This document provides an overview of developing an IoT service by learning from case studies. It discusses technologies used in an solar energy monitoring web app including AMQP, WebSockets, Azure Web Apps, Arduino, Raspberry Pi, and IoT gateways. It also outlines Azure services that can be used for streaming analytics including Event Hubs, Stream Analytics, HDInsight, and Machine Learning. Key capabilities of Event Hubs are mentioned like scalability, integration with analytics services, and storage adapters.

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사례를 통해 배우는
IoT 서비스 개발

6. SpaceOne
Solar Energy Monitoring
Web App Database

7. http://www.amqp.org/
http://www.joinc.co.kr/modules/moniwiki/wiki.php/man/1
2/websocket
WebSocket
https://azure.microsoft.com/ko-kr/services/app-service/web/
Azure Web App

14. Arduino
netduino
Visual Studio
(C++, C#)
Devices Sensor Hub

15. Raspberry Pi 2
OS: Windows 10 or Linux
CPU: Broadcom BCM2836 ARMv7
Quad Core Process
900Mhz
Memory: 1G
GPU: Internal 250Mhz
Interface: HDMI
USB x 4 port
40Pin GPIO
Storage: microSD
Network: Ethernet
Audio: 3.5mm audio jack
Devices Gateway
IoT Gateway
MDS테크놀러지
DragonBoard 410c

16. Windows 10 IoT Core

17. Raspberry Pi 2 Intel Minowboard DragonBoard 410c

20. Guaranteed FIFO, with push-style API, up to 80GB maximum size, 10,000
queues per namespace, 2,000 messages per second, 256KB per message.

21. A higher level abstraction from queues, enables pub/sub models with similar
scale out capabilities and consistent pricing

23. 



24. Event Sources Cloud Services
Storage &
Analytics
Custom Code &
3rd Party Services
Web/Mobile
User Interfaces
Integration
Services
Event Hub
- Hyper Scale -
- Fully Managed -
- Interoperable -
- Secure -
- Cost Effective -

26. BigData = HDInsight
Real-time = Stream Analytics
Machine Learning
= Azure ML

32. TKE Remote Monitoring

33. ProcessingCollectionProducers
Low power
devices
(RTOS)
IP capable
devices
(Windows/Linux)
Field gateway
Legacy IoT
(Custom protocols)
Custom Cloud
gateway
AMQP/HTTP
C, .NET, Java…
MQTT/COAP/Custom
1 Day message
retention,
Consumer groups
Partitioned receivers
Check-pointing
Partition distribution
APIs
Low end-to-end latency
Easy integration with
analytics frameworks
and services
Configurable adapters
for storage devices
-
AMQP/HTTP, C, .NET, Java…
Scale on throughput (GB/s)
and concurrent senders
(1M with auth./flow control)
Azure DBs
Azure Storage
Custom code
Stream Analytics
Storm
Storage
adapters
Service Bus
HDInsight
Event Hubs
Services Data Service