The open source platform for comprehensive practice of intelligent network simulation and intelligent transportation is a platform that integrates unmanned driving comprehensive platform, digital twin and intelligent sand table vehicle RTRC Pro, and is suitable for teacher education and student learning in major universities. At present, the intelligent networked automobile education in major colleges and universities is facing problems such as lack of teachers, shortage of course resources, and outdated teaching materials. The open source platform for the comprehensive practice of intelligent networked simulation and intelligent transportation not only provides first-class teacher education and complete curriculum resources, but also supports corresponding practical education teaching aids, software and hardware integration solutions to solve the problems of talent training in major universities.
1. Construction background
With the deep integration of informatization and automobiles, automobiles are transforming from traditional means of transportation into new types of intelligent travel carriers. The development of intelligent networked vehicles is of strategic significance to a country. Therefore, in recent years, my country has vigorously supported the development of intelligent networked vehicles. Li Keqiang gave a keynote speech on "Intelligent Networked Vehicle Cloud Control Basic Platform and Its Implementation" at the "First International Forum on Vehicle-Road Cooperative Autonomous Driving". It introduces how to promote the development of intelligent networked vehicles in my country from various aspects such as policy support, formulation of road test regulations, construction of demonstration areas, basic data platforms, industrial innovation alliances, and approval of key projects. In the same year, the Ministry of Industry and Information Technology issued a notice on the "Internet of Vehicles (Intelligent Networked Vehicle) Industry Development Action Plan". The notice emphasizes the need to accelerate the joint development and transformation of perception devices such as vehicle vision systems, laser/millimeter wave radars, multi-domain controllers, and inertial navigation. Accelerate the research and development of key components such as smart vehicle terminals and car-grade chips, and promote the industrial application of technologies such as new-generation artificial intelligence, high-precision positioning and dynamic maps in intelligent networked vehicles.
The open-source platform for the comprehensive practice of intelligent network simulation and intelligent transportation is a set of intelligent traffic road system that can realize the comprehensive sand table of intelligent network connection and driverless driving. It can support students' relevant course construction, scientific research projects and undergraduate extracurricular scientific research activities in the undergraduate year. It can help students develop various functions including collaborative priority vehicle traffic, dynamic lane management, floating car data collection, intelligent signal control, etc.
2. Platform display
1. Unmanned driving integrated sand table (RTST Stand dard )
1. Basic composition
(1) base
The picture shows that the unmanned driving integrated sand table (RTST Standard) covers an area of about 32 square meters. At the same time, the height structure of the internal frame can be adjusted according to its own needs.
(2) Scene content
It mainly includes: lighting circuits, plots and buildings, greening (landscape ratio: 1:100), urban roads (road ratio: 1:10), expressways, traffic scenes, urban vehicle RTRC Pro and other related scenes.
2. Function display
By simulating the intelligent vehicle module of the real intelligent transportation system, it can perform multiple functions such as automatic driving, automatic cruise, automatic obstacle avoidance, intelligent traffic signal control, and global path planning for unmanned vehicles. The intelligent traffic lights are configured according to the number of intersections, and the traffic lights are changed in turn.
3. Case presentation
(1) Customization case of unmanned driving comprehensive sand table
(2) Real picture of unmanned driving comprehensive sand table case
2. Digital twin (RTST System)
The system fully presents the whole picture of the future intelligent transportation system, cultivates students' overall cognition of the intelligent networked transportation system and the in-depth grasp of the structure and composition of each part of the system, the operating principle, and the overall operation process and principle of the system, and assists the comprehensive teaching of intelligent networked vehicle technology.
1. Basic composition
(1) Intelligent data access and management
Provide users with one-stop big data processing capabilities, can quickly access smart sand table vehicle RTRC Pro data, intelligent driverless sand table data (such as road information data, real-time video sources, etc.), and realize unified management.
