Accelerating the
Industrial Internet of Things
Case Studies (70)
LumenData Delivers Real-time Predictive Analytics through IoT
LumenData Delivers Real-time Predictive Analytics through IoT
ThingWorx (PTC)
In 2013, LumenData found itself in need of adding new real-time predictive analytics capabilities to its suite of services. To meet this need, LumenData acquired a state-of-the-art streaming data, capture and real-time predictive analytics company. This solved the pure predictive analytics end, but left LumenData with a need to be able to build IoT-targeted services.From an IoT perspective, LumenData was still missing the means to create suitable applications and dashboards that would make it easy for its customers to effortlessly make sense of whatever predictive analysis they might require.
Avoid Unplanned Downtime with Predictive Analytics
Avoid Unplanned Downtime with Predictive Analytics
SAP
Objectives• Create an innovative IT environment that supports the move toward a solution-provider business model• Enhance existing business processes and leverage the power of Big Data and predictive maintenance to become more proactive, customer oriented, and competitive• Leverage the SAP HANA® platform to transform and simplify the entire SAP® solution landscape
Driving Predictive Maintenance into ThyssenKrupp Elevators
Driving Predictive Maintenance into ThyssenKrupp Elevators
CGI
TKE had a number of initiatives underway around the world to enable remote monitoring of its elevators. However, none of the solutions provided the data and insight required to move from a traditional reactive maintenance approach to one that is predictive and even preemptive, and all were challenged by information overload issues that limited their value.TKE wanted a solution that would enable it to anticipate and quickly resolve maintenance issues for the majority of the 1.2 million elevators it services across the globe.
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Hardware (7105)
e2v - ADC (TDC1035B7C)
e2v - ADC (TDC1035B7C)  -  TDC1035B7C
e2v
Single Channel Single ADC Flash 8-bit Parallel 24-Pin CDIP
Linear Technology - ADC (LTC2223CUK)
Linear Technology - ADC (LTC2223CUK)  -  LTC2223CUK
Linear Technology
LTC2223 - 12-Bit, 80Msps ADCs
STMicroelectronics - ADC (TSA1203IF)
STMicroelectronics - ADC (TSA1203IF)  -  TSA1203IF
STMicroelectronics
Dual Channel Dual ADC Pipelined 40Msps 12-bit Parallel 48-Pin TQFP Tray
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Software (63)
Apama
Apama
Software AG
Imagine how responsive your enterprise could be if you could glean real-time insights from all that big fast data—data streaming in from global markets, mobile devices, the Internet of Things (IoT), internal transactional systems and a myriad of other sources. You can be that event-driven enterprise by using Apama. Software AG's Apama Streaming Analytics—supporting predictive analytics—is the world’s #1 platform for streaming analytics and intelligent automated action on fast-moving big data. With Apama, you can analyze and act on high-volume business operations in real time.
LogixStudio
LogixStudio
NLP Logix
LogixStudio has been used help data scientist quickly develop, deploy and maintain predictive analytic solutions within any industry. Models are developed using Julia, a modern high-performance scientific computing language. Packaging and deployment interfaces allow the solution to easily be integrated into a number of different technologies.
Avantis Condition Manager
Avantis Condition Manager
Avantis (Schneider Electric)
A Condition Management solution that collects and analyzes real-time diagnostics from all plant production assets and drives appropriate action to improve overall asset performance and manage the appropriate operations, engineering and maintenance actions. Avantis’ Condition Based Maintenance drives predictive conditional alerts real-time, delivers simplicity from complexity and provides predictive maintenance management with the resultant improvement in asset integrity.
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Vendors (66)
DataRPM
DataRPM -
DataRPM is an award-winning predictive analytics company focused on delivering the next generation predictive maintenance solutions for the Industrial IoT. DataRPM platform automates data science leveraging the next frontier in machine learning known as meta-learning, which is machine learning on machine learning. The platform increases prediction quality and accuracy by over 300% in 1/30th the time and resources delivering 30% in cost savings or revenue growth for business problems around predicting asset failures, reducing maintenance costs, optimizing inventory and resources, predicting quality issues, forecasting warranty and insurance claims and managing risks better.DataRPM's advisory board consists of industry luminaries from companies such as Google, Hortonworks, Oracle, Cloudera, EMC, Facebook and Booz Allen Hamilton. Headquartered in Redwood City, California, the company is privately held. Customers of DataRPM include companies like GE, Cisco, Jaguar, Orange and similar Fortune 500 companies.
Simularity
Simularity -
Simularity specializes in software that does real time artificial intelligence for event prediction, predictive maintenance (Condition Based Maintenance), and anomaly detection. Simularity has proprietary methods to bring cutting edge machine learning right to the edges of the network, making connected devices smarter. We have created patent-pending Event Predictive Archetypes that are able to detect anomalies and predict adverse events in time series data, even on small devices with limited computing capacity, bandwidth, and connectivity. In addition, our core technology allows decision-makers to interactively create explainable, transparent, accurate predictive models without writing code.In short, we can increase your profits by creating valuable, actionable, decisions, and even new revenue streams, from your and your customers' "Internet of Things" data.
