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AWS IoT Lab Introduction


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近年來,物聯網(IoT)產業正以驚人的速度成長中,相關的應用與服務也陸續問市,而包含物聯網(IoT)、人工智慧(AI)與機器學習(machine learning)等科技的革新,致使從新創企業乃至傳統產業皆投入這一波新科技的發展,更添產業動能,尤其是在製造業、運輸及物流、公共安全、智慧城市等幾大面向。

據消費及商業企業服務供應商JT Group白皮書預估,到2020年全球物聯網累計裝置量(installed base)將達204.1億台。更多企業也將改變其商業模式,由產品導向轉為服務導向,客戶機構採購的不再只是硬體產品,而是尋求整套完整的解決方案。AWS 即將於3/7 (四) 舉辦『AWS AIoT未來智造高峰論壇』,持續以創新、全球視野帶領您與您的企業一起探索物聯網價值最大化的關鍵。

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AWS IoT Lab Introduction

  1. 1. AWS IoT Lab Introduction Andy Kwong Manager, AWS IoT Lab AWS
  2. 2. We need data, connected devices, and end-to-end solutions to solve business problems Why IoT? Know Act, make Right decision Improve & Predict
  3. 3. • IoT Eco-System Enablement (Hardware/Software) • Accelerate IoT solution deployment for verticals Why IoT Lab – Our Mission? City/Utility Commercial/IndustrialRetail/Consumer
  4. 4. • Global Technology Hub • Years of semiconductor/foundry experiences • Electronic component/product design experiences (OEM/ODM) • Lab Engineers with chip/firmware expertise • Regional Advantages • Proximity to the larger region of manufacturing hub • Government support for hi-tech manufacturing Why IoT Lab in Taiwan – Our Goal?
  5. 5. • Build local solutions • Getting devices qualified • Getting solution design and fine tuned • Deploy global products • Hardware from OEM/ODM • Applications & solutions from partners/IoT Lab • Powered by AWS platform Why working with IoT Lab – Our Vision?
  6. 6. IoT Platform for Growth Problem LG’s new smart products include embedded WiFi chips for communication and AI technology for learning about their user’s behavioral patterns. LG built its own IoT Platform but experienced difficulties in supporting growing number of connected devices. Solution Migrated its platform of 1000+ servers from its data center to AWS. Using serverless architecture with AWS Lambda to register and mange devices on the cloud through IoT Core, and store data in Amazon ElastiCach and DynamoDB. Impact By using AWS for the new IoT Platform, LG saved 80 percent in development cost. We found that it was better to receive help from AWS solutions architects compared to solving problems ourselves. We enables developers to focus on writing business logic for LG service scenarios. Kim Kunwoo Chief of the Service Development Team LG Cloud Center, LG Electronics “ ”
  7. 7. • Business Opportunities • Connect hardware partners with AWS customers • AWS credits and benefits • Marketing Opportunities • AWS Partner Device Catalog • Branding and co-marketing opportunities • Technical Differentiation • Integration with AWS platform • Expertise at AWS IoT Lab Why Device Qualification Program?
  8. 8. Partner Device Catalog As customers evolve in their digital transformation journey, they are looking for ways to quickly and efficiently move certain workloads to the edge. Collaborating with AWS helps us bring the best of the cloud to the edge on Lenovo infrastructure and devices. Lenovo has qualified industry-leading servers, PCs, and intelligent devices through AWS’s simple and easy to use AWS IoT Device Tester qualification tool found in the AWS Device Qualification Program for AWS IoT Greengrass and listing the hardware in the AWS Partner Device Catalog. Wilfredo Sotolongo VP and GM of IoT Lenovo Data Center Group “ ”
  9. 9. 2017 2018 2019 Greengrass GA Jun 2017 FreeRTOS GA Nov 2017 87 Greengrass Devices 34 IoT Core Devices 50 KVS Devices Mar 2019 74 Greengrass Devices 32 IoT Core Devices re:Invent 2018 50 Devices Sep 2018 AWS IoT Lab Started Oct 2018 5 Partner Kits Sep 2018 10 Partner Kits re:Invent 2018 12 Partner Kits Mar 2019 Device Qualification Program and Device Tester Development (Greengrass+ FreeRTOS) Aug-Oct 2018 AWS IoT Lab – Timeline Alexa/IoT POC IoT/ML/Summerian POC IOT/BI POC Nov 2018 AWS IoT Lab TW Announced Mar 2019 Alexa/IoT/ML POC Feb 2019 Greengrass
  10. 10. ERP PLM APS Prototyping, Pilot Production, Machine Evaluation, System Integration and Scale-up Large scale demonstration site, integrated test environment of Industry 4.0 VMX = Virtual, Multi-machine (different brand of manufacturing machinery) Integrated with AWS (Edge Computing + IoT Gateway + Cloud) Intelligent Machinery Technology Innovating a better future
  11. 11. 以工業物聯網打造 智慧供應鏈 彭達仁 副組長 工研院 智慧機械科技中心
  12. 12. Smart factory powered by AWS IoT VMX integrated with OPCUA on Greengrass and AWS IoT Device SDK Stability, Device Management, Analytic, Resource Tracking achievements ITRI/AWS IoT Lab Engineering Partnership AWS
  13. 13. ERP SMB App PLM APS AWS
  14. 14. AWS
  15. 15. Thank you.
