Track for precise tracking, boost operational capabilities, while the POI feature aids 3D modeling and fixed-point observations.
AI power for Smarter Operations
Excel In Low-Light Environments
The Matrice 4 series excels in low-light conditions with upgraded Night Scene Mode, offering full-color night vision in three modes and enhanced noise reduction. Equipped with an IR Cut Filter and NIR auxiliary light, it ensures clear visibility, making search and rescue subjects easily detectable. The Matrice 4T’s NIR illumination extends lighting up to 100 meters, ideal for wildlife protection. It supports infrared High-Res Mode at 1280 × 1024 resolution, revealing fine temperature details. Six high-definition low-light fisheye lenses enhance positioning and obstacle avoidance for safe urban navigation.
Improved Night Capability
Precision Mapping for Surveying and Construction
The Matrice 4E enhances geospatial mapping with rapid 0.5-second interval shooting and speeds up to 21 meters per second. Its wide-angle camera supports orthophoto and oblique modes, while 5-directional oblique and 3-directional ortho capture maximize area coverage. It also enables Smart 3D Capture, allowing users to create rough models on the remote controller and generate precise mapping routes for detailed measurements of irregular buildings. It also displays virtual space routes and waypoint photos, enhancing flight safety assessment and coverage area analysis. Distortion Correction 2.0 provides high-precision in-camera distortion correction with residual distortion less than 2 pixels. DJI Pilot 2 auto-generates survey reports, offering key insights and enabling on-site adjustments to improve efficiency.
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Smart 3D Capture
Robust Telephoto Capabilities for Inspections
The Matrice 4 series stands out with its advanced imaging capabilities, featuring a medium telephoto camera for detailed medium-range inspections and a telephoto camera with 48 MP clarity, capturing intricate details from up to 250 meters away. Furthermore, the Matrice 4T is equipped with an IR-Cut Filter, ensuring reliable 24/7 operations. The series also boasts upgraded telephoto stabilization, which keeps foreground subjects stable and clear during telephoto shooting at 10x zoom or higher. Additionally, Electronic Dehazing in three modes ensures optimal clarity in challenging atmospheric conditions.
Matrice 4 series in infrastructure inspection
Innovative Safety and Navigation Systems
DJI’s self-developed RTK module comes standard in the Matrice 4 Series, providing comprehensive visibility for enhanced safety. Its GNSS+Vision Fusion Positioning and Navigation System enables worry-free flights even in areas with poor GPS signals.
Safety Highlights:
- Omnidirectional obstacle sensing prevent potential collisions.
- Intelligent guidance automatically plans paths around mountainous terrain.
- Return-to-Home functionality works seamlessly in GNSS-deprived environments.
Omnidirectional Obstacle Sensing
New Heights in Video Transmission
The O4 Enterprise video transmission system redefines performance in challenging environments. With the Matrice 4 Series’ 8-antenna setup and a high-gain antenna on the remote controller, it achieves an impressive 25 km maximun transmission range. The system offers a download bandwidth of 20 MB/s, doubling the bitrate of the Mavic 3 Enterprise Series, for precise and stable image transmission. Additionally, the Matrice 4 series supports the optional DJI Cellular Dongle 2, enhancing signal stability with 4G image transmission.
O4 Enterprise Video Transmission System
Efficient Accessory Ecosystem
The Matrice 4 Series upgrades accessories for more efficiency and adaptable operations. The DJI AL1 Spotlight can clearly illuminate subjects even from 100 meters away, supporting both always-on and strobe modes. It also offers enhanced coverage in wide-angle modes.
Meanwhile, the DJI AS1 Speaker delivers powerful audio, broadcasting up to 300 meters and reach 114 decibels at 1 meter. Further elevating operations, the D-RTK 3 Multifunctional Station supports drones with centimeter-level positioning accuracy, extending image transmission through signal relay* at elevated altitudes and facilitating high-precision data collection in network-free areas. Additionally, it can also be used to mark ground control points.
* Relay station mode only supports DJI Matrice 4 Series
Gimbal-Following Spotlight and Real-Time Voice Speaker
Seamless Software Integration
The Matrice 4 Series offers diverse software tools to simplify mission planning and data analysis.