(2) Construction of diversified data analysis panels
The richness and practicability of the digital twin scene are not only reflected in the precise sculpting of the physical model, but also in the multidimensional analysis of the upper data. The chart style changes according to the needs, flexibly responds to the needs, and meets the multi-scenario, high-complexity, and high-value data analysis and display needs of the data panel in the digital twin scene.
(3) Layer information interaction
"Layers" are used for information interaction, and management information of different dimensions is cut and dissected into separate information layers. Each information layer can be freely combined and superimposed on demand, and the original information understanding method is followed to the greatest extent.
(4) Data interaction
Through the data interface, it forms a close cooperative relationship with the existing unmanned comprehensive sand table and smart sand table vehicle applications. On the basis of the original system, it only needs to increase the data interaction with the 3D scene to complete the leap from planar visual application to 3D visualization industry application.
(5) Visual programming
Provides the drag-and-drop assembly function of the front-end 2D and 3D components and the visual configuration of the back-end complex logic control. The visual logic configuration capability can generally support three types of logic control, logic flow and process control, realize complex business logic, and meet the needs of application scenarios in actual use.
(6) Full simulation capability platform
A tool development kit that provides the basic capabilities of base scenarios and simulation capabilities. Users can repackage commonly used functions to achieve large-scale replication of digital twin projects.
2. Function display
(1) Sand table central control and transmission software system
The central control of the sand table can display the image of the camera of the car in real time, and the central control of the sand table can display the scene of the entire sand table and the current position of the car on the sand table in real time.
ⅠSupport real-time status display and remote control of the traffic lights in the simulation suite for the traffic lights scene;
ⅡSupport the real-time status display and remote switch dimming control of the equipment in the intelligent street lamp scene in the simulation suite;
Ⅲ Supports the real-time status display of the equipment of the gate in the simulation suite;
At the same time, it can build a remote RTRC Pro debugging terminal based on the indoor communication network, realize the separation of RTRC Pro control and intelligent driving, realize the separation of sand table control and sand table entity, and realize content control in the data process, thereby improving the efficiency of vehicle debugging.
(2) Real-time screen and simulation suite
Display the digital twin model of the vehicle on the 3D map, the real-time planning trajectory of the vehicle, and the steering prompt when the vehicle turns; it supports real-time data collection and uploading functions, including: body data, radar perception data, image data, control data, etc., real-time collected vehicle lidar point cloud data and vehicle camera images, real-time idle/running status of the vehicle, vehicle speed and steering angle, and displays the status of vehicle cameras, lidar radar, millimeter wave radar, ultrasonic radar and other equipment.
3. Intelligent network sand table car (RTRC Pro)
1. Basic composition
The intelligent networked sand table car (RTRC Pro) can be based on the traffic sign recognition of the intelligent networked teaching vehicle, the construction of the campus map of the lidar, the visual scene recognition of the deep learning, the traffic light recognition of the YOLO deep learning framework, etc., to carry the graduation design project of the students, build the teaching laboratory of the intelligent networked vehicle, set up the basic course of the intelligent vehicle engineering, professional practice course practice, course design, graduation design and graduate comprehensive practice course and algorithm verification experiment course.
(1) chip
Bring supercomputer performance to the edge with the Small Form Factor System on Module (SOM). Up to 21TOPS of accelerated computing power runs modern neural networks in parallel and processes data from multiple high-resolution sensors. Development and verification of functional scenarios such as Lane Keeping Assist (LKS) System, Automatic Emergency Braking (AEB) System, Adaptive Cruise Control (ACC) System, Pre-Collision Safety System (PCS) and Automatic Parking System (APS) that support intelligent driving courses.