  16. 16. Vortex Data River enabling vendor- neutral device ecosystem Integrated with AWS IoT Greengrass connecting with AWS IoT platform Complete, efficient data acquisition leads to way to the business of the future Edge Computing Platform Enabling Data-to-Decision
  17. 17. ADLINK “AIoT at the EDGE” Chia-Wei Yang Business Development Manager ADLINK Technology
  18. 18. ADLINK Overview Over 20 Years of Embedded Experience >1900 Employees Established August Publicly Traded Since Taiwan Stock Exchange Listing USA Canada France India Korea Israel Chairman Jim Liu President Daniel Yang Revenue (USD) Capital (USD) $73M Headquarters in Germany UK Singapore China Japan ● ● ● ● 1995 Taipei, Taiwan 2002 TAIEX: 6166 $297M (Y2016) $350M (Y2017) Market Cap (USD) $468M ●
  19. 19. AIoT at the Edge Data 2 Decision Convert Info to Decision & Action to enhance overall Efficiency Data River Steam the RIGHT INFO to RIGHT Place @ RIGHT Time Heterogeneous Computing Platforms Powerful EDGE, Integrated CPU, VPU, FPGA, GPU Industrial Automation Telecom & Networking Test & Measurement TransportationMedical / Healthcare Infotainment & Vending Military & Aerospace AWS
  20. 20. Source: Engineering Collaboration Accelerating IoT - EDGE Development • Collaborating in certificating AWS IoT Greengrass with ADLINK EDGE Devices • Enabling 3rd party DL / ML modeling builds on AWS • Integration of AWS RobotMaker Service and ADLINK ROS2.0 Robotic Platform
  21. 21. Synergy for Factory of the Future AI Machine Vision Industrial IoT Robotic (Mobile)
  22. 22. Thank you.
  23. 23. Connectivity to AWS IoT platform Accelerated ML inference with Intel Movidius and OpenVINO Ubiquitous solution designed for each application domain from industrial IoT to smart retails. Industrial IPC Solutions Designed for each industrial and business applications
  24. 24. ASRock Industrial AIoT Edge Devices Solution Jeremy Pan Project Manager ASRock Industrial
  25. 25. Thank you.
  26. 26. Integrating hardware devices, software applications, and the cloud for customers. Innovative solutions adapt to different vertical industries with device and cloud working in harmony. Integrate protocol by click and done (BLE, Z-Wave, CAB Bus, ZigBee, ModbusRTU, Modus TCP, WiFi) Make IoT A Reality One day, all devices will be connected to the Internet and will be given intelligence
  27. 27. Josh Chai 翟海文 CEO SoftChef 軟領科技 AWS IoT Labs Collaboration
  28. 28. Activities with AWS IoT Labs
  29. 29. MCU/MPU Integration Test
  30. 30. Edge Intelligent & ML
  31. 31. Interoperability & Integration
  32. 32. Thank you.