- DJI Pilot 2 refines user interfaces, featuring a customizable intelligent function toolbar and support for various types of flight routes. Additionally, it includes virtual space models and route preview functions.
- DJI Terra enables high-precision camera distortion correction for the Matrice 4E. It supports free offline PPK processing of visible light images and allows for importing D-RTK 3 data.
*One-year DJI Terra license provided with Matrice 4E purchase.
- DJI FlightHub 2 has been upgraded for remote control, allowing a variety of flight route planning functions, specifically for the Matrice 4 series aircraft. Operators can control payloads and aircraft simultaneously through Live Flight Controls and synchronize multiple livestreams during multi-drone operations for efficient air-ground collaboration.
* Users who purchase the Matrice 4 Series and initially bind to FlightHub 2 will receive corresponding live streaming minutes, map image quotas and storage space.
- DTAT 3.0 provides thermal analysis tool to mark, analyze, and process images, detecting abnormal temperature points.
Elevate Your Operations with the Matrice 4 Series
Whether you’re spearheading a search-and-rescue mission or inspecting complex infrastructure, the DJI Matrice 4 Series delivers superior intelligence, safety, and operational efficiency. Its seamless integration of AI and advanced sensor technology ensures that no matter the challenge, you’ll always have the upper hand.
Ready to take your aerial operations to the next level? Contact DJI or your local authorized dealer to schedule a demo or learn more about purchasing options.
DJI releases Matrice 4 series of small industrial drones with built-in AI to automatically find vehicles and people
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Deep Learning Installation Guide: From GPU to Monitor, the latest recommendations for the complete set of hardware
Deep Learning Installation Guide: From GPU to Monitor, the latest recommendations for the complete set of hardware
Xiaocha Annie Guo Yipu
reported from the qubit of the Aofei Temple | Official Account QbitAI
Hardware equipment is an indispensable core equipment for any deep learning agent. Dear primary scribbling magicians, do you feel that the destined wand is missing?
However, how should we choose various CPUs, GPUs, memory sticks, peripherals, and so many brands, types and numbers?
In order to help you get a set of equipment that you can build, a young man named Tim Dettmers condensed his installation experience of assembling seven workstations in a year into a practical guide to share it, helping you determine a complete set of hardware selection, and also made recommendations based on this year’s new hardware.
Okay, let’s start with the GPU and see how each important component should be selected in turn. The full text is more than 5,000 words, and the estimated reading time is 11 minutes. Of course, at the end of the article, we have prepared a ” element list ” for everyone ~
GPU
Graphics cards (GPUs) are important components of deep learning, even more important than CPUs. It is obviously unwise to do deep learning without using GPU and just using CPU, so the author Tim first introduced the choice of GPU.
There are three major things to note when purchasing a GPU: cost-effectiveness, video memory, and heat dissipation.
Use the 16-bit RTX 2070 or RTX 2080 Ti to be more cost-effective. In addition, it is also a good choice to buy second-hand 32bit GTX 1070 , GTX 1080 or 1080 Ti on eBay .
In addition to the GPU core, video memory (GPU RAM) is also a part that cannot be ignored. RTX has more advantages in terms of graphics memory than GTX series graphics cards. With the same graphics memory, RTX can train models that are twice as large.
The usual requirements for video memory are as follows:
- If you want to pursue the highest score in your research: video memory >=11 GB;
- Search for interesting new architectures in the research: video memory >=8 GB;
- Other studies: 8GB;
- Kaggle competition: 4~8GB;
- Startup: 8GB (depending on the model size of the specific application)
- Company: Create a prototype of 8GB, training is no less than 11GB
It should be noted that if you purchase multiple RTX graphics cards, you must not ignore the heat dissipation. The two graphics cards stacked in adjacent PCI-e slots can easily overheat the GPU and reduce frequency, which may result in a 30% performance drop. This issue will be discussed in detail later.
Memory
There are two parameters for selecting memory (RAM) : clock frequency and capacity. Which of these two parameters is more important?
