IoT行业案例分享

Lit Li | 李婷 微软中国有限公司 DX Echo Wang | 王巍 微软中国有限公司 EA

IoT-B101

课程议题

IoT的发展和市场趋势

微软云+端的IoT平台

IoT的行业解决方案

相关资料

25 BILLION Connected “things”

will be in use by 2020

Gartner

$7.2 TRILLION worldwide market for IoT solutions

by 2020

IDC: Worldwide and Regional Internet of Things (IoT) 2014–2020

Forecast

IoT技术四要素

连接 数据 分析 物体

Retail Manufacturing

And more!

25.5 billion devices

$72.5 trillion market

Consumer

Finance Healthcare

从设备到云端的全面解决方案

为广大设备提供专用的IoT版本

20 年嵌入式行业经验

一个windows平台匹配所有设备

对企业友好、对创客友好

为现代化IoT环境设计

免费的 IoT Core 版本

云端的IoT服务和解决方案

开箱即用

按量付费、按需扩展

全球就绪、超大规模

全面安全和隐私保护

支持Windows, Mbed, Linux, iOS, Android, RTOS

Azure IoT

Microsoft IoT 平台

Vehicle Tracking Device Cameras Power Meter Load Meter Smoke Fire Alarms Humidity Sensor Flow Meter Occupancy Sensor Temperature Sensor

Machine Controller

Vehicle Tracking Smart Grid General Equipment Retail Kiosk Smart Home Healthcare Smart Building Automation Digital Advertising Fire Detection

MAKER

Intelligent Device

OEM

Device-as-a-Service

ENTERPRISE

Intelligent Operations

END USER

Personal Productivity

Windows I0 IoT FIELD

GATEWAY

Data Ingress, Egress Data Storage, Security Event Processing Analytics Platform

Microsoft Azure

Remote Monitoring & Servicing

Asset Management

Usage based Billing

AllJoyn, Device Orchestration

Device & Firmware Updates

Command & Control

Content Delivery

Compliance Management

Predictive Maintenance

Analytics (BI, ML)

Enterprise integration

Data Visualization

NETWORK

Windows 10 IoT Enterprise Desktop Shell, Win32 apps, Universal Apps and Drivers

1 GB RAM, 16 GB Storage

X86

Windows 10 IoT Mobile Enterprise Modern Shell, Universal Apps and Drivers

512 MB RAM, 4 GB storage

ARM

Windows 10 IoT Core No Shell, Universal Apps and Drivers

256MB RAM, 2GB storage

X86 or ARM

Devic

e C

ost

Resource Requirements

智能终端b

Producers Connect Devices Storage Analytics Take Action

Event Hubs SQL Database Machine

Learning Azure Websites

Service Bus Table/Blob

Storage

Stream

Analytics Power BI

External Data

Sources DocumentDB HDInsight

Notification

Hubs

External Data

Sources Data Factory Mobile Services

BizTalk Services

{ }

Producers

参考架构

Data Ingress Data Egress Data Processing

Retail Devices

Service Portal(s)

Message Mgmt & Storage

Custom Code Deployed on Azure

LoB Apps

Third-party

Systems

External

Analytics Tools

Custom Portal &

Clients

Third-Party Apps

Uses Event Hub, Storage, SQL DB, & Services

<AMQP/>

• 基于EventHub的数据采集 • 高并发

• 海量用户数据采集

• 基于Stream Analytics的流数据处理 • 结构化数据转化

• 实时处理

• 基于Storage/SQL DB/HDinsight的结构化与非结构化数据存储 • 丰富/成熟的集成接口

• 多格式的数据存储

• WebApp/PowerBI/Azure App Service

• 提供满足不同需求的业务数据展现

• 集成Cortana实现语音交互

智能仓储

Azure

Event

Hub

Azure Stream

Analytics

• 业务终端

• 管理决策

智能仓储/设备/环境监控

Azure Storage/

Azure SQL

管理员/监控人员

Azure App

Service Power BI Web App

• 下行管理控制指令

• 基于EventHub的数据采集 • 高并发

• 海量设备部件监控数据采集

• 基于Stream Analytics的流数据处理 • 结构化数据转化

• 实时处理

• 基于Storage/SQL DB数据存储 • 丰富/成熟的集成接口

• 多格式的数据存储

• 基于Machine Learning的预防性维护决策模型

• ML studio简化建模

• 预测性分析平台

预防性维保

Elevator

Azure

Event

Hub

Azure Stream

Analytics

• 维护保养工单

• 维护保养Dashboard

特种设备预防性维保

电梯设备数据

Azure Storage/

Azure SQL

运维管理人员

Machine Learning

(predictive analytics)

