microcontroller

Over the last three years the number of battery-operated electronic-component solutions for the Internet of Things (IoT) and Industrial IoT (IIoT) applications has been increasing steadily. This trend will continue for years to come, particularly with the growing popularity of mobile devices of all flavors. Addressing power consumption for battery-powered always-on IoT/IIoT devices – which rely on dozens of electronic components, including sensors — is critical to their commercial success.The demand for ultra-low-power sensors has accelerated the race to squeeze every last mW from components. Compared to previous-generations of sensors, semiconductor suppliers have managed to drastically reduce power by as much as 50%-60% over older solutions. Leveraging new state-of-the-art analog design techniques, we have effectively optimized capacitive readings of MEMS structures. How effective are they? We estimate that with the right mix of our company’s power-saving technologies, it is possible our customers could save 3MW/year globally[1].What’s next?While the semiconductor industry continues to investigate novel technologies, approaches and analog IP for greater energy efficiency, we believe that bigger gains in reducing power consumption will come from thinking at the system level. The sensor node is a good place to start.A typical IoT node is composed of a set of sensors, a microcontroller, a radio frequency (RF) link, and a power-supply system, often based on Li-Po batteries.Of these, the microcontroller and RF link consume the most energy and, in the RF link, power consumption is a function of the distance between end point and receiver and of the amount of data transmitted. Thus, at longer distances reducing the amount of data transmitted can save power. We can achieve this by including some pre-elaboration capabilities on-board and by extracting more meaningful information from the raw sensor data.We address this by moving some computation and data analysis inside the sensors, where smart hardware “digital blocks” perform faster and more efficiently than software-based routines running in the microcontroller. We can achieve this by using dedicated hardware resources to reduce overall system power consumption. The beauty of this solution is that it allows the microcontroller to operate in low-power states by only transmitting significant information in batches. The SensorTile development kit can speed up prototyping of ultra-low-power IoT devices by integrating an ultra-low-power MCU and BlueNRG Bluetooth radio with sensors. Some examples of these advanced digital blocks are the Advanced Embedded Pedometer, the Finite State Machine and Decision Tree, and Compressed FIFO in an IMU.The Advanced Embedded Pedometer is a hard-wired step counter that works independently inside the sensor, without CPU intervention: By comparing sensor outputs to pre-defined and -loaded patterns, it autonomously decides whether the user is walking or running to start and stop counting the user’s steps. The sensor then makes this information available to the microprocessor for further elaboration or for simple notification to the user.The Finite State Machine and Decision Tree are new functions dedicated to pattern recognition (machine learning) and decision-making: They can perform complex classifications and state detection, and can send dedicated warning and signaling to the microprocessor. A good real-world example is industrial predictive maintenance, where the sensor can categorize and identify different malfunctioning states in the equipment before waking the microprocessor to react.Our products, on average, save about 1 mA (1e-3) over competitive devices or over our previous-generation parts. So 2.0 x 1e-3 x 1.5e9 = 3MW. Programmable Sensor and Decision Tree Finite State Machine Integrating programmable sensors and decision trees as well as finite state machines in the sensor allows the sensor to do more of the work while the MCU sleeps. Source: STMicroelectronics Another example is compressed FIFO (first-in, first-out) buffer, which can store sensor data in the sensor, not in raw format, by using efficient compression algorithms. In addition to saving memory (and therefore silicon area) inside the sensor chip, it also saves power by reducing the number of bytes transferred to the processor and by shortening the communication data flow, which reduces processor-active time.These examples – the Advanced Embedded Pedometer, the Finite State Machine and Decision Tree, and compressed FIFO buffer – are just some showing that we can develop low-power IoT/IIoT devices through intelligent management of sensors, microcontrollers and other components in any given system. Your starting point is an IoT/IIoT node that lets you selectively allocate some power-hungry tasks — such as computation and data analysis — to sensors instead of the microcontroller. Leveraging data blocks that reside in the sensors alleviates the microcontroller’s typical power drain, allowing the microcontroller to operate with maximum efficiency.[1] ST sells about 1.5 billion pieces/year (1.5e9), which typically run from a 2V supply. Luca Fontanella joined ST Microsystems in 1995 as an analog designer. In 2001 he joined the MEMS team in a marketing role and today he is marketing manager in the MEMS Sensor Division. Luca has contributed to 25+ international patents and has presented at multiple conferences. He earned a degree in Electronic Engineering from Padua University. Simone Ferri joined STMicroelectronics in 1999 as Central R D engineer, moved to the Audio Division as a digital designer and is now director of the Consumer MEMS Business Unit. He holds a degree in Electronic Engineering and an MBA from the Polytechnic of Milan. _______________________________________________________________________________________________Brush up on the latest MEMS and sensors trends and gain a new perspective on emerging applications. Register today!