Clock frequency
Hype about memory clock frequency is a commonly used marketing method by manufacturers. They promote the faster the memory, the better. Is this really the case?
Linus Tech Tips, a well-known digital blogger, answered this question: manufacturers will lure you to buy “faster” RAM, but in fact there is little performance improvement.
The memory frequency has nothing to do with the speed of data transfer to video memory. The increase in frequency can only have a performance improvement of up to 3%. You should spend your money elsewhere!
Memory capacity
Memory size does not affect deep learning performance, but it may affect the efficiency of your execution of GPU code. With a larger memory capacity, the CPU can directly exchange data with the GPU without going through the disk.
Therefore, users should be equipped with memory capacity that matches the GPU video memory. If you have a Titan RTX with 24GB of video memory, you should have at least 24GB of memory. However, if there is more GPU, you don’t necessarily need more memory.
Tim believes that memory is related to whether you can concentrate resources and solve more difficult programming problems. If you have more memory, you can focus on more pressing issues without spending a lot of time solving memory bottlenecks.
He also found that extra memory is very useful for feature engineering while competing in Kaggle.
CPU
Too much attention to CPU performance and PCIe channel number is a common cognitive misunderstanding. What users need to pay more attention to is the number of GPUs that support running simultaneously with the CPU and motherboard combination.
CPU and PCIe
People’s obsession with PCIe channels is almost crazy! In fact, it has little impact on deep learning performance.
If there is only one GPU, the PCIe channel is only used to quickly transfer data from memory to video memory.
The 32 images (32x225x225x3) in ImageNet take 1.1 milliseconds to transmit on 16 channels, 2.3 milliseconds to 8 channels, and 4.5 milliseconds to 4 channels.
These are just theoretical numbers, and in fact, PCIe’s speed is only half that of the theory. PCIe channels usually have nanosecond-level delays, so the delay can be ignored.
Tim tested the transmission time required to train the ResNet-152 model using mini-batch with 32 ImageNet images:
- Forward and Backward Transmission: 216 ms
- 16 PCIe Channels CPU->GPU Transfer: About 2 milliseconds (theoretical 1.1 milliseconds)
- 8 PCIe Channels CPU->GPU Transfer: Approximately 5 milliseconds (2.3 milliseconds)
- 4 PCIe Channels CPU->GPU Transfer: Approximately 9 milliseconds (4.5 milliseconds)
Therefore, in total time, from 4 to 16 PCIe channels, the performance improvement is about 3.2%. However, if PyTorch’s data loader has fixed memory, the performance is improved to 0%. So, don’t waste money on PCIe channels if you use a single GPU.
When selecting CPU PCIe channel and motherboard PCIe channel, make sure that the combination you choose can support the number of GPUs you want. If you buy a motherboard that supports 2 GPUs and want to use 2 GPUs, you have to buy a CPU that supports 2 GPUs, but you don’t have to check the number of PCIe channels.
PCIe channel and multi-GPU parallel computing
If you train a network on multiple GPUs, is the PCIe channel important? Tim once published a paper in ICLR 2016, pointing out ( https://arxiv.org/abs/1511.0456 1): If you have 96 GPUs, then PCIe channel is very important.
However, if the number of GPUs is less than 4, you don’t have to care about the PCIe channel at all. Almost few people run more than 4 GPUs at the same time, so don’t waste money on PCIe channels. This doesn’t matter!
Number of CPU cores
In order to choose a CPU, you first need to understand the relationship between CPU and deep learning.
What role does CPU play in deep learning? When running a deep network on a GPU, the CPU does little calculations. The main functions of the CPU are: (1) Start GPU function calls (2) Execute CPU functions.
By far, the most useful application of CPU is data preprocessing. There are two different general data processing strategies with different CPU requirements.
The first strategy is to preprocess during training, and the second is to preprocess before training.
For the first strategy, high-performance multi-core CPUs can significantly improve efficiency. It is recommended that each GPU has at least 4 threads, i.e., to allocate two CPU cores to each GPU. Tim expects that every time one core is added to the GPU, an additional performance boost should be achieved in about 0-5%.