| Basic parameters |
|
| name |
chip |
| quantity |
1 |
| Technical Parameters |
GPU：384-core NVIDIA Volta GPU with 48 Tensor Cores CPU：6-core NVIDIA Carmel Arm v8.2 64-bit CPU 6MB L2+4MB L3 Memory: 8GB 128-bit LPDDR4x 51.2GB/s Storage: 16GB eMMC+128G SSD Support network: 10/100/1000 BASE-T Ethernet |
(2) Ultrasonic sensor
Ultrasonic radar is to measure the distance by the time difference when the ultrasonic transmitter emits ultrasonic waves and receives the transmitted ultrasonic waves through the receiver. Ultrasonic short-distance detection, the higher the frequency of the probe, the higher the sensitivity, and it is waterproof and dustproof, even if there is a small amount of mud and sand, it will not be affected. It can support ultrasonic radar obstacle detection, ultrasonic radar installation, cognition, calibration, data reading, automatic emergency braking (AEB) system, adaptive cruise (ACC) system, automatic parking (APS) system and other teaching and training courses.
| Basic parameters |
|
| name |
ultrasonic sensor |
| quantity |
2 |
| Technical Parameters |
Working frequency: ≤40kHz Shooting range: 2cm～4m Measuring angle: ≤15 degrees |
(3) Camera
The camera can transmit dynamic video and record objects into the data. Using 3D laser contour sensor technology, the object contour data is collected and converted into 2D image data for analysis. After image area segmentation processing, the external data information of the vehicle and the real-time motion status information and location information of many target vehicles can be obtained. The camera module can support teaching and training courses such as pedestrian recognition, traffic light recognition, traffic sign recognition, obstacle recognition, lane line recognition, camera installation, cognition, calibration, data reading, and camera + lidar fusion perception.
| Basic parameters |
|
| name |
Camera |
| quantity |
1 |
| Technical Parameters |
Depth resolution and frame rate: ≥1280x720 90fps RGB sensor resolution and frame rate: ≥1920x1080 30fps Depth distance range: 0.105m-10m Use environment support: indoor/outdoor |
(4) Millimeter wave radar
Millimeter wave radar is composed of antenna, transceiver module, and signal processing module. The electromagnetic wave whose frequency gradually increases with time is emitted by the oscillator, and the relative distance and relative speed of the target in front are calculated according to the frequency difference between the returned waveform and the emitted waveform. Millimeter wave radar can support millimeter wave radar obstacle detection, millimeter wave radar installation, cognition, calibration, data reading and adaptive cruise (ACC) system and other teaching and training courses.
| Basic parameters |
|
| name |
millimeter wave radar |
| quantity |
1 |
| Technical Parameters |
Working voltage: DC 3.0V～3.6V (typical value 3.3V) Working temperature: -35～80℃ Quiescent current: <10uA Ranging range 0.2m～12.5m Single maximum ranging length: ≤12.3m |
(5) IMU sensor
An IMU sensor is a combination of accelerometer and gyroscope sensors that are used to detect acceleration and angular velocity to indicate motion and motion intensity. The IMU sensor can not only provide information about the position of the vehicle, but also provide information about the attitude of the vehicle body, providing a decisive reference for the vehicle's direction perception. IMU sensors can support teaching and training courses such as lane keeping assist (LKS) system, automatic emergency braking (AEB) system, pre-collision safety (PCS) system, adaptive cruise (ACC) system and automatic parking (APS) system.
| Basic parameters |
|
| name |
IMU sensor |
| quantity |
1 |
| Technical Parameters |
Working voltage: 4.7-5.5V Shockproof range: ±8g Number of axes: ≥9 axes Frequency output: 200Hz Pitch/roll angle accuracy (static): 0.7°RMS Pitch/roll angle accuracy (dynamic): 2.5°RMS |
(6) LiDAR
Lidar is an active measurement device that emits a laser beam to detect the spatial position of an object. The detection signal is transmitted to the target, and then the received signal reflected from the target is compared with the transmitted signal, and after proper processing, the relevant information of the target can be obtained. Lidar can support teaching and training courses such as lane keeping assist (LKS) system, pre-collision safety (PCS) system, automatic parking (APS) system, etc.
| Basic parameters |
|
| name |
lidar |
| quantity |
1 |
| Technical Parameters |
Measuring distance: ≤12m Measurement blind area: ≤0.2m Scanning frequency: 5Hz-15Hz Pitch angle: ±1.5° Sampling frequency: ≤16K |
（7）GPS
It is a vehicle-mounted dead reckoning module that integrates a GNSS receiver and a 6-axis inertial sensor to provide continuous high-precision 3D positioning for road vehicles. With high sensitivity and low power consumption, it is suitable for vehicle navigation and handheld positioning.
