Rise and Myth of Edge Computing
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With the fast technological progress of sensors, processors, operating system and AI, more and more data are generated and processed. Cloud computing is usually the 1st choice for such tasks, however, cloud computing does have many limitations, like real-time processing, security, scalability etc. Cloud needs to work together with the end point to achieve the best result. in the presentation, I will introduce the concept, example and progress of edge computing, as well as the challenges we are facing to push more computing and analytics to the edge.
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Rise and Myth of Edge Computing
- 1. Copyright Thunder Software Technology Co., Ltd. 2008-2016 All right reserved http://www.thundersoft.com/ the Rise and Myth of Edge Computing 2017.7.8 7/13/2017 1 Ppengcheng Zou CTO of Thundersoft
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- 4. “Do you have eyes but fail to see, and ears but fail to hear? And don't you remember?” - Mark 8:18 7/13/2017 4
- 5. Too Many Eyes that Cannot See 7/13/2017 5
- 6. Data that Cannot Be Understood 7/13/2017 6 About 5GB data will be generated every second by a Boeing 787, but the bandwidth … 1GB data will be generated by the autonomous car every second and it requires real-time processing… I A 3526 C 50 IDC/ ABI/ Cisco forecast connected devices will be 26 / 35 / 50 Billion by 2020… Tens of Billions of face images collected each day
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- 8. Challenges of AI 7/13/2017 8 Massive Data Real-Time Security / Privacy 40%About 40% raw data will be processed at the edge by 2019 IDC estimates that IoT data will make up 95% of real-time data by 2025 More and more devices require security but now unprotected… 45% 42% 13% Requires security unprotected Does not require security Requires security protected
- 9. Rise of Edge Computing 7/13/2017 9 Before 1980 1980-2000 2000-2020 After 2020 Mainframes Client-Server Cloud-Mobile Intelligent Edge Centralized Distributed Centralized Distributed Limited adoption-high end enterprise, government, and education Broader enterprise adoption, some consumer Mass consumerization; life enhancing applications Ubiquitous adoption; life critical applications Thousands of devices, millions of users Hundreds of millions of devices and users Billions of devices and users Hundreds of billions of devices, billions of users Structured data Mostly Structured Structured and unstructured Increasingly unstructured ❖ By 2022, all new IP Cameras will support embedded CNNs ❖ By 2030, the majority of cameras connected to the internet will not stream video
- 10. Movidius - 深度学习 vs. 传统图像处理算法 深度学习是不是只适合图片分类呢？ Movidius（就是去年被Intel收购的那家深度学习芯片公司）的答案当然 是"不"。Movidius会介绍一些也同样可以全部或部分应用深度学习的领域，比如：手势识别和跟踪，SLAM等， 而其他一些图像处理算法（比如ISP，图像拼接，点云处理等）可能还暂时用不上深度学习。