For the second strategy, no very good CPU is required. It is recommended that each GPU has at least 2 threads, i.e. allocate one CPU core to each GPU. With this strategy, more cores will not significantly improve performance.
CPU clock frequency
Is the CPU performance of 4GHz stronger than that of 3.5GHz? For comparisons of processors in the same architecture, it is usually correct. However, between processors in different architectures, frequency comparison cannot be simply compared. CPU clock frequency is not always the best way to measure performance.
In the case of deep learning, the CPU participates in very little calculations: such as adding some variables, evaluating some boolean expressions, and making some function calls within the GPU or program. All of this depends on the CPU core clock rate.
While this reasoning seems wise, the CPU still has 100% usage when running a deep learning program, so what is the problem here? Tim did some CPU downsizing experiments to find out the answer.
Effects of CPU downs on performance:
Note that these experiments were performed on some “old” CPUs (the third generation Core processors launched in 2012). But it should still be suitable for CPUs launched in recent years.
Hard disk/solid-state drive (SSD)
Usually, hard disks will not restrict the operation of deep learning tasks, but if you underestimate the function of hard disks, you may pursue, regret, and not to.
Imagine that if the data you read from the hard disk is only 100MB/s, then loading a mini-batch of 32 ImageNet images will take 185 milliseconds.
Conversely, if the data is obtained asynchronously before using it, the data for these mini-batches will be loaded in 185 milliseconds, while the computation time of most neural networks on ImageNet is about 200 milliseconds. So, load the next mini-batch when computing the state and there will be no loss in performance.
Brother Tim recommends solid-state drives (SSDs), which he believes are both comfortable and efficient when using SSDs. Compared with ordinary hard disks, SSD programs start and respond faster, and preprocessing of large files is much faster.
The top-end experience is NVMe SSD, which is smoother than ordinary SSDs.
Power supply unit (PSU)
The most basic expectation of a programmer for power supply is to meet the energy required by various GPUs. As GPUs develop towards lower energy consumption, a PSU with excellent quality can accompany you for a long time.
How should I choose? Brother Tim has a set of calculation methods: add the power of the computer CPU and GPU, and add 10% of the power to calculate the energy consumption of other components, and the power peak is obtained.
For example, if you have 4 GPUs, each with 250 watts of power and a CPU with 150 watts, you need the power supply to provide 4×250+150+100=1250 watts of power.
Tim usually adds an additional 10% on this basis to ensure that it is foolproof, which will require a total of 1375 watts. Therefore, in this case, the power supply performance needs to reach 1400 watts.
It should not be difficult to understand how to teach step by step. It is also important to note that even if a PSU reaches the required wattage, there may not be enough PCIe 8-pin or 6-pin connectors, so when buying, make sure there are enough connectors on the power supply to connect to the GPU.
Also, buy a power supply with a high energy efficiency level, especially when you need to connect to a lot of GPUs and may run for a long time, you know the reason.
Let me give you another example. If you run a 4 GPU system at full power (1000-1500 watts) and spend two weeks training a convolutional neural network, it will consume 300-500 kWh of electricity. Calculated at 0.2 euros per kilowatt-hour in Germany, the final electricity bill is equivalent to RMB 455-766.
If the power supply efficiency is reduced to 80%, the electricity bill will increase by 140-203 yuan.
The more GPUs you need, the more obvious the gap will be. Is the choice of PSU a little more complicated than I thought?
Cooling of CPU and GPU
For CPUs and GPUs, poor heat dissipation will reduce their performance.
For CPUs, standard radiators or AIO water-cooled radiators are good choices.
But it is a complicated matter which heat dissipation solution to the GPU.
Air-cooled heat dissipation
If there is only a single GPU, air cooling is safe and reliable, but if you have as many as 3-4 GPUs, air cooling may not meet the needs.
Current GPUs will increase the speed to maximum when running the algorithm, so the power consumption will also reach the maximum. Once the temperature exceeds 80℃, it is very likely to reduce the speed and cannot achieve optimal performance.