| Basic parameters |
|
| name |
GPS |
| quantity |
1 |
| Technical Parameters |
Supply voltage: 3.3-5V Current: 45mA 波特率：9600(默认）、38400、115200 更新速率：1Hz 工作温度：-30---85℃ 模块尺寸：36*25*4 带陶瓷天线：厚13mm |
（8）UWB
UWB是一种无载波通信技术，通过在较宽的频谱上传送极低功率的信号，能实现数百Mbit/s至2Gbit/s的数据传输速率。而且具有穿透力强、功耗低、抗干扰效果好、安全性高、空间容量大、能精确定位等诸多优点。
| 基本参数 |
|
| 名称 |
UWB |
| 数量 |
1 |
| 技术参数 |
供电电压：3.3-5V 电流：45mA 波特率：9600(默认）、38400、115200 更新速率：1Hz 工作温度：-30---85℃ 模块尺寸：36*25*4 带陶瓷天线：厚13mm |
（9）激光测距传感器
激光测距传感器支持通信方式配置，预留两个通信接口用于级联测距。同时支持输出模式配置，让数据获取更加自由。每个传感器可配置ID，将多个传感器串联通过一个通信接口即可读取所有的传感的测距信息。
| 基本参数 |
|
| 名称 |
激光测距传感器 |
| 数量 |
1 |
| 技术参数 |
尺寸：35.6*13.0*8.1mm 低盲区：1.5cm 重量：2.7g 测量范围：1.5cm-5m 分辨率：1mm 量程：8m FOV角27° 尾线线长：30cm 线材接口：GH1.25 4P |
（10）舵机
舵机是在自动驾驶中操纵转动的执行部件，适用于需要角度不断变化并可以保持的控制系统。RTRC模型车舵机转向系统直接采用固定轴承加摆臂的形式转变拉杆的运动方向，最后使转向节臂左右摆动，实现转向。舵机可支持自动驾驶等多种功能场景等教学实训课程。
| 基本参数 |
|
| 名称 |
舵机 |
| 数量 |
1 |
| 技术参数 |
角度：O-360° 齿轮虚位≤0.5° 保存温度：-30℃～80℃ 运行温度：-20℃～60℃ 工作电压：4V-7.4V |
（11）电机
电机是依据电磁感应定律实现电能转换或传递的一种电磁装置。通过变速器、减速器等机械传动装置，将电动机输出电矩，传递到左右车轮驱动汽车行驶。通过变速器、减速器等机械传动装置，将电动机输出力矩，传递到左右车轮驱动汽车行驶。电机可支持自动驾驶等多种功能场景等教学实训课程。
| 基本参数 |
|
| 名称 |
电机 |
| 数量 |
1 |
| 技术参数 |
比例：1/10th 有刷/无刷：无刷 有感/无感：有感 支持锂电池节数：2-3S |
（12）电调
电调针对电机不同，可分为有刷电调和无刷电调，它根据控制信号调节电机的转速，控制电机的启、停、加速、减速、正转、反转等，控制，控制电机的启、停、加速、减速、正转、反转等，控制智能网联RTRC的运动状态。电调可支持自动驾驶等多种功能场景等教学实训课程。
| 基本参数 |
|
| 名称 |
电调 |
| 数量 |
1 |
| 技术参数 |
电压：6V-60V，（安全LiPo为3S到12）电压峰值不超过60V 电流：连续电流80-100A，突发电流120A 输出电流：0.5-1A 输出电压：3.3-5V 模式支持：BLDC，FOC（正弦） 支持传感器：ABI，HALL，AS5047，TS5700N8501 通讯端口支持：USB，CAN，UART，PWM |
2.功能展示
提供紧急制动系统、预碰撞安全系统、自适应巡航系统、自动泊车系统、斑马线识别制动、红绿灯识别制动、行人识别并跟随、锥桶识别、交通标志识别、激光雷达构建室内地图(gmapping)等功能。
| RTRC PRO设备功能 |
||
| 实时建图 |
既定路线导航 |
交通信号灯识别并进行启停 |
| 获取实时车辆速度、转角、自身姿态 |
深度摄像头定位 |
停车场监控系统 |
| ETC交互系统 |
智能泊车 |
车道保持辅助系统 |
| 静态障碍物绕行 |
闯红灯拍照 |
路面锥桶识别并制动 |
| 十字路口、T字路口、环岛转向通行 |
激光雷达定位 |
与碰撞安全系统 |
| 紧急制动系统 |
UWB定位 |
自适应巡航 |