Power BI

Other Data

Sources

设备状态日志 设备维修报告

预测性维护大数据平台

其他数据

预防性维护 & 被动式维护

机器学习模型

站点ID 设备ID 设备特性选取 设备统计类型（交易） 检查日

StationID DeviceID Feature_1 Feature_2 Feature_3 Feature_4 Feature_5 Dev_Stats_1 Dev_Stats_2 Predictive

Day

安河桥北 TV01 48 13 40 9 4 20 30 5 Days

北宫门 TV02 57 13 35 17 10 40 80 7 Days

Mean Absolute

Error

Root Mean

Squared Error

Relative Absolute

Error

Relative Squared

Error

Coefficient of

Determination

Linear Regression 1.645314 2.263212 0.635882 0.35498 0.64502

Neural Network

Regression 1.7183 2.235722 0.66409 0.346409 0.653591

Decision Forest Regression 0.836082 1.532812 0.32313 0.162829 0.837171

Booted Decision Tree

Regression 0.557559 0.921331 0.215486 0.058828 0.941172

Bayesian Linear Regression 1.661037 2.270156 0.641959 0.357161 0.642839

• 基于EventHub的数据采集 • 高并发

• 海量用户数据采集

• 基于Stream Analytics的流数据处理 • 结构化数据转化

• 实时处理

• 基于Storage/SQL DB/Media的结构化与非结构化数据存储 • 丰富/成熟的集成接口

• 多格式的数据存储

• 支持Media的直播/录播/字幕检索

• 基于Machine Learning用户行为数据学习模型

• ML studio简化建模

• 提供用户行为数据

• 微软云平台其他人工智能服务

• Cortana

• Oxford

智能家居

Azure

Event

Hub

Azure Stream

Analytics

• 用户终端应用

• 服务提供商决策支撑

案例分享：智能家居

Azure Storage/

Azure SQL

用户/服务提供商

Azure App

Service

Machine Learning

(user experience analytics)

Other Data

Sources

极路由智能生活演示视频.微疯客.720p.v3.mp4

Managing trucks

with mobile devices

Connected Trucks Enable customers to connect to and manage

their trucks with a mobile device.

Grow New premium service business model with

a scalable fleet management system.

Scale Efficiently manage one million vehicles using

the central fleet management system.

案例分享：智能车队管理

Scania Architecture (Semi-Legacy)

Devices

Message Mgmt, Models & Storage Gateway Service

Public APN Datacenter

<AMQP>

X.509

…

…

Subscriber

Publisher

车队管理

Data-driven retail business

transformation

Efficiency Improve efficiency by tracking inventory location and shipping

status end-to-end to maintain on-shelf availability and reduce

out-of-stock situations.

Innovation Enable innovation by dynamically managing digital promotions on

vending machines and display content tailored to specific audiences.

Targeting Integrate data from smart shelves with point-of-sale and trade

promotions data to determine the most productive merchandising

treatments within stores.

案例分享：智能零售业案例

Hussmann Architecture (Recent)

Devices

Service Portal/Clients

Message Mgmt, Models & Storage

LoB Apps

Third-party

Systems

External

Analytics Tools

Custom Portal &

Clients

Third-Party Apps Gateway Server/Service

Retail Store

Datacenter

CHALLENGE SOLUTIONS BENEFITS

• No direct connection with mayority of installed base

which leads to a reactive customer service from the

OEM with relatively inefficient resolution processes

• Equipement Maintenance schedules are based on

defined time-intervals which is the reason that

services are performed to often, to early or to late.

• Service costs grow linear to the number of installed

machines. Similar learning curves like in production

for service operation necessary.

• Monitoring – visualizing real time data

• Reporting – Analysing and visualizing historical data

• Prediction – … predicted events

• Alarming – sending information to people

• Guidance – realtime communication

• Repair/Parametisieung – sending controls to the machine

• Portal – information & collaboration platform

• Mobility – mobile access from anywhere

• Integration – Integration with other Enterprise IT Systems

• Optimise cost structure for service organization

through new capabilities like e.g. Remote Monitoring

and Reporting, Remote Support and Diagnostic

• Provide new consulting services or business process

outsourcing

• Deepen customer relationship management and

improve customer loyalty

• Improve overall equipement, machine and device

performance and safety

www.InternetofYourThings.com

Krones: a manufacturer of industrial equipment for the beverage industry - presented together with Microsoft how M2M real-time communication between end user and OEM could look like.

案例分享：智能工厂

课后提醒

https://channel9.msdn.com/Events/Ignite/Microsoft-Ignite-China-2015

http://aka.ms/IgniteChina2015