This phenomenon is more common for deep learning tasks. A general cooling fan is far from achieving the desired effect and reaches the temperature threshold after running for a few seconds. If you use multiple GPUs, the performance may be reduced by 10% to 25%.
what to do? At present, many Nvidia GPUs are designed for gaming, so they have specially optimized for Windows systems and can also easily set up fan solutions.
But this trick cannot be used in Linux systems. The trouble is that many deep learning libraries are also written for Linux.
This is a problem, but it is not unsolvable.
In Linux systems, you can configure Xorg servers and select the “coolbits” option, which still works well for a single GPU.
If you have multiple GPUs, you have to simulate a monitor. Brother Tim said he tried it for a long time, but there was still no improvement.
If you want to run in an air-cooled environment for 3-4 hours, you should pay attention to the fan design.
There are roughly two principles for cooling fans on the market: a blower fan pushes hot air from the back of the chassis to allow cool air to come in; a non-blowing fan sucks air in the GPU to achieve cooling effect.
So, if you have multiple GPUs adjacent to each other, there is no cold air available around you, so in this case, you must not use a non-blowing cooling fan .
Then what to use? Then look down—
Water cooling heat dissipation
Although water-cooling cooling is slightly more expensive than air-cooling, it is very suitable for situations where multiple GPUs are adjacent. It can hold the four most powerful GPUs to keep the whole body cool, which is an effect that air-cooling cannot achieve.
In addition, water cooling can be performed more quietly, and the advantages of water cooling are more prominent if you run multiple GPUs in a common area.
As for the cost issue that everyone is most concerned about, a water-cooled single GPU costs about US$100 (about RMB 690) and some additional upfront costs (about RMB 350).
In addition to financial preparation, you also need to invest some energy, such as spending extra time assembling a computer, etc. There are already many online tutorials on this kind of thing, and it only takes a few hours to complete, and the later maintenance is not complicated.
in conclusion
For a single GPU, air cooling is cheap and sufficient; for multiple GPUs, blown air cooling is cheaper, which may cause a performance loss of 10% to 15%. If you want to pursue the ultimate heat dissipation, water cooling will be quiet and have the best effect.
Therefore, air-cooling or water-cooling is reasonable, depending on your actual situation and budget. But the guy finally suggested that under normal circumstances, it is better to consider low-cost air cooling.
Motherboard
The motherboard should have enough PCIe slots to support the required number of GPUs. But it should be noted that most graphics cards need to occupy two PCIe slots in width.
If you plan to use multiple GPUs, you need to purchase a motherboard with enough space between the PCIe slots to ensure that the graphics cards do not block each other.
Chassis
When choosing a chassis, you must ensure that the chassis can install the full-length GPU on the top of the motherboard. Although most chassis are fine, if you buy it smaller, it depends on whether the merchant gives you seven days and no reason…
Therefore, it is best to confirm the size and specifications of the chassis before buying, or search for the picture of the chassis containing the GPU. If there are other people’s finished pictures, you can buy it with confidence.
In addition, if you want to use custom water cooling, make sure your chassis can be installed with a radiator, especially when using custom water cooling for the GPU, the radiator of each GPU needs to take up space.
monitor
How to use the monitor?
Must be taught.
Tim releases the buyer show:
Yes, as a mature technician, using multiple monitors is the basic configuration.
Imagine stacking the contents on these three monitors on the buyer show on the same screen and switching windows back and forth. How tiring it is.
Too long to watch the version
GPU :
RTX 2070, RTX 2080 Ti, GTX 1070, GTX 1080, GTX 1080, these are all good.
CPU :
1. Equip each GPU with 1-2 CPU cores, which depends on how you preprocess the data;
2. The frequency should be greater than 2GHz, and the CPU should be able to support your GPU number;
3. The PCIe channel is not important.
Memory :
1. The clock frequency doesn’t matter, just buy the cheapest memory;
2. Memory ≥ The RAM of the GPU with the largest video memory;
3. Don’t need to be too large, buy as much as you want;
4. If you often use large datasets, it will be useful to buy more memory.
Hard disk/SSD :
1. Prepare a large enough hard disk (≥3TB) for your data set;
2. It is more comfortable to use with SSD and can also preprocess small data sets.
PSU :
1. The maximum required power value ≈ (CPU power + GPU power) × 110%;
2. Buy a high-efficiency power supply, especially when you need to connect to a lot of GPUs and may run for a long time, which can save a lot of electricity bills;
3. Before buying, please make sure that there are enough connectors (PCIe 8-pin or 6-pin) on the power supply to connect to the GPU.