| 车载摄像头实时传输 |
超速抓拍系统 |
行人识别 |
| 多车编队巡航 |
斑马线识别 |
红绿灯识别 |
3.预期成效
支撑本科或高职等相关课程开设。老师可根据相关课程进行科技研究项目的开发和学生课外项目，可移植、孵化自主申报科研立项，参加“互联网+”创新创业大赛等国家级比赛，进行技术成果转化进行专利申报和论文发表。
1.课程开设
本建设方案教学设备可支撑开设以下课程：
| 智能网联课程开设 |
||
| 智能网联汽车环境感知技术 |
测试与传感技术 |
汽车电工电子技术 |
| 智能终端安装与测试 |
智能网联汽车环境感知技术 |
车联网技术与应用 |
| 智能网联车辆改装技术 |
测试与检测技术基础 |
汽车车载网络技术 |
| Matlab及其工程应用 |
汽车电子控制原理与技术应用 |
新能源汽车技术 |
| 汽车电子控制 |
智能网联汽车实践 |
车用发动机原理 |
| 有限元在车辆工程中的应用 |
智能网联汽车概述 |
智能网联汽车计算基础 |
| 智能网联汽车底盘控制技术 |
计算机图像与图像处理 |
ROS系统原理与应用 |
| 车辆人机工程学 |
汽车车身结构与设计 |
Python语言程序设计 |
| 汽车电子控制技术 |
智能网联汽车实践 |
智能网联汽车技术 |
| 驱动电机及控制技术 |
汽车电子控制技术 |
智能网联传感器的原理认知 |
本建设方案教学设备可开设以下课程（详情可点击www.relaxing-learning.cn查看）：
免费配套完整的课程视频、PPT、实验指导书、实验报告、源代码
| RTRC Pro课程目录 |
||
| 前期准备 |
车辆安装 |
|
| 传感器及执行件标定 |
舵机标定 |
|
| 电机标定 |
||
| IMU标定 |
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| ROS与传感器数据读取及执行件控制 |
舵机控制 |
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| 电机控制 |
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| 深度摄像头数据读取 |
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| 超声波数据读取 |
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| 毫米波数据读取 |
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| IMU数据读取 |
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| UWB数据读取 |
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| 激光雷达数据读取 |
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| ROS与基础功能 |
车道保持系统 |
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| 紧急制动系统 |
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| 自适应巡航系统 |
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| 预碰撞安全系统 |
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| 自动泊车系统 |
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| 斑马线减速系统 |
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| 红绿灯制动系统 |
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| 定位导航 |
建图 |
