1. Inside the Technical Data Cloud
Julien De Freitas
Engineer's degree / M.Sc. in Electrical Engineering
Applications Engineer
National Instruments Switzerland
2. Example
A NI integrator sells Autonomous Surface Vehicles (ASV) that use
embedded controllers and loggers
How to manage data storage and access from different
distributed systems?
3. Outline
• From Distributed Measurement Systems to NI Technical Data
Cloud
• Introduction and Definition to „The Technical Data Cloud“
• How can „The Cloud“ help you?
4. Outline
From Distributed Measurement
Systems to NI Technical Data Cloud
7. Distributed / Inaccessible / Remote
Measurement Systems
Types of monitoring systems:
• Environmental
• Machine condition
• Power
• Green energy
• Pipeline
8. Distributed / Inaccessible / Remote
Measurement Systems
• Any application where:
• Measurements are made with geographically distributed
systems
9. Measurement Challenges
• Expensive or difficult to reach system locations
• Limited storage at site
• Access to data at any time and anywhere
• Many data producers, many data consumers
10. Outline
Introduction and Definition to „The
Technical Data Cloud“
15. Description
Services to store, manage, and access data from distributed
monitoring systems based on standard Internet communication
and security
System 1
System 2
19. Data Structure in TDC
A “Project” allows a user to
organize online data
Data Project
Measurement System HTTPS
chan1 Measurement
Device chan2 chan1
chan3
Sensors chan2
A device is specifically chan3
provisioned to log data The user device
to the cloud creates online channels
when it logs data
23. But the Top Benefit is
• You will gain in scalability / elasticity
Cloud Approach to Infrastructure Expansion
Data storage
Time
24. Easy to implement
• Use LabVIEW TDC APIs (Application Programming Interface)
• Create low-level HTTP requests in a text-based programming
language
25. LabVIEW TDC APIs
• High Level APIs
• Data transmission can be encrypted by SSL
• Data caching during broken connection
• Supported on both Windows and NI Real-Time targets
Open Action Close
26. Easy to test the use of future TDC
• The „official“ TDC planned for the beginning of 2014.
• You are able to test it with the Early Access Release.
• For more information, do not hesitate to ask me.
What do you need to start?
Ask for username and password to access TDC
Install the LabVIEW API for TDC
27. Summary
• Services to store, manage, and access data from distributed
monitoring systems based on standard Internet communication
and security
• Easy to implement: LabVIEW TDC APIs
• Official release of TDC planned for the beginning of 2014
28. Try
“The true method of
knowledge is experiment.”
[William Blake]
29. Try for free
Try „Technical Data Cloud“ for free
30. Demonstration 1: Wind farms in Switzerland
1 4 Data Readings
Data Dashboard
TDC Access
2.0
Data Management/ Access
Readings keys
2 TDC
Management
Portal
tdcportal.niwsc.com 3
Data Management/
Generations/Readings
32. References and links
• Inside the NI Technical Data Cloud – TDC Overview, Benefits of TDC
http://zone.ni.com/devzone/cda/epd/p/id/6422
• Technical Data Coud Product In-Depth – Details about Data types in the Cloud, TDC APIs,
Authentication
http://zone.ni.com/devzone/cda/epd/p/id/6421
34. Questions
Thank you for your attention!
