Using MSP430 MCUs in wireless, M2M, and IoT apps

As the potential impact of the Internet of Things on a wide variety of embedded markets has continued to grow, a great deal of effort has been spent by ARM Ltd. and many of the licensees of its architecture to make sure that next wave of low power wireless sensor, machine to machine applications would be built with the Cortex-M family of 32-bit MCUs.

So far, as noted by the collection of recent design articles and technical papers in this week's Tech Focus newsletter on the use of the Texas Instruments MSP430 16-bit MCUs, this has not yet happened. While ARM-based 32-bit IoT applications are beginning to appear, I come across many more still being done on 8/16 bit MCUs such as the MSP430. I have included some of those designs in this week’s Tech Focus Newsletter. Of these, my Editor's Top Picks are:

Ambient RF Energy Harvesting for Wireless Sensor Networks
An MSP430 based wireless sensor network energy harvesting technique that makes use of the RF energy contained in TV broadcast signals that is normally dissipate as waste heat energy.

A Self-Powered WSN Based on Energy Harvesting of mechanical vibration
An MSP430 microcontroller-based design for wireless sensor network energy harvesting that involves sensing then collecting and converting engine vibration into useable energy.

Wearable Monitoring Unit for Swimming Performance Analysis
An MSP430 wearable inertial monitoring unit for use in a pervasive monitoring system that collects physiological and biochemical signals from swimmers during training, both in and out of the water.

The basics of application development on an MSP430 16-bit MCU
A series on application development on the Texas Instruments MSP430 16-bit MCU using IAR’s free Embedded Workbench Kickstart Integrated Development Environment.

What explains this continued use of 8-bit and 16-bit MCUs such as the MSP430 in a broad range of leading edge IoT designs, given that TI – along with many of the providers of other 8/16-bit MCUs such as Freescale, ST Micro, and Renesas, to name a few – also license one or more of the Cortex-M family?

Most of these companies have shifted from architecture-specific design tool strategies to a common cross-platform strategy that makes it easier not only for developers to move their applications across a number of different ARM variants, but to allow them to more easily migrate from 8/16-bit implementations to 32-bit designs. For example, although it still provides support for such dedicated tools as the IAR tool suites for the MSP430, Texas Instruments is heavily pushing a cross-platform strategy based on its own Launchpad development platform.

But based on the applications I have read, that migration has not yet happened. Why? Is it because the Cortex-M based MCUs have not been around long enough to make any appreciable inroads into the customer base for existing 8-/16-bit MCUs?

Or is it that current 8/16-bit implementations more than adequately serve their developers needs so why change? Are 8/16-bit MCUs still lower in power — important in IoT applications — than most 32-bit ARM Cortex designs? Even with the aggressive efforts of ARM and its licensees to lower the cost of their 32-bit MCUs, are 8/16-bit devices still the most cost effective decision to make?

What factors are you taking into account in your decisions about 8-, 16- or 32-bit in your embedded wireless sensor, M2M, and IoT designs? Power requirements? Tool availability? Ease of migration? Space considerations? Real time and deterministic performance?

Embedded.com Site Editor Bernard Cole is also editor of the twice-a-week Embedded.com newsletters as well as a partner in the TechRite Associates editorial services consultancy. If you want to see a calendar of topics for the weekly Tech Focus newsletter or have a topic you would like to see covered, he welcomes your feedback. Send an email to , or call 928-525-9087.

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1 thought on “Using MSP430 MCUs in wireless, M2M, and IoT apps

  1. “I am using MSP430 to know the status of temperature in industrial areas with low power Microcontroller .nI tried to write the code using energia platform flame sensor using RTOS Environment and push the data to cloud (to observe the output in the display

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