Accelerating the Industrial Internet of Things
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Number of Case Studies38
Leveraging Machine Learning To Enhance a Molding Process Involving IoT Solutions
Leveraging Machine Learning To Enhance a Molding Process Involving IoT Solutions
In the third wave of industrial evolution, we had automation that produced large amounts of data. This data had high potential for analytic applications, but it was not easy to analyze because it was siloed in the machines where it was generated. With this project, we demonstrate that it’s not complex to send the data to the cloud using secure and reliable services that allow us to analyze the data in near-real time and build maching learning models to extract knowledge from it.
Siemens | Using Machine Learning to Get Machines to Mimic Intuition
Siemens | Using Machine Learning to Get Machines to Mimic Intuition
The ability to learn is a precondition for autonomy. With this in mind, Siemens researchers are developing knowledge networks based on deep learning-related simulated neurons and connections. Such networks can be used to generalize information by identifying associations between extraordinarily complex realms, such as the publicly accessible Internet and a company’s internal information systems. Far-reaching and generic, this technology appears to hold the potential of mimicking what humans call intuition.
Reducing the Rate of Readmissions
Reducing the Rate of Readmissions
The client had limited or inefficient integration of its data sources, which made it difficult to see patients through a longitudinal lens. The client was, however, uniquely positioned to leverage the expansive patient data contained within its network of care, and set out to do so in 2012. Specifically, they wanted to improve the outcomes of patients with Ischemic Heart Disease (IHD) through improved care management with goals of reducing readmission rates, better managing patient cholesterol levels, and better managing patient blood pressure.Specifically, the regional healthcare provider was interested in implementing a machine learning platform, that quickly automates complex analytical processes and integrates powerful information into existing applications and portals.
Number of Suppliers83
Qylur Intelligent Systems
Qylur Intelligent Systems
Qylur is a Silicon Valley-based technology company disrupting the operational intelligence market through significantly smarter adaptive systems that deliver great user experiences at large public venues. They develop software and system solutions that are vertically integrated across the entire IIoT/M2M stack and employ social networks of machines, machine-learning and human interaction design (M2H).
Presenso
Presenso
Presenso provides an AI Driven Industrial Intelligence solution.
Nervana Systems
Nervana Systems
At Nervana,they are developing the next generation of machines to tackle challenges in data analysis and computation. Using deep learning as a computational paradigm, they are optimizing from hardware to software to develop intelligent solutions for real-world problems. Founded by experts in machine learning, neuroscience, and computer engineering, Nervana is bringing unprecedented scale and simplicity to these brain-inspired algorithms.
Number of Organizations4
Bishop Ranch Innovation Intelligence Accelerator
Bishop Ranch Innovation Intelligence Accelerator
Bishop Ranch Innovation Intelligence Accelerator (BRIIA) was founded in 2017 as an integrated data innovation accelerator and collaborative community for machine learning and artificial intelligence. BRIIA’s 12-week Accelerator curriculum gives early-stage entrepreneurs the resources to start and grow companies that are fueled by machine learning, artificial intelligence, natural language processing, and related technologies. BRIIA is a community of specialists with diversity and passion in emerging technologies, analytics, marketing, sales, UX, and business development. Here, cutting edge data technologies meet entrepreneurship to foster growth in new ideas and markets.
Zetta Venture Partners
Zetta Venture Partners
Zetta Venture Partners is the first focused fund committed to delivering exceptional returns from the high-growth analytics market. The firm, founded by industry veteran Mark Gorenberg, launched in 2013. With offices in San Francisco and Utah, and a worldwide network of partners, entrepreneurs and investors, Zetta Venture Partners is at the forefront of the next huge and long-lasting investment opportunity. Focused funds deliver exceptional returns. In fact, over the past 10 years, focused funds have outperformed all funds by 72 basis points, according to the National Venture Capital Association. As an analytics-only fund, Zetta delivers the expertise, network and portfolio to create ongoing, exceptional deal flow.
Microsoft Venture
Microsoft Venture
Microsoft Ventures brings you access to unrivaled technology, go-to market resources and relationships around the world. Our technology ranges from enterprise platforms such as Azure and Office 365 through to cutting-edge innovations in virtual reality and AI. Microsoft Ventures is your strategic partner, actively investing in startups from SeriesA to Series D. We focus on technologies enabling a mobile-first, cloud-first future, spanning big data & analytics, business SaaS, cloud infrastructure, machine learning, productivity and security, among others.
Number of Use Cases3
Fog Computing
Fog Computing
Fog computing refers to a decentralized computing structure, where resources, including the data and applications, get placed in logical locations between the data source and the cloud; it also is known by the terms ‘fogging’ and ‘fog networking.’The goal of this is to bring basic analytic services to the network edge, improving performance by positioning computing resources closer to where they are needed, thereby reducing the distance that data needs to be transported on the network, improving overall network efficiency and performance. Fog computing can also be deployed for security reasons, as it has the ability to segment bandwidth traffic and introduce additional firewalls to a network for higher security. 
Security Claims Evaluation
Security Claims Evaluation
Security Claims Evaluation is an open and easily configurable cybersecurity platform for the evaluation of endpoint, gateway, and other networked components’ security capabilities.In an industrial environment setting, monitoring of sensors provides a window into the system and operational efficiencies. Specifically, monitoring key parameters such as temperature, vibration, currents, and voltage provide the operator with insights into whether operations are normal, within normal failure mode, or whether there is an indication of a cybersecurity/security breach.Security Claims Evaluation provides a platform for users to evaluate whether data from the sensors under test is indicative of normal operation or abnormal operation in a non-invasive and non-intrusive manner. Furthermore, using machine learning in combination with real-time analytics capabilities, the sensor operation can be monitored and analyzed 24/7. Logging of abnormal events can be performed for further assessment and future remediation actions. Through running a pre-defined security test suite that encompasses pen testing, known vulnerabilities, and other testing methodologies, testbed users’ security claims can be evaluated at a single or multiple connection points – encompassing an endpoint to a gateway to cloud assessment. A report based on the test results can be provided to users describing potential security weaknesses and proposed recommendations and remediation methods. 
Vehicle Telematics
Vehicle Telematics
Fleet telematics enable the monitoring of location, movement, status, and behavior of a vehicle within a fleet. This is achieved through a combination of a GPS receiver and an electronic GSM device that is installed in each vehicle, which then communicates with the user and cloud-based software. Additional sensors and actuators may be added to the system to enable additional functionality, such as vehicle remote control and driver status tracking.Telematics systems provide analytics to determine the optimal route based on location and traffic information, the vehicle's condition, and operational cost prediction.  
Number of Terms11
Industrial Internet
Industrial Internet
A short-hand for the industrial applications of IoT, also known as the Industrial Internet of Things, or IIoT.
Artificial Intelligence (AI)
Artificial Intelligence (AI)
 A technology that gives computers the ability to learn based on data, previous experiences, and their environment in order to make decisions in order maximize results.
Machine Data
Machine Data
Also known as machine-generated data, this is digital information created by the activity of computers, mobile phones, embedded systems, and other networked devices.
38 Case Studies
83 Suppliers
4 Events
4 Organizations
3 Use Cases
11 Terms
8 Guides
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