Warp10 Warp 10: the key enabler of digital transformation of IoT business From sensors to industrial processes, from monitoring to cybersecurity, Warp10 proposes a disruptive software technology which makes you to consider data and artificial intelligence in a new and different perspective for IoT business Cityzen Data www.cityzendata.com / www.warp10.io
Warp 10: A powerful and disruptive software #1 platform to address sensors / IoT / Machine Data
Iot Data = Machine Data = Time Series Four generic families of Data examples Big Data = Data Data from major Relational #1 Mining companies databases SQL No Disruption Data from Social Semantic, Content #2 NoSQL Networks, mails … analytics Data for Sensors, NoSQL Where IoT Big #3 Meters, Mobiles … Time Series Data is Warp10 Structured Geospatial #4 3D Modeling Géospatial databases When traditional IT application is based on relational databases, IoT requires other tech and more flexible approaches 3 Machine Data Analytics
Warp 10/ Asset #1: Geo Time Series™ + A disruptive architecture for sensor data 4 Machine Data Analytics
Warp 10/ Asset #2: Analytics & Language Business Application A stack based language Predictive dedicated to time Statistics, pattern series analytics detection, machine learning, correlations, 800 functions anomalies detection … Warp10 Data filtering Data synchronisation From summary statistics to advanced signal Data cleansing processing and pattern detection Data transmission Things / Sensors A efficient framework for IoT applications to develop faster and to focus on their core business first 5 Machine Data Analytics
Warp 10/ Asset #3: High Level Security Secured by Design Metadata encrypted by default Total data encryption in option Dynamic allocation of cryptographic tokens Data access by token holders tracked Data portfolio management Total control guaranteed by WarpScript language > Key differentiator 6 Machine Data Analytics
From Big Data to Artificial Intelligence …or How to take profit of complex algorithms in business applications Machine learning tasks: Tree-based Algorithms - Sensors & Multisensors machine - Random forests behavior understanding - Gradient boosted trees - Classification, regression, clustering - Anomaly, failure, fault detection - Data visualization Statistical Learning - Support vector machine - Bayesian Networks - Stochastic control/Markov Dimensionality reduction decision processes - t-distributed stochastic neighbor embedding (t-SNE) - Principal component analysis Deep learning - Independent component analysis - Artificial neural networks - Laplacian eigenmaps (perceptron, convolutional, - Isomap recurrent, long short term memory, ...) - Generative adversarial Warpscript proposes generic extensions to learn, to networks reproduce, to detect, to predict, or to simulate patterns, behaviors, outliers, anomalies, failures … 7 Machine Data Analytics
3 offers Standalone Distributed Embedded Version Version Version HA Datalog 8 Machine Data Analytics
Open Source Distribution http://www.warp10.io 9 Machine Data Analytics
A key value booster for getting value from IoT & events data To an horizontal business Cityzen Data helps clients to value added for apps get value from their data Cityzen Data is a tech companies without any interference with client Energy Transport Health own business. App App App Businesses functions, algorithms and services developed by clients remain - - - - - - DATA -- - - - - their property. Warp10 by Cityzen Data Cloud or On Premise IT A horizontal, neutral and Telecoms industrial approach on the Sensors Meters IoT sensors and IoT market Cityzen Data ingests and Cityzen Data works with major manages more companies than 250 Bn measures / day GE, Airbus, Orange, Amazon, OVH , Cap Gemini … in SaaS mode When many companies claim they have IoTData platform, we can (Sept 2016) prove that we have the best and the most promising one. 100,000 to 1.5 million 10 Machine Data measures / sec / Core Analytics
Warp10 designed by Mathias Herberts, Co-founder, CTO Warp10 Ranked #5 11 Machine Data Analytics
Warp10 #2 Use Cases
Use Case #1: Energy on the whole value chain Cities, Neighborhoods, Market / trading Buildings Home Transmission Consumption Microphasers Storage Ingesting Renewable energies from small sources to bigger ones in real time Industrial Consumption 13 Machine Data Analytics
Use Case #2: Smart City / Mobility 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 … 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 14 Machine Data Analytics
Use Case #3: Smart Building/Smart Factories 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 15 Machine Data Analytics
Use Case #4: Aeronautic maintenance Source: Airbus 16 Machine Data Analytics
Use Case #5: Connected Cars 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. http://www.ibmbigdatahub.com/blog/how- vehicle-telematics-changing-auto-industry A Self-DrivingCar Will Create 1 Gigabyte of Data Per Second https://datafloq.com/read/self- http://www.economist.com/blogs/economist- driving-cars-create-2-petabytes- explains/2013/04/economist-explains-how- data-annually/172 self-driving-car-works-driverless 17 Machine Data Analytics
Use Case #6: Groupama Sailing Team America’s Cup Bermuda 2017 Data analytics: - To improve performances - To predict problems 18 Machine Data Analytics
Use Case #7: Systems, IT, Telecom Monitoring Monitoring of systems is done by sensors measuring a large range of parameters: mechanic, power, data transmission, data processing, latency … Warp 10 cross and analyzes data coming from any type of sensors, subsystems, scada … to detect fault, anomalies, discords or to predict future troubles 19 Machine Data Analytics
Use Case #8: Major group investing worldwide in agriculture companies (2017) Data Analytics 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 20 Machine Data Analytics
Use Case #9: Health, wellness and sport Movements Heart rate / ECG Temperature PH 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 - … 21 Machine Data Analytics
Use Case #10: Security / Cybersecurity Internet access Internet surfing Smartphones Social media Personal connections Phone calls Mails Payments Hard disks contents Borders controls Airport controls Interview minutes Videosecurity 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. 22 Machine Data Analytics
Use Case #11: Conditional & Predictive Maintenance A strong trend: “Where Predictive Analytics Is Having the Biggest Impact”. Harvard Business Review To get real value in To be historicized maintenance, sensors data need: To be cleaned To be synchronized 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 “on the shelves” tools & algorithms to different sectors: industry, power generators, cars, aeronautics, telecoms … 23 Machine Data Analytics
Use Case #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 24 Machine Data Analytics
Beyond the tech, a #3 new paradigm in IT architectures
Recommend
More recommend