Heat dissipation :
CPU:
Standard configuration CPU radiator or AIO water-cooled radiator;
GPU:
1. Single GPU, air-cooled and heat-dissipated;
2. If you use multiple GPUs, choose blower air-cooled heat dissipation or water-cooled heat dissipation.
Motherboard :
Prepare as many PCle slots as possible to link GPUs. One GPU requires two slots, and each system has up to 4 GPUs, but you also need to consider the thickness of the GPU.
monitor :
To improve efficiency, buy more screens.
My brother who has published three top-level doctoral students
Tim Dettmers, the author of this guide, graduated with a master’s degree last year and is currently studying PhD at the University of Washington. He mainly studies knowledge expression, question-and-answer systems and common sense reasoning. He has interned in the UCL machine learning group and Microsoft.
According to the doctoral program after graduation last year, Tim’s PhD has only been a year and a half, and now he is the author of three top-summary papers, including one of which is AAAI and one of which is ICLR and the only author.
In addition, he is also a Kaggle enthusiast, and once ranked 63rd in the world (top 0.22%) in 2013.
One More Thing
Actually, after saying so much, you don’t want to install the machine, right?
Tim had already expected that, in addition to the installation guide, he also took the initiative to contribute some installation encouragement:
Although buying hardware is expensive, it will hurt if you make a mistake by mistake, don’t be afraid of installing a computer.
First, the installation itself is very simple. The motherboard manual clearly writes how to install it, which is not much more difficult than installing Lego. It also comes with a lot of guides and step-by-step operation videos. Even if you are a novice in experience, you can learn it.
Second, as long as there is a first installment, it will not be difficult later, because all computers are composed of those hardware. Therefore, just install it once and you can get a lifelong skill, with a very high return on investment.
So, come on, prepare your own equipment ~
Portal
original:
A Full Hardware Guide to Deep Learning
http :// timdettmers.com/2018/12/16/deep-learning-hardware-guide/
Recommended by the author, digital blogger Linus Tech Tips answers questions: Is high-frequency memory useful for performance improvement? (Official Chinese version of Bilibili):
https://www. bilibili.com/video/av14 528439
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Recommended aerial photography, tilt photography, orthophoto processing desktop, portable, cluster hardware configuration (updated)
Recommended aerial photography, tilt photography, orthophoto processing desktop, portable, cluster hardware configuration (updated)
Quotation update date: 2020/10/13
Upgrade 1: Graphics card RTX20 series upgrade to RTX3080/RTX3090 series, with significant performance improvement
Upgrade 2: Desktop and cluster CPU heat pipe heat dissipation upgrade to industrial-grade water-cooled heat dissipation, with higher frequency increase
Upgrade 3 Upgrade related models desktop and cluster
Main content
(1) Desktop image processing workstation configuration scheme
(2) Portable image processing workstation configuration scheme
(3) Tilt photography image processing multi-machine cluster configuration scheme
(4) Mini mobile image processing cluster configuration scheme
In the surveying and mapping industry, the aerial image application of drones is becoming more and more extensive, and the amount of data is becoming increasingly large. The market needs computing and processing equipment from desktop to mobile portable, multi-machine cluster , mobile multi-machine cluster, etc.
Since Xi’an Kunlong Computer Company has focused on the application of aerial image processing of drones in 2013, we have accumulated a large number of performance test data of various specifications and sizes of hardware in different eras, as well as many years of rich successful cases, experienced test engineers and technical support engineers, and many years of experience in hardware configuration and performance optimization.