激光雷达及IMU融合建图 |
| 定位 |
激光雷达及IMU融合定位 |
|
| uwb及IMU融合定位 |
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| 轨迹规划 |
高精度地图信息 |
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| 轨迹行驶控制算法 |
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| 功能 |
全局路径规划导航 |
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| 单车自主巡航 |
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| 多车编队行驶 |
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| 避障 |
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| 车路协同 |
通讯实例 |
沙盘 |
| 数字孪生 |
||
| 功能 |
红绿灯与ETC交互 | |
（1）实验指导书&实验报告书
包含车道保持辅助系统、预碰撞安全系统、自动紧急制动系统、自适应巡航控制系统、自动泊车系统等内容，满足学生上课需求，学生课后学习，学生作业下达，让学生了解实验目的，掌握实验原理，能独立完成实验，并能够根据所学知识进行自主开发创新设计，培养学生实践能力、学科交叉能力、创新能力和自主学习能力。
（2）课程PPT
应包含车道保持辅助系统、预碰撞安全系统、自动紧急制动系统、自适应巡航控制系统、自动泊车系统等内容，满足教学大纲要求，满足学生上课需求，图文并茂，学生可根据PPT学习设备标定、环境感知融合、路径决策规划等智能网联专业基础知识，培养学生有信息获取与表达能力、自学能力、创新思维能力和应用知识解决问题的能力。
（3）教学视频
应包含车道保持辅助系统、预碰撞安全系统、自动紧急制动系统、自适应巡航控制系统、自动泊车系统等内容，满足教学大纲要求，满足学生上课需求，学生可根据基础教学视频，正确使用设备、操作注意事项、设备维护等，能熟练掌握设备的各种基本操作，并能完成一般故障的定位和排除，同时可对设备进行维护等，培养学生自学能力、创新思维能力和实践能力，为后续学习奠定坚实的基础。
（4）开源代码
应包含车道保持辅助系统、预碰撞安全系统、自动紧急制动系统、自适应巡航控制系统、自动泊车系统等内容，学生可根据提供的开源代码，进行二次开发，基于原理性知识给学生提供应用实践教学，把理论知识与实践相结合的教学模式自主进行实践和拓展，学习智能网联汽车相关知识的同时提高自学能力和创新能力。
2.科研项目
可支撑研究生及教师科研项目，教师和研究生可基于视觉和雷达的目标检测与识别、环境感知系统多传感器融合技术、基于激光雷达的SLAM点云地图构建、对智能驾驶感知算法验证与应用（环境感知、图像处理开发、地图构建、深度学习、规划控制、复杂驱动方式电机控制、功能测试验证）。
结合行业新动态进行实验室功能拓展，基于项目进行科研类研究，可带领学生申请专利、科研立项、发表论文，不断更新相关知识如车路协同、障碍物检测系统、车位召唤驶出、自动驾驶与车身姿态联合控制、车身姿态稳定性控制等智能驾驶辅助系统相关项目，以及基于人工智能和深度学习的交通标志标线识别、红绿灯识别、文字识别、行人识别、泊车位识别、激光雷达SLAM建模等环境感知系统相关项目。
3.科技创新
可举办智能驾驶设计技术相关的课外科技活动或者学科竞赛项目，例如将激光雷达建图、雷达导航、红绿灯以及控制升降杆、自动泊车系统等集合开展智能网联车大赛，例如：APS泊车位识别、V2V无线数据交互等学生竞赛。通过搭载各种学生科技活动建设成为学生科技创新活动承载平台，以培养学生工程实践能力、学科交叉能力、创新能力和自主学习能力。
同时，也可基于学生创新创业教育的平台，在科技活动以及学科竞赛进行的同时，从中挑选出优秀的科研项目，带领学生参加国家大学生创新创业大赛，使学科竞赛平台更加完善与成熟，锻炼学生的综合能力并使其得到有效提升。
| 创新项目名称 |
|