For any questions, startup help, support,
do not hesitate to e-mail me:
julien.de.freitas@ni.com
35. Thank you
Many thanks to Derrick Snyder – Product Marketing
Manager at NI Corporate – for his support
Editor's Notes
(1)Take time to explain exampleThe ASV is a completely autonomous small surface craft. Its autonomy and reliability are guaranteed by its state of the art equipment. Navigation itself is monitored by a DGPS positioning system. The progress of the ASV is tracked by a mobile control station (MCS) which can either remain on-shore or be placed on-board a mother ship. The mobile control station is needed to define and preprogram the mission of the ASV before its departure, launch the ASV, monitor its progress (the MCS can retake control of the ASV at any moment) and recover it at the end of its mission. This paper describes the general architecture of the ASV and the technological choices made. It then focuses on the identification process and on the development of the control system.(2)Break(3)Ask question- transition with outline
Keypoint:How can „The Cloud“ help you? = Benefits, what applications
Measure data locally .... Distribute globally (Distributed Measurement Systems)
-- different types of business lines
-- definition of a remote measurement system -> next slide
Big pb: - new challenge
In each of these application areas, it is extremely challenging for an engineer or technician to access one of these measurement devices to retrieve stored data, let alone hundreds or thousands of devices. Even if the data can be accessed (either physically or remotely), there still exists the secondary challenge of collecting data from multiple locations in one place and then sharing important data so that others can access it for analysis or reporting.
Solution: TDCPut all the data togetherCompare data from different locationsAccess to these data ANYwhere-- Definition: TDC -> 1st part: One goal: Storage of the data
-- 2nd goal: manage and access your data
Anywhere ... ANY types of devices: ipad, smartphones, PC (website, LV) Important point !!!! -- 3rd goal: from different locations
And not only one and notonly at one place.... It could be in Africa, EU, US....-- 4th point: Data transmission in safe (find more details about it)
SECURITY: https (Hypertext Transfer Protocol Secure) - SSL/TLS protocol-- Summary
- examples of data computing in ‚real‘ life
-- take the dropbox example
Dropbox allows you to create a special folder on each of your computers. Dropbox synchronises every folder on each of your computer so that it appears to be the same folder (with the same contents).Files placed in this folder are accessible through a website and mobile phone applications.--- transition with TDC to explain the external communication + internal structure
Any type of devices can have access to the cloud --- only keypoint: have a internet communication or have the posibility to publish the data over internetAny types of devices to read and write: ipad (with data dashboard app), pc (with TDC Mgmt Portal), PC (with LV)Internal structure: real data + descriptive informationIf event -> e-mail notification -- next feature-- multitenant architecture
-- Data structure: Project / Meas / Chan
Garanteed uptime: it will work at anytime Lower cost of entry: it will cost much less that building its own arhitecture No IT headaches: use only the architecture suggested by NI. No need to build another one On-demand service: it will adapt to the demands of the customer
Sending data to and retrieving data from TDC is possible from any application running on any PC or intelligent device that is connected to the public internet via an Ethernet, WiFi, cellular or satellite connection. TDC has a set of web service APIs based on the RESTful standard that allow for sending and receiving data; users have two options for accessing those APIs:Use the LabVIEW TDC API. This API is a set of VIs (similar to a toolkit) for opening a connection to a particular TDC project and then reading, writing, updating or deleting data. Using this approach, a LabVIEW user works at a very high level (similar to file I/O) and does not need to understand low-level HTTP commands. This API also supports functionality like automatically retries in the event of a lost internet connection and VIs for temporary caching on disk so that data is not lost.Create low-level HTTP requests in a text-based programming language. TDC projects can also be accessed using C, C++, C#, and Python using the raw RESTful webs services directly. can be used to upload data to and access data in TDC because its APIs are based on standard REST web services. However, this approach is much more complex and requires knowledge of programming with HTTP and XML.
Most engineers are used to the idea of purchasing computing as a product – such as the procurement of a laptop or server machine – but with the advent of cloud computing, computational, data storage, and software resources are increasingly being delivered and leveraged as a service. Affectionately referred to as “the cloud,” this networked, shared computing infrastructure is accessible via standard internet technologies and offers users the benefit of elastic, on-demand computing services that are metered by use. In other words, instead of working with IT in order to allocate the time and budget necessary to obtain, set up, and maintain the capital investment in a server resource, leveraging the cloud allows users to quickly scale up (or scale down) use of computing resources in an agile fashion and only pay for what is used.