Rulex
Rulex -
Rulex is a new kind of AI platform, born from advanced government and academic machine learning research, and proven by years of deployment in diverse industries. Rulex’s unique logic-based approach to predictive analytics enables business and process experts to rapidly create and deploy AI applications with no need for math or programming skills.
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Events (2)
Predictive Analytics World for Business | Chicago
Predictive Analytics World for Business | Chicago
Predictive Analytics World
Jun 19, 2017   -   Jun 22, 2017
Chicago, IL
Predictive Analytics World for Business, June 20-23, 2016 in Chicago, is packed with the top predictive analytics experts, practitioners, authors and business thought leaders. Predictive Analytics World focuses on concrete examples of deployed predictive analytics. Hear from the horse's mouth precisely how Fortune 500 analytics competitors and other top practitioners deploy predictive modeling, and what kind of business impact it delivers. PAW's San Francisco 2016 program will feature over 30 sessions with case studies across 3 tracks – 1) All Audiences, 2) Expert/Practitioner and 3) Financial Services PAW San Francisco's agenda will cover hot topics and advanced methods such as Automotive applications, B2B sales, churn modeling, cross-enterprise deployment, crowdsourcing predictive analytics, deep learning, design of experiment, employee theft detection, energy, hadoop for predictive analytics, healthcare analytics, insurance, intrusion detection, modeling methods (algorithms), network security, omni-channel, open source tools, optimizing public safety outreach, predictive maintenance, predicting virality on social media, predictive audit planning, predictive investing (VC), predictive SEO ("reverse-engineering Google"), predicting virality on social media, revenue modeling, self-serve prediction, social media applications and uplift modeling.
Predictive Analytics World for Business | San Francisco
Predictive Analytics World for Business | San Francisco
Predictive Analytics World
May 14, 2017   -   May 18, 2017
San Francisco
Predictive Analytics World for Business, April 3-7, 2016 in San Francisco, is packed with the top predictive analytics experts, practitioners, authors and business thought leaders.Predictive Analytics World focuses on concrete examples of deployed predictive analytics. Hear from the horse's mouth precisely how Fortune 500 analytics competitors and other top practitioners deploy predictive modeling, and what kind of business impact it delivers.PAW's San Francisco 2016 program will feature over 30 sessions with case studies across 3 tracks – 1) All Audiences, 2) Expert/Practitioner and 3) Financial ServicesPAW San Francisco's agenda will cover hot topics and advanced methods such as Automotive applications, B2B sales, churn modeling, cross-enterprise deployment, crowdsourcing predictive analytics, deep learning, design of experiment, employee theft detection, energy, hadoop for predictive analytics, healthcare analytics, insurance, intrusion detection, modeling methods (algorithms), network security, omni-channel, open source tools, optimizing public safety outreach, predictive maintenance, predicting virality on social media, predictive audit planning, predictive investing (VC), predictive SEO ("reverse-engineering Google"), predicting virality on social media, revenue modeling, self-serve prediction, social media applications and uplift modeling.
Organizations (1)
Zetta Venture Partners
Zetta Venture Partners
United States | Venture Capital
We invest in software that gets better as you add data to it. We invest in companies that build a competitive advantage through proprietary data generation and/or algorithms that improve over time. This includes any machine learning-based software, predictive analytics, data-as-a-service and data infrastructure.
Use Cases (17)
Condition-based Maintenance (CBM)
Condition-based Maintenance (CBM)
Condition-based Maintenance (CBM) or predictive maintenance is the science of maintaining physical assets over time, in order to maximize their return on those assets. It is enabled by sensors and data analytics that provide visibility into the current and future status of assets.
Equipment Efficiency Optimization
Equipment Efficiency Optimization
Optimizing the efficiency of equipment has a significant impact on profits and shareholder value. It affects productivity an quality.
Asset Efficiency
Asset Efficiency
Asset Efficiency refers to the process of analyzing the health of an asset. The health of an asset in itself relates to the asset's utility, its need to be replaced, and its need for maintenance. The Use Case is broken down into three key components:-Monitoring: Tracking the actual health and viability of the asset-Diagnostic Analysis: Comparing new, real-time data to relevant data from the past in order to detect any anomalies-Prognostics: Given past data, algorithms are developed to determine the remaining useful life of an asset
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Terms (4)
Contextual Experiences
Contextual Experiences
Big data analytics solutions, combined with the proliferation of edge devices collecting highly contextual data, are allowing businesses to craft experiences that are unique for each user.
Data Science
Data Science
The extraction of knowledge from large volumes of data that are structured or unstructured.
Industrie 4.0
Industrie 4.0
Industry 4.0, Industrie 4.0 or the fourth industrial revolution, is the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things and cloud computing. The term "Industrie 4.0" originates from a project in the high-tech strategy of the German government, which promotes the computerization of manufacturing.Invoking a fourth Industrial Revolution, Industrie 4.0 creates intelligent manufacturing networks where decentralized smart factories can communicate and react to each other autonomously.Industry 4.0 creates what has been called a "smart factory". Within the modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real time, and via the Internet of Services, both internal and cross-organizational services are offered and used by participants of the value chain.
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Guides (19)
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