  33. 33. Help Wanted City/Utility Commercial/Industrial Solution, Solution, Solution ... Customers have business initiatives Partners help on POC & Prototypes Retail/Consumer
  34. 34. Target • Smart retail analytics and video/image analytics partners • Smart retail facility operators Problem • Need actionable data to engage customers, optimizing the business and making smarter data- driven decisions. • Need accurate, real-time insights of the audience’s spontaneous behavior, interest and demographic profile. POC/Solution • Based on sophisticated Computer Vision and Face Analysis algorithms, the software enables detection and measurement of multiple faces in a video frame. The software used in combination with a HD/UHD4K camera sensor to detect and track audience facial information. • Actionable data (Viewers/OTS, Dwell Time, Attention) with anonymous audience visual analysis with customer ML model (Demographics, Age, Gender, Location and Mood Insights) IoT Core Amazon QuickSight Amazon S3 Kiosk w/ Video Analytics Amazon EMR (w/ Zeppelin) Smart Retails Prototype
  35. 35. Amazon Lambda Amazon SNS Amazon SQS IoT Core Target • Smart home device manufacturers • Smart facility solution partners • Smart school Problem • Hardware manufacturer have limited knowledge with Alexa/IoT integration • Challenges with best practice on integrating the IoT platform with Cloud POC/Solution • Prototype GreenGrass/FreeRTOS/IoT SDK plus Alexa AVS/AIS API • Prototype best practice OTA, Device Management, and serverless lambda functions. • Include customer facing application template for device registration/provision. • Enable Alexa integration smart home solution using AWS IoT platform (and documented for other smart home product manufacturers). Smart Home Prototype
  36. 36. Alexa and IoT Integration Problem Looks to improve customer loyalty by delivering new features for Vizio’s customers such as voice control. However, Vizio don’t want to build an IoT solution from scratch to deliver this improved customer experience. Solution Working with AWS, we created a secure and scalable implementation using AWS IoT platform and serverless architecture to deliver Alexa voice skill to our TVs. Impact Delivered a working prototype in a few days, and soon after delivered new Alexa voice skill to millions of TVs in the field. Vizio now have a high scalable IoT backend build on AWS, which can now power many more applications that will deliver new features. Working with AWS has been one of the most positive engagement with a technology company. Bill Baxter Chief Technology Officer VIZIO “ ”
  37. 37. Application (SNS, SQS, APIG, Cloud9) Target • Smart retail hardware/solution partners • Smart Facility/Building/Hotel/Community operators Problem • Lack of end-to-end solution integrating IoT/AI platform with Operational Tech • Lack of resources for vertical application and a marketplace for these applications POC/Solution • Work with partners and customers to create technology prototypes and templates for: • Facial/People Recognition (VIP, Intrusion Detection, guest registration, guest access permission) • People Tracking (tailgating, people search) • Operational tools, provisioning tools, and management tools. • Analytics (traffic patterns, hot spot for guest visit) IoT Core Smart Store Front Data Lake (S3, Dynamo, Redshift) Analytics (Athena, Kinesis, QuickSight) AI (SageMaker, Rekogition) MQTT (Meta Data/Shadow Update) Direct Secure Connect (Raw Data, Log, Photo, Video) Smart Facility/Hotel POC
  38. 38. Application (SNS, SQS, APIG, Cloud9) Target • Smart device provisioning/manufacturing partners • Smart utilities operators, community owner associations, city planning authority and data carrier Problem • Lack of end-to-end solution integrating IoT and provisioning platform with operational tech • Lack of market-ready templates for big-data/ML analytics POC/Solution • Work with partners and customers to create technology prototypes and templates for: • Facial/people Recognition (VIP, people search, intrusion detection). • Object Recognition (license plate, parking, toll). • People/Object Tracking (tailgating, Left passenger, unattended object/bag/trolley, parking clearance). • Operational tools, provisioning tools, and management tools. • Analytics (traffic patterns, hot spot). IoT Core Smart Sensors/Meters Data Lake (S3, Dynamo, Redshift) Analytics (Athena, Kinesis, QuickSight) AI (SageMaker, Rekogition) MQTT (Meta Data/Shadow Update) Direct Secure Connect (Raw Data, Log, Photo, Video) Smart City POC Field applications for provisioning and maintenance
  39. 39. Trusted IoT Platform Efficient, cost effective serverless platform Support most popular ML frameworks Why working with AWS on AIoT?
  40. 40. Thank you.