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利用電腦視覺與人工智慧
創造更多物聯網價值
John Chang ( 張書源 )
資深軟體開發協理
john.chang@microsoft.com
Azure 雲的萬物論
物聯網架構
Custom Cloud
Gateway
Custom Cloud
Gateway
Field
Gateway
Device
VPN/ExpressRoute
OPC, HTTP, CoAP,…
Custom Protocols
Client SDK
IoT Edge
AMQP
Management app
Device registry/Management
Monitoring
Send commands
Client SDK
Management app
Device registry/Management
Monitoring
Send commands
Client SDK
Cloud protocol
gateway sample
Cloud protocol
gateway sample
AMQP, MQTT, HTTPS
Applications
- Companion apps
- Dashboards
- Controllers
- …
CoAP, AllJoyn, OPC,…
Device
Device
CoAP, AllJoyn, OPC, …
Device
Device
Device
IoT Hub
Field
Gateway
物聯網解決方案現況
依賴傳感器偵測環境狀態
傳感器誤差影響判斷結果
必須依賴大量傳感器
不易處理複雜的情境
需要整合不同傳感器判斷
需要大量投資在非本業項目
理想的物聯網解決方案 :
主動了解環境狀態並做出反應
理想的物聯網解決方案 :
主動了解環境狀態並做出反應
攝影機
麥克風
Custom Cloud
Gateway
Custom Cloud
Gateway
Field
Gateway
Device
VPN/ExpressRoute
OPC, HTTP, CoAP,…
Custom Protocols
Client SDK
IoT Edge
AMQP
Management app
Device registry/Management
Monitoring
Send commands
Client SDK
Management app
Device registry/Management
Monitoring
Send commands
Client SDK
Cloud protocol
gateway sample
Cloud protocol
gateway sample
AMQP, MQTT, HTTPS
Applications
- Companion apps
- Dashboards
- Controllers
- …
CoAP, AllJoyn, OPC,…
Device
Device
CoAP, AllJoyn, OPC, …
Device
Device
Device
IoT Hub
Field
Gateway
Data + AI
結合攝影機偵測環境狀態
降低傳感器誤判
降低傳感器數量
容易處理複雜的情境
深度學習讓影像辨識技術更成熟
OpenCV 可在 IoT Edge 篩選影像
Azure 認知服務支援影像分析
可與 Azure 其他服務結合
Sensor
Sensor
Sensor
Sensor
Sensor Blob Queue
Azure FunctionOpenCV
Computer Vision
Rule Engine
AzureIoT
Device Bot
SMS
Text
Phone
Call
Demo
智慧物聯網範例
Vision
200K celebrities
JSON:
{
"language": "en",
"orientation": "Up",
"regions": [
{
"boundingBox": "41,77,918,440",
"lines": [
{
"boundingBox": "41,77,723,89",
"words": [
{
"boundingBox": "41,102,225,64",
"text": "LIFE"
},
{
"boundingBox": "356,89,94,62",
"text": "IS"
},
{
"boundingBox": "539,77,225,64",
"text": "LIKE"
}
. . .
"faceRectangle": {"width": 193,
"height": 193,
"left": 326,
"top": 204}
“scores": { "anger": 5.182241e-8,
"contempt": 0.0000242813,
"disgust": 5.621025e-7,
"fear": 0.00115027453,
"happiness": 1.06114619e-8,
"neutral": 0.003540177,
"sadness": 9.30888746e-7,
"surprise": 0.9952837}
"faceRectangle": {"width": 193, "height": 193, "left": 326, "top": 204}
…
"attributes": { "age": 42, "gender": "male",
"headPose": { "roll": "8.2", "yaw": "-37.8", "pitch": "0.0" }}
Demo
使用 Custom Vision
Service 建立智能物聯
網方案
www.botframework.com
謝謝
john.chang@microsoft.com

