Warp 10: the key enabler of digital transformation in IoT … and IT business From IoT and sensors to user applications, from maintenance to business services, Warp10 proposes a disruptive software technology which makes you to consider data analytics and artificial intelligence in a new and different perspective Cityzen Data www.cityzendata.com / www.warp10.io Warp10
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Warp 10: the key enabler of digital transformation in IoT … and IT business
From IoT and sensors to user applications, from maintenance to business services, Warp10 proposes a disruptive software
technology which makes you to consider data analytics and artificial intelligence in a
new and different perspective
Cityzen Datawww.cityzendata.com / www.warp10.io
Warp10
Warp 10: A powerful and disruptive software
platform to address sensors / IoT / Machine Data
#1
3Machine Data
Analytics
#1 Data from major companies databases
Big Data = Data MiningNo Disruption
#2Data from documents, social networks, videos …
Content data analytics, semantic
RelationalSQL
NoSQL
#3 Data for Sensors, Meters, Mobiles …
Where future business is
NoSQLTime Series
#4 Geospatial databases
Structured Géospatial3D Modeling
Theradicalchangeinsensor data:TimeSeries
examples
Warp10
Four families of data (including understanding, technologies, culture, governance)
Sensor/IoT Data and Machine Data go stronly to Time Series technologies
4Machine Data
Analytics
Asset #1:Geo TimeSeries®
+
A disruptive architecture for sensor data in which all data are not only defined by time, but by time+location
5Machine Data
Analytics
Asset #2:Analytics &Language
800 functions
A efficient framework for applications developers - To go faster and to focus on their core business first- To improve radically performances
From summary statistics to advanced signal processing and pattern detection
A stack based language
dedicated to time
series analytics
Things/Sensors
Datatransmission
Datacleansing
Datasynchronisation
Statistics,patterndetection,machine
learning, correlations,anomaliesdetection…
Datafiltering
BusinessApplication
Predictive
Warp10
6Machine Data
Analytics
Asset #3:HighLevel Security
Secured by Design
Metadata encrypted by default Total data encryption in optionDynamic allocation of cryptographic tokensData access by token holders tracked Data portfolio management
Total control guaranteed by WarpScript language > Key differentiator
7Machine Data
Analytics
Businessapplicationsandservices
Datacollection- Communications
GenericLayout
Warp10
WarpScript
Warp10 Data Storage or connectors to existing database
Library of functions, algorithms & tools +Language
Interactive modules
VisualizationReal timestreaming
8Machine Data
Analytics
Performances&scalability
Ingestion, data management and analytics- Real time operations- Total scalability
Ingestion from 100.000 measures per second to 1.5 million per core
Ingesting Renewable energies from small sources to bigger ones in real time
Market / trading
Industrial Consumption
Cities, Neighborhoods, Buildings
Storage
Home Consumption
15Machine Data
Analytics
UseCase#2:SmartCity/Mobility
Future mobility is typically the use case that requires to cross a large range of data.With CIRB in Brussels, Cityzen Data aims to :• To build up horizontal and scalable data infrastructure• To analyze data in order to improve traffic management and to propose services to citizens
Multimodal mobility management based on gathering and crossing data from:- Public transport timetables- Public transport real time data- Traffic monitoring- Traffic lights control- Trackers- Weather forecasts- Air quality- Electric vehicles stations monitoring- Bike sharing station monitoring- Car parks- Smartphones- Roads & streets works status …
16Machine Data
Analytics
UseCase#3:SmartBuilding/SmartFactories
Smart Building and Smart Factories are controlled by a large range of sensors in different areas: electricity, lighting, heating, water, cooling, security ….
Storing and crossing data allow to get value from a large amount of existing data
17Machine Data
Analytics
Source:Airbus
UseCase#4:Aeronautic maintenance
3 years data of a operational aircraft fleet analyzed by “off-the-shelf” warpscript functions
Speed
Alti
tude
18Machine Data
Analytics
A Self-Driving Car Will Create 1 Gigabyte of Data Per Second
Last year, an estimated 26 million connected cars collected more than 480 Terabytes of data. That number is expected to increase to 11.1 petabytes by 2020. Some plug-in hybrid vehicles are capable of generating up to 25 Gigabytes of data in just one hour.
Cityzen Data assists a worldwide company to prevent risks on the yields and market value of production
Warp 10 leveraged to cross and analyze :- Data coming from local sensors
- Data generated by equipment (manure spreaders, irrigation …)
- External data like weather forecast
22Machine Data
Analytics
UseCase#9:Health,wellnessandsport
The original use case for Cityzen Data : getting data from smart textile in order :- To understand body behavior - To detect historical and personal patterns- To anticipate specific troubles or diseases- …
MovementsHeart rate / ECGTemperaturePH
23Machine Data
Analytics
UseCase#10:Security/Cybersecurity
Security and cybersecurity need to cross data from a large range of sources.
Geo Time Series™ technologies is particularly relevant to detect weak signals among the ocean of various types of data.
The Warp10 technology is used to monitor Internet accesses.
To get real value in maintenance, sensors data need:
To be synchronized
To be historicized
To be cleaned
To be modeled
To be crossed with other data
To be interpreted in real time (and in batch mode)
Cityzen Data provides all these features through “off-the-shelf” tools & algorithms to different sectors: industry, power generators, cars, aeronautics, telecoms …
A strong trend: “Where Predictive Analytics Is Having the Biggest Impact”. Harvard Business Review
25Machine Data
Analytics
UseCase#12:Testbeds
Testbeds are facing to the increasing of the number of physical sensors and systems probes. They produces a huge amount of measures.
Warp10 provides “on the shelves” features and tools to testbeds experts to get benefit from:- Dealing with a large amount of data- Cleaning and synchronizing high frequency data- Detecting weak signals- Taking profit of data historian