This article was authored by Allan Tan, and was originally posted on telecomasia.net.
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.
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.
“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,” ABI Research principal analyst Kevin McDermott said.
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 forecast to grow at over 540% CAGR over the next five 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 five years,” concludes McDermott.
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