IoT Data Traffic “Per Node”: The New Critical Metric for IoT System Designers

IoT Data Traffic "Per Node": The New Critical Metric for IoT System Designers

IoT Data Traffic "Per Node": The New Critical Metric for IoT System Designers

All Messages are Important, Just Some Messages are More Important Than Others.

The best IoT message bandwidth planning may not survive the first contact with real-world data as IoT System Integrators (SIs) and network planners face the challenge of developing a project concept while at the same time anticipating the data traffic use-case requirements.

The latest report from ABI Research explores the growth factors driving the IoT data traffic per node, including bandwidth requirements in 23 key market segments.

Analysis of the IoT data provides valuable insights and is the foundation of new business opportunities and services, which in turn is driving the future requirements of IoT Data Traffic across multiple markets and applications.

Kevin McDermott, Principle Analyst ABI Research, said:

“IoT system design needs to consider multiple factors around the critical communication links including messaging size, frequency, and data types. However, by anticipating the detailed use case scenarios including data bandwidth growth, the uncertainty between design expectations and real-world experiences can be minimized.”

While requirements and use case factors are application dependent, all share the common goal of interpreting raw sensor data and deriving value-added information. The fastest growing segment for data traffic per node is OEM telematics, which is forecasted to grow at over 540% CAGR over the next 5 years. This market will drive the highest IoT solution revenues per connected vehicle – partly driven by the additional security and integrity measures needed to protect the vast amounts of data exchanged.

While many standards and technologies are developing protocols for IoT networks, the essential message structure and information flow depend on the use-case around the data traffic of the target application. With IoT adoption across wide-ranging applications and market segments, the use case scenarios are driving IoT data traffic growth.

“Urgent messages, alerts and alarm indicators may require both priority attention and assured bandwidth allocation, but planning also needs to consider peak demand and exception utilization. SIs, IoT system designers, and network planners can utilize the data traffic per node approach to anticipate the use case and application factors that are expected to drive growth over the next 5 years,” concludes McDermott.

These findings are from ABI Research’s IoT Data Traffic: Application and Market Analysis report.

The post IoT Data Traffic “Per Node”: The New Critical Metric for IoT System Designers appeared first on IoT Business News.

IoT Business News

The Imperializer makes quick work of metric conversions

When you work in a machine shop, you often need to convert numbers from metric to imperial. As long as you have to do this on a regular basis, why not make a tool to do so easily?

Instead of pulling out a phone or taping a calculator to their CNC machinery, NYC CNC came up with an Arduino Nano-based device that does this conversion in style. “The Imperializer” features a beautifully milled enclosure that magnetically sticks onto a machine, a backlit LCD, and a toggle switch to flip between metric and imperial units.

The Imperializer is a desktop or machine mountable device that does one thing: converts inches to millimeters (and millimeters to inches)!  It uses an Arduino Nano and is powered by a Lithium battery that can be recharged with a Micro-B USB cable!

If you’d like to have your own for your shop, the bill of materials and Arduino code can be found on the project page. The housing, and even a fully-assembled version, can be purchased here.

Arduino Blog

What is the right metric for carsharing?

Deloitte’s Mobility as a service report tracks how to create successful shared transportation infrastructure.

The idea of sharing a car has become a reality thanks to connectivity, cheap sensors, and platforms to foster trust.

A highly influential and tested stat notes that private cars sit idle 95% of the time. It makes sense to figure out a way to efficiently shuttle cars between users and there’s a wide consensus that most people will someday participate in car sharing as opposed to owning their own vehicle.

Sharing cars changes a lot of things about the car industry, such as the car buying model. It also affects infrastructure including where people build garages.

But how will the sharing programs themselves measure success? If they are private companies, then profits will matter, but what are the metrics that matter when it comes to generating profits? Is it the cost-per-ride? Wait time? The member-to-vehicle ratio offered above?  Right now, we’re not sure. Even Uber apparently doesn’t turn a profit, since it has those pesky humans in the mix.

What if governments decide that car sharing is a public good or service that should be taken over as part of a city’s infrastructure? On-demand cars become a public resource much like public transit is today. In that situation making money to cover the system’s costs matter, but a better measurement of success might be wait time or the ratio of cars to riders.

Deloitte has written a report covering the future of mobility as a service that questions the right models for this looming future and how cities are thinking about their role in this shift. So read past the egregious use of the phrase “user-centered mobility paradigm” and dig into the meat of this report.

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