- 11. 13.7.2017 г. 11 Imagry - 在终端上运行深度学习 Imagry是一家以色列的深度学习算法公司，他们将介绍如何在移动终端上进行深度学习计算，特 别是如何在终端上对新的学习数据进行处理。
- 13. 微软 - 更好地标记图片，更好地识别表情 机器可能比你更清楚你老婆是不是生气了。微软开发的情绪API (Emotion API)可以识别8中表情： 生气、藐视、害怕、厌恶、开心、悲伤、惊喜以及面无表情。毕业于清华和卡内基梅隆的微软的 Cha Zhang博士会介绍这个造福所有已婚男人的算法，图片标记的质量会很大程度地影响深度学 习算法的准确性，Cha Zhang博士会介绍他们是如何通过众包的方式进行图片标记，并且管理标 记的质量的。
- 14. 13.7.2017 г. 14 Tyco - 识别火情 火没有固定形状，没有固定大小，比较难于识别。Tyco(泰科)是全球 最大的消防、安防专营公司，他们会介绍如何用CNN对火情进行识别。
- 15. 13.7.2017 г. 15 LUXOFT - 识别实际生活物品，解决实际生活问题 深度学习最开始是从识别阿猫阿狗开始的，但只拿来区分个猫狗是远远不够的。 LUXOFT会介绍如何用DNN实现在农业，建筑，医疗和零售等领域的深度学习应用。
- 16. 13.7.2017 г. 16 Magic Leap - 一个深度学习网络上跑多个应用实例 无人机，自动驾驶汽车，机器人等各种智能设备对深度学习有着越来越多的需求，往往需要同时跑多 个应用实例，比如人脸识别，场景识别，人脸跟踪等等。而如何在功耗和计算能力都是有限的嵌入式 设备上高效地运行多个深度学习应用呢？Magic Leap会介绍如何只用一个共同的深度学习网络，同 时跑多个应用实例。
- 17. 13.7.2017 г. 17 Amazon - 摄像传感器和传输参数对机器学习的影响 对于好的脑子，如果进去的是屎，出来的也还会是屎。深度学习也是如此，如果摄像头采集和传输的图像数据很垃圾， 那么结果和好不到哪里去。Amazon显然是在Amazon Go的试点过程中就深刻体会到这一点了。Amazon会分享摄 像头调校参数以及传输参数对深度学习算法效果的影响，给出改善识别准确率的具体调校具体方法。
- 19. 13.7.2017 г. 19 NVIDIA - 搞清楚那些图形API 图形处理API有很多，包括OpenVX, OpenCV, OpenCL, Vulkan, CUDA, TensorRT等等，你的项目中应该用哪个？ 有谁比Khronos的总裁更适合回答这个问题的呢。
- 20. Intel - 让OpenCV跑得更快 OpenCV的首席架构师会谈谈如何在深度学习和嵌入式领域更好地发挥OpenCV的 性能，看看透明API，Halide, OpenVX等技术是如何在行人检测应用中发挥效能的。
- 22. Google - 用高通的低功耗DSP运行TensorFlow Google和高通合作使用DSP更高效地运行TensorFlow。高通的Hexagon DSP 一直是被低估了的计算资源，用来跑深度学习引擎，飞控算法，光流算法等运 算非常适合。这里Google会介绍相关的工作，包括所做的基准测试结果。
- 23. ARM - 用ARM算子优化深度学习算法 ARM提供了针对深度学习优化的底层算子（ARM Compute Library），来识别食物，计算食物的卡路里。有demo。
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- 25. 13.7.2017 г. 25 中科创达 (Thundersoft) - Camera交钥匙方案及开发套件 好的Camera系统涉及的因素很多，传感器，镜头，马达，驱动，ISP，内核，多媒体框架， 算法，应用等等，每个环节都涉及复杂的专业知识和经验。Thundersoft介绍如何用交钥匙方 案的方式更高效地开发Camera系统，并且展示专门用于Camera系统开发的套件。
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- 32. 创造丰富多彩的智能世界
- 33. the Messy World of Intelligence 7/13/2017 33
- 34. the Messy World of Deep Learning 7/13/2017 34Thundersoft TPU SNPE
- 35. A Typical IoT Team 7/13/2017 35
- 36. Too Much to Build a Vision Product 7/13/2017 36 Operating System Camera Solution Product • Linux, Android or RTOS? • Low Footprint • Quick Boot Time • SoC Support • Camera H/W Selection • Driver Development • Camera Tuning • Camera Features • Quality Control • Certification Support • H/W Customization • Stability Test Algorithm Dev. • Algorithm Design • Benchmarking • Optimization • Integration
- 37. To Live on the Edge 7/13/2017 37
- 38. Thundersoft Overview 7/13/2017 38 ❖ Founded in 2008 ❖ Smart Device OS & Platform ❖ 3000+ SW/HW Engineers ❖ IPO in 2015 ❖ Worldwide Presence Mobile Automotive Multi-OS and Multi-Platform Support Key Market IoT Security & Enterprise