| 基于MATLAB的万物识别及目标物分类 |
基于Yolo的红绿灯检测识别 |
| 基于Yolo的交通标志识别 |
基于Tensorflow的锥桶识别 |
| 基于OpenCV的斑马线识别 |
基于OpenCV的行人识别 |
| 激光雷达的SLAM实时定位与建图 |
伺服电机控制算法优化 |
| 基于RTRC的无线充电系统设计 |
基于OpenCV的车道保持辅助系统开发 |
| 基于超声波雷达的AEB系统开发 |
基于MATLAB/Simulink的APS系统开发 |
| 基于毫米波雷达的紧急制动系统开发 |
基于智能网联模型车的手机端APP开发 |
| 基于UDP通信 的视频传输 |
利用公网通信实现4G远程控制及视频读取 |
| 识别车牌记录车辆进出高速路口智能升降杆 |
|
4.办赛竞赛
学生可基于软件编程和程序调试等全方面的实践学习，从而提高参赛学生对当下热门的运动控制、无人驾驶算法、视觉识别算法的工程应用和现场调试能力，强化参赛学生对智能感知技术在实际工业应用的综合技能。
校赛可面向全校学生，以车辆工程学院、人工智能、计算机科学与通信工程学院、电气信息工程学院、机械学院等相关智能网联专业学生为主要参赛对象，加强学校的学科交叉，让不同院系的学生团结协作、相互学习、共同进步，培养多学科融合综合性人才。同时乐知行科技支持相关赛事举办，并拥有丰富经验。例：第一届智能网联汽车大赛。
市赛，以全省高等院校为参赛对象，每校推选队伍参赛，队伍可由与智能网联汽车相关的所有专业的学生自由组队，旨在加强学科交叉，让不同学校的学生团结协作、相互学习、共同进步。同时，该省部级赛事可面向多省开设，或者多省联合举办，旨在培养更多优秀综合性人才、扩大智能网联汽车影响力，为企业选拔定向输出优秀人才。同时乐知行科技支持相关赛事举办，并拥有丰富经验。例：首届重庆市大学生智能网联汽车大赛。
国赛，涵盖了控制、模式识别、传感技术、电子、电气、计算机、机械等多个学科交叉的科技创意性比赛，旨在培养学生对知识的把握和创新能力，以及从事科学研究的能力。
4.售后服务
提高产品质量和加强全方位的服务，是我公司一贯的宗旨，在售后服务上特别注重服务质量和维修的技术力量及响应的时间速度。为此配备了专业维修技术人品，由公司统一为用户进行定期和不定期的维修和保养等各种售后服务。公司内设有专门的售后服务部，经过专业的培训，技术过硬，服务态度好。除此之外，我司对购买设备客户可提供教学课程资源以及设备使用教程等，从而能够满足客户对我们的产品需求和售后服务的要求，实现对客户的承诺。
乐知行科技售后服务体系
1.产品质保
（1）质保期
提供产品质保期1年（非人为损坏），在质保期内，若由于我方的责任而需要对本系统中的部件（包括软件和硬件）予以更换或升级，则该部件的质保期相应延长。质保期外或其他原因，我方免费提供技术咨询服务，并提供有偿的维修服务。
（2）质保期维修方案
产品方案中所提供的服务内容，我方共为设备维护配备技术人员以及一对一客服人员。质保期到期后，我方技术人员将对设备每年进行一次整体测试及校正，同时针对我方客户定期提供免费设备维护及回访，并作记录。
（3）应急维修时间安排
我们以“客户第一、服务第一”的宗旨、进行系统的售后服务工作，我公司承诺所有的设备提供24h线上答疑服务，可随时通过电话、微信、邮件等多种通讯方式向我方进行技术咨询或相关设备咨询，我方会根据具体的需求情况通过线上或指派技术人员与客户直接沟通以解决问题，保证用户的故障投诉都得到及时的调查和解决，技术维护人员全天值守。
售后服务联系方式
电子邮件：[email protected]
微信售后客服人员：
2.设备使用及课程
（1）设备使用教程
免费提供基础设备使用教程，教程内容包含正确使用设备、操作注意事项、设备维护等。通过培训后，客户能熟练掌握设备的各种基本操作，并能完成一般故障的定位和排除，同时可对设备进行维护、日常管理等。
（2）同步更新课程
免费提供配套教学资源，包含课程PPT、教学视频、实验指导书、实验报告书等教学资源，并开通网站课程权限，客户可随时登录我司网站查看相关设备信息及对应课程内容。课程官网设置留言互动板块，客户可前往留言板块提问、互动，我司人员会及时针对客户问题作出解答。随着我司设备更迭换代，课程内容在课程网站进行同步更新，相关更新内容客户亦可随时阅览。