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透過電腦視覺與人工智慧創造物聯網新價值

Editor's Notes

  1. https://kaboompics.com/photo/1780/dogs-behind-metal-bars https://kaboompics.com/page/license-and-faq
  2. https://kaboompics.com/photo/1780/dogs-behind-metal-bars https://kaboompics.com/page/license-and-faq
  3. Summary Millions of people worldwide have embraced Uber as a new means of reliable transportation and flexible income. To safeguard against fraud and enhance both driver and rider peace of mind, Uber uses the Face API, part of Microsoft Cognitive Services, to help ensure the driver using the app matches the account on file. The extra verification step is fast, works on all smartphones and in dim light, and scales to more than 1 million driver-partners. By using the Face API, Uber saved months of development work, time it could devote to tailoring the user experience. Challenge Uber sends photos of drivers to riders as soon as their ride is on the way, but occasionally the Uber driver who shows up doesn’t look like the person in the photo that the rider receives. Uber wanted to make sure that the person it had screened and approved was the person behind the wheel. Solution Uber decided to use photo-matching to verify drivers when they signed in to the Uber app. Drivers would periodically take and submit a selfie to verify their identity. Uber used the Microsoft Cognitive Services Face API to build its Real-Time ID Check feature. The Face API supported the ability to compare photos in varying pose, focus, and lighting conditions. Benefits Three-week development time and rapid time-to-market with new driver authentication step Amazing performance, which provides quick authentication without slowing down drivers Very high photo-matching accuracy Scalable to support up to 1 million users https://customers.microsoft.com/en-US/story/uber
  4. Why choose these APIs? They work, and it’s easy. Easy:  The APIs are easy to implement because of the simple REST calls.  Being REST APIs, there’s a common way to implement and you can get started with all of them for free simply by going to one place, one website, www.microsoft.com/cognitive.  (You don’t have to hunt around to different places.)  Flexible:  We’ve got a breadth of intelligence and knowledge APIs so developers will be able to find what intelligence feature they need; and importantly, they all work on whatever language, framework, or platform developers choose. So, devs can integrated into their apps—iOS, Android, Windows—using their own tools they know and love (such as python or node.js, etc.). Tested: Tap into an ever-growing collection of powerful AI algorithms developed by experts. Developers can trust the quality and expertise build into each API by experts in their field from Microsoft’s Research organization, Bing, and Azure machine learning and these capabilities are used across many Microsoft first party products such as Cortana, Bing and Skype. 
  5. Do you need an API that gives you actionable information about images used in your app? The Computer Vision API gives you the tools to understand the contents of any image. Create tags identifying objects, beings, or actions present in the image, and then craft coherent sentences to describe it. Whether you want to execute better image search, or you want to create an assistive app for the visually impaired, the Computer Vision API helps get the job done.
  6. How are you feeling? Can your app tell? With the Emotion API, you can build an app that recognizes emotions according to facial expressions—giving you the capability to provide an amazing, personalized experience. Using facial expressions, this cloud-based API can detect happiness, neutrality, sadness, contempt, anger, disgust, fear, and surprise. The AI understands these emotions based on universal facial expressions, and it functions cross-culturally, so your app will work around the world.
  7. Detect human faces and compare similar ones, organize people into groups according to visual similarity, and identify previously tagged people in images.
  8. Intelligent video processing produces stable video output, detects motion, creates intelligent thumbnails, and detects and tracks faces.
  9. Do you need an API that gives you actionable information about images used in your app? The Computer Vision API gives you the tools to understand the contents of any image. Create tags identifying objects, beings, or actions present in the image, and then craft coherent sentences to describe it. Whether you want to execute better image search, or you want to create an assistive app for the visually impaired, the Computer Vision API helps get the job done.
  10. Animation set to loop (replace /Build walk in ?) BOT Framework provides everything you need to build and connect intelligent BOTs that interact naturally wherever your users are talking, from text/sms to Skype, Slack, Office 365 mail, Facebook Messenger, Kik and other popular services. BOT Framework consists of three main components: BOT Connector, BOT Builder, and BOT Directory