- 39. What We Do OS Customization Android OS Upgrade Carrier Certification Customer Technical Support Component Verification and Driver Development BSP&APP Maintenance • Small RAM • Fast Boot • Power Saving • System Tailoring • Hardware Security • Secure APPs • Network Security • Device Management • Camera Tuning Turnkey Solution • Dual Camera • 360 panorama • Face recognition • Object tracking • Deep learning • Sensor Fusion • TurboX Series SoM Products • Reference Design of Drone, Smart Camera, AR/VR and Robot • Customization • APP & UI/UE development • Global Carrier Certification • Automatic Test Solution • FOTA Solution • IVI • Automotive HMI • Digital Cluster • MDM • Mobile office • Enterprise security • APP development tools Mobile Automotive Enterprise & Security IoT System Optimization Security Image Processing Computing Vision 7/13/2017 39
- 41. 13.7.2017 г. 41 中科创达 (Thundersoft) - Camera交钥匙方案及开发套件 好的Camera系统涉及的因素很多，传感器，镜头，马达，驱动，ISP，内核，多媒体框架， 算法，应用等等，每个环节都涉及复杂的专业知识和经验。Thundersoft介绍如何用交钥匙方 案的方式更高效地开发Camera系统，并且展示专门用于Camera系统开发的套件。 Camera Turn-key Solution
- 42. Thundersoft Camera Solution 7/13/2017 42Thundersoft HW OS Algorithm Services Products BSP HTTP Server Video Algorithm System Tuning Face detection, recognition EIS, Motion detection Stability, Performance, Power, Image Quality Multi-Media Framework Drivers/Camera/V4l2) Camera Service Encoder Control Engine Connectivity WiFi, USB2.0/3.0 Ethernet I/F(RJ45) RTSP Server HW Design Camera Reference Design 8~13 Megapixel Camera 4K, H264(AVC), 265(HEVC) Algorithm Mobile App Camera Tuning Cloud
- 43. Deep Learning in the Device 7/13/2017 43 Segment Your Food Recognize Your Food • Up to 700 diverse dishes • Up to 80% Top-1 accuracy • Up to 6 FPS with only model optimization • 5x performance boost using Deep Learning Engine • Depth camera • Relative precise bounding contours • Calorie counting
- 44. ❖ Overview ► A clip-like BLE wearable device, measure biological information such as physical activity information, heart rate information, stress level, sleep information ► Transfer the sensor data from device to Gateway and IOT cloud. ❖ Use Scenario ► wear on the belt, gather and process the the sensor data from the devices ► place on the cradle, detect the pressure data by connecting a close soft tube which placed under-the-bed ❖ Gateway Type ► Proxy on smart phone ► Dedicated smart gateway Smart Belt 7/13/2017 44 • Cortext M4 + BLE Module • Accelerometer + Pressure Sensors • mbed OS 5.4 • Body Position Algorithms
- 45. ThunderConnect 7/13/2017 45 •Data Collection •Data Pre-processing •Security Auth •Basic Algorithm •Connectivity •Data Storage •Security Bridge •Advanced Algorithm •Connectivity •Basic Analysis •Autonomous Mgmt •Data Storage •Security Service •Premium Algorithm •Data Analysis •Device Management •FOTA Robust ·Configurable ·Secure ·Flexible ·Developer Friendly
- 46. 机会与挑战 7/13/2017 46 更小 • 更小硬件：智能传感器 • 更小系统：K级OS • 更小应用：HTML5应用 更安全 • 生物认证 • 防物理攻击 • 安全操作系统 更快 • 快速通讯：5G • 极速启动： <1s • 快速修复：热补丁 更简单 • 交互简单：超声，眼球，脑电 • 开发简单：自动测试 • 优化简单：自动优化 更智能 • 智能汽车 • 情绪理解 • 智能卫星 更强大 • 深度学习处理器 • 全面异构计算 • 多层次分布式计算
- 48. Thanks Website: http://www.thundersoft.com/ Contact us: biz@thundersoft.com +86-10-62662686 Address: 4th floor, Taixiang Building 1A#, Longxiang Road, Haidian District Beijing, China, 100191 7/13/2017 48