Extending the Internet to a virtually limitless variety of embedded devices or “Internet of Things” has far reaching implications, particularly in applications that leverage machine-to-machine (M2M) computing and the massive amounts of “Big Data” that must be collected, processed, and secured. Here are links to the top community posts that address these opportunities and challenges:
White paper: Optimize Enterprise IoT Deployments with eUICC
Discover how eUICC and eSIM technologies give early enterprise adopters the edge on global IoT deployments and mobility services.
Article: Seeing Clearly in the Fog
The growth of the Internet of Things is burdening wireless networks, running up corporate cloud costs, and exposing gaps in real-time analytics. See how Intel addresses these issues with a system architecture specification for the IoT.
Article: Making the Fog Smarter
Many IoT solutions cannot afford the latency in cloud analytics, nor all the network, storage, and processing costs of cloud computing. Discover an edge analytics architecture that uses intelligent edge devices and gateways to deliver real-time analysis and action, and then aggregate results.
Check out a few examples of the ways developers can analyze data from millions of sensors across a smart city.
Article: From IoT Vision to Reality
In evaluating new technologies, businesses look for return on investment (ROI). Today they are finding it in the Internet of Things (IoT). Discover how the continuing evolution of IoT solutions is delivering tangible results in productivity, efficiency, and revenue generation.
One of the big challenges with IoT design is integrating all of the sensors. Sorting out all the firmware for the various sensors and networks can be a time-consuming and tedious process. Explore a modular, plug-and-play approach that can significantly speed up the development cycle.
Read about an end-to-end solution that makes it much easier to connect embedded devices to commercial cloud service like those from Microsoft, IBM, and Amazon. With these IoT starter kits, companies can focus their design efforts on analytics and decision support rather than contentious configuration details.
Manufacturers starting down the road to Industry 4.0 need a plan to achieve operational and information technology (OT-IT) convergence that will help fix issues with data silos and system interoperability. Learn about a cross-platform capability that exposes previously unconnected data and systems to higher layers of the organization.
Fast data differs from other data in that it is generated in very high volume and its value is time-sensitive, such as financial ticker and sensor data from real-time processes. Explore innovative solutions that combine IoT data from multiple sources in real time to support advanced analytics.
Using the IoT to enable energy and industrial-process optimization often requires connecting legacy systems isolated by non-IP-friendly protocols. Discover a solution that combines the resilience of mesh networking with the low latency of a star topology to connect sensors to IoT gateways.
A primary task for an IoT platform is the gathering and sending data from sensors to cloud components for analysis. Learn how an IoT platform needs to be able to support third-party vendor (TPV) middleware solutions for enabling specific end-to-end data flows.
As competition continues to heat up in the Internet of Things (IoT) space, developers face increasing pressure to compete on price as well as performance and feature set. Check out some new boards and systems based on a new 64-bit system-on-chip (SoC) from Intel.
Have you read any related content that you would recommend to the community? What other aspects of Internet of Things and Big Data would you like to see covered?
J. Felix McNulty
Intel® Embedded Community