Entering 2020, for the latest listed computing architecture, tilt photography modeling, orthophoto processing and other applications, we have once again launched a variety of solutions with better configuration, faster speed and rich models – desktop workstations , mobile workstations, multi-machine clusters, mobile clusters, etc., with significant technical features:
- The recommended machine hardware configuration, its CPU+GPU performance, memory, hard disk io, network port, and maximum performance in every link of the computing process, without bottlenecks and no blind spots.
- A complete and reliable computing solution is provided for different computing scales and different budgets.
- Ensure that different image processing software (such as: Context Capture, Pix4D, Inpho, DJI , etc.) can achieve the ultimate performance of workstation processing
(I). Recommended hardware configuration for desktop (stand-alone) image processing workstations
Related model: H390
Air three processing, three-dimensional modeling, etc. for tilt photography/ orthography based on office silent environment
Technical points:
Adopt Intel’s 10th generation ultra-high frequency processor (10 cores 5.2GHz)
Maximum memory capacity 128GB DDR4 2933
Configure RTX graphics card with Turing architecture
Configure 2.5G Ethernet port
All-round optimization of the entire machine performance
In short, this is the fastest desktop image processing workstation on the market (2nd quarter of 2020),
Data processing data reference:
Machine configuration: 10 cores 5.2GHz + 64GB + RTX2080ti 11GB
Data volume: 3860 pictures, resolution 6000×4000,
Single machine processing capability: Air three processing time 1:10, 3D modeling time 46:9, average 82 pictures/hour
Provide remote testing verification, the above data
Recommended hardware configuration of desktop image processing workstations
(II) Tilt photography modeling hardware configuration solution (mobile portable workstation)
This is the fastest portable mobile computing architecture on the market, with the highest computing processing capacity of 10 cores 5.1GHz, a maximum memory configuration of 128GB memory, and the RTX graphics card equipped with the latest Turing architecture (maximum 2 blocks)
is positioned in the air three processing, three-dimensional modeling, and orthophoto processing of mobile tilt photography . It is much higher than the computing and storage capabilities of industrial control computers and laptops on the market, while ensuring absolute high mobile and high performance.
2.1 Recommended single-screen portable configuration
2.2 Three-screen portable workstation configuration solution
(III) Recommended multi-machine cluster configuration
The calculation volume of massive aerial image data is huge, and the processing time of a single machine’s computing power is too long and the efficiency is low. With the help of the most advanced multi-machine parallel cluster processing system, air three processing and three-dimensional modeling are carried out, which greatly shortens the processing time.
Related models:
(1) Image processing workstation (computing node)
Model: UltraLAB M390 (the latest model launched in 2020)
Technical features:
adopt Intel’s 10th generation ultra-high frequency processor, equipped with industrial-grade water-cooled radiator, Nvidia Turing architecture GPU computing card, network port is equipped with 2.5G, and hard disk is M2.SSD, ensuring stronger hardware configuration calculation, higher io bandwidth, and comprehensive optimization of the entire machine performance, ensuring that aerial image data processing is completed in the shortest time.
(2) Main control and storage server ( storage node )
Related models: UltraLAB N630i (8 disks), N630 (16 disks)
Technical features:
CPU adopts Intel Xeon second-generation scalable processor
cache disk : equipped with M2.SSD to ensure high-speed read and write (read and write 3G/s or above) and ultra-low io latency,
equipped with parallel storage: data backup is safe and reliable, with maximum capacity to 112TB (8 disks)/240TB (16 disks)
network port: equipped with dual 10G optical ports, theoretical io bandwidth reaches 2.5GB/s
, and the entire machine performance is fully optimized to ensure the best aerial image data io.
This is the latest and fastest multi-machine parallel cluster solution on the market currently (June 2020)
Solution 1 Recommended high-speed drone image processing cluster configuration (5 computing nodes)
Solution 2 Recommended high-speed drone image processing cluster configuration (10 computing nodes)
Solution 3 Recommended high-speed drone image processing cluster configuration (20 computing nodes)
Solution 4 Recommended high-speed drone image processing cluster configuration (30 computing nodes)
Solution 5 Recommended high-speed drone image processing cluster configuration (60 computing nodes)
Solution 6 Recommended high-speed drone image processing cluster configuration (90 computing nodes)
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