Accelerating the Industrial Internet of Things
Log In
Number of Case Studies9
Security for Edge Computing and Mesh Network
Security for Edge Computing and Mesh Network
An enterprise security client wanted to develop a security product to address decentralized IoT security. Numerous reports and articles have been written on the security vulnerability of Industrial Internet of Things (IoT), smart cities, smart buildings, smart home automation, and healthcare. The standard best practices and solutions for cloud security and application security do not adequately address the specific nuances of the Internet of Things, especially for edge-to-edge computing and networking.
A repeatable model for industrial data intelligence
A repeatable model for industrial data intelligence
Exara’s oil and gas client required a reliable way to gather, store, and process data from sophisticated machine assets in remote oil fieldsites. These harsh, real world environments present significant challenges for high performance computing devices.
IIC Approves Factory Automation Platform as a Service (FA PaaS) Testbed Proposed
IIC Approves Factory Automation Platform as a Service (FA PaaS) Testbed Proposed
Edge computing via local Edge controllers allows uniterrupted, high speed collection, filtering and processing of real time data line side. Initial fast reactions can be initiated with the full data sets also being sent to associated cloud systems for further analysis. This processing at two layers respects the data integrity but allows the collected data to be processed as live and historical instances. The challenge is how to collect the data from diverse sources without interrupting the existing processes but also being able to span "brown field" systems where there may not even be any existing communication or data capture functions. 
Number of Suppliers37
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.
Foxconn
Foxconn
Foxconn Technology Group is a Taiwanese multi-national design, manufacturing and logistics services provider for Computer, Communications and Consumer Electronics (3C) industries. It is the world's largest electronics contractor manufacturer and the third-largest information technology company by revenue, with 1.3 million employees worldwide.Year founded: 1974
Micron Technology
Micron Technology
Micron offers the industry’s broadest portfolio of silicon-to-semiconductor solutions―starting with foundational DRAM, NAND, and NOR Flash memory, and extending to SSDs, modules, MCPs, HMCs, and other semiconductor systems. This technology powers leading-edge computing, consumer, enterprise server and storage, networking, embedded, automotive, industrial, and mobile products.
Number of Organizations2
EdgeX Foundry
EdgeX Foundry
EdgeX Foundry goals include:-Build and promote EdgeX as the common open platform unifying Internet of Things (IoT) edge computing-Enable and encourage the rapidly growing community of IoT solutions providers to create an ecosystem of interoperable plug- and-play components around the EdgeX platform architecture-Certify EdgeX components to ensure interoperability and compatibility-Provide tools to quickly create EdgeX-based IoT edge solutions that can easily adapt to changing business needs-Collaborate with relevant open source projects, standards groups, and industry alliances to ensure consistency and interoperability across the IoT
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
Edge Computing | Edge Intelligence
Edge Computing | Edge Intelligence
Edge (fog) computing shifts computing applications, data, and services away from centralized servers to the extremes of a network. This enables analytics and knowledge generation to occur at the source of the data. Industrial IoT companies face challenges turning machine data into business intelligence. Existing cloud-based technologies do not solve problems of data analytics, software deployment, or updates and security for remote devices. Edge or fog computing solves the problem of accessing large amounts of machine-generated data by processing data at the edge of the network and converting it into actionable, useful business information. In an Intelligent Industrial Fog, software can be deployed at various points in the network to not only automate monitoring and control, but also to apply embedded intelligent agents that can adjust device behaviors in relation to ongoing performance variables, reduce running costs by reducing power consumption during off-cycles, or even detect imminent failures and notify technicians to perform preventative maintenance.Edge computing also allows remote software deployment and secure M2M communication. Edge computing leverages resources that are not continuously connected to a network, such as laptops, smartphones, tablets, and sensors. It covers a wide range of technologies, from wireless sensor networks and mobile data acquisition to cooperative distributed peer-to-peer ad hoc networking and processing. Import IoT applications include remote cloud services, distributed data storage and retrieval, and self-healing networks. 
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. 
Indoor Positioning System (IPS)
Indoor Positioning System (IPS)
Indoor Positioning Systems (IPS) are used to locate persons or objects inside buildings, as opposed to GPS which works outdoors. IPSs impact asset monitoring and automation at the enterprise level. The technology is expected to bring in integration capabilities of analytical software tools with the existing maps and navigation software. 
Number of Terms2
Edge Computing
Edge Computing
Edge Computing is pushing the frontier of computing applications, data, and services away from centralized nodes to the logical extremes of a network.
Fog Computing
Fog Computing
Fog computing is a term created by Cisco that refers to extending cloud computing to the edge of an enterprise's network.
9 Case Studies
37 Suppliers
2 Organizations
3 Use Cases
2 Terms
4 Guides
test test