Ahead of his presentation on the future of wearables at the European MEMS Sensors Summit 2018, 19-21 September in Grenoble, France, SEMI spoke with Dr. Peter Weigand, vice president, Business Strategy and Portfolio Management, Bosch Sensortec GmbH. Dr. Weigand gave a glimpse into insights he’ll share at the event.1. Wearables such as smartwatches, fitness trackers or hearables are becoming ubiquitous – but what are the must-haves for wearables for daily use by wearers?We see that users nowadays want to track their activities such as steps walked, calories burnt and floor levels “climbed” on a daily and holistic basis. “Quantifying yourself” is becoming an overall trend in our society with health, fitness and well-being continuously gaining in importance. This is only possible if information about activities is delivered comprehensively in an accurate manner. Therefore, at Bosch Sensortec we provide MEMS sensors that measure the user’s activity very precisely. For example, the smart sensor hubs BHI260 and BHA260 provide sophisticated in-sensor algorithms (e.g. activity recognition) with very low latency and guaranteed performance due to the real-time nature of the embedded software. From the system manufacturer’s perspective, “quantifying yourself” on a 24/7 basis means that the device has to be “always-on.”However, these always-on functions usually consume a lot of battery power, which poses challenges to the manufacturers and system designers, as the battery capacity is usually small due to the size of the wearable. This shows two other must-haves for the users nowadays. First, the compact size of the device. While smartphones have become larger, users of wearables benefit from the devices’ small size and their low weight, offering the possibility to wear them directly on the body. Therefore, we design the footprint and height of our MEMS sensors as small as possible to ensure the compact size and the ease of integration into new, stylish types of wearables. For example, the BMP388, measuring only 2 x 2 x 0.75 mm³, qualifies as the world’s smallest barometric pressure sensor. The second requirement in this regard is long battery life. Users do not want to charge their wearable device every other day, as this would also impede the always-on activity tracking aspect. At Bosch Sensortec, we hence provide MEMS sensors that run at ultra-low power to ensure always-on endurance and a long battery life. The BMA400 is an ultra-low power acceleration sensor that draws ten times less current than existing accelerometers.2. Are there any other user requirements for wearables?Yes, we see for example that just tracking the number of steps or the calories burnt is not enough anymore. Users require multi-functional devices that also provide information that can be used to monitor sleeping behaviour, navigate in cities, or prepare your smart home for your arrival. We are equipping our sensors with more features and developing new types of sensors that add new functionalities to wearable devices. For example, we have developed a smart watch Projection Module that can project information on the back of the user’s hand for an additional, enlarged display. While smart watches are rising in popularity, demand for basic wristbands is waning. Users are paying more attention to device design. Like clothing, the look and feel of the device should support the user’s individual style.At the same time, with more fashion brands are entering the wearables market we are providing sensors that are easy to integrate into new types of wearables such as hybrid watches. Our products feature a small form factor to ensure flexible, simple design-in. For example, the new BMA400 acceleration sensor easy to design into various applications. Finally, to conform to the user, the wearable must adapt to the user’s individual habits and motions such as learning different gestures, requiring the devices to be not only smart but increasingly intelligent with artificial intelligence (AI). We are providing sensors, such as the BHI260, with embedded, local intelligence with advanced algorithms that enable devices to learn. We are developing intelligent software solutions that use deep learning, enabling device to adapt to the user’s individual behaviour.3. What current techniques are design engineers using to reduce power consumption of wearables?Several techniques are being developed to reduce power consumption. The goal largely is to reduce the power draw of components that are always-on, such as the screen in a smartwatch. In activity trackers, the motion sensor is always on to sense, track, classify and store motion data. Reducing the power needed to operate these features will cut total system power consumption as well. A good example is our BMA400 accelerometer that has a current consumption of less than 1 µA in full operation.At the same time, it independently processes sensor data. For example, the device converts the three-axis motion sensor data stream into step counting events. This allows the main (host) microcontroller to remain in the stand-by mode required for activity tracking and to be activated by the accelerometer to deliver full power only, say, every 100 steps. The sensor, rather than the microcontroller, manages the overall duty cycling of the microcontroller to reduce system power and increase overall efficiency.4. What alternatives are engineers exploring to reduce power consumption? What is the role of intelligence directly within sensors for local processing capabilities in wearables?We have seen how the BMA400 can reduce power by integrating the motion classification functions. We can take this concept further by integrating a microcontroller that’s specifically tailored for low-power sensor data processing, such as the “fuser core” that Bosch Sensortec uses within its smart sensor hubs such as BHI260 or BHA260. The built-in sensor data fusion and machine learning hardware accelerators make it uniquely suited to reduce overall system power. The concept of edge computing has been around for many years, but only in this and the previous sensor generation with built-in local intelligence are we reducing the full power profile of the wearable device. Our sensor architecture design allows us to process the power locally in the MEMS sensor without waking up the main application processor.5. What technologies are you developing to lengthen battery life without compromising performance? We are continuously improving the MEMS and ASIC designs of our sensor portfolio to drive ever higher power efficiency. The BMA400 draws 10 times less current than existing accelerometers while delivering solid high performance (e.g. low-noise data). 6. Wearable device feature and performance requirements are continuously rising. Will batteries need to be larger to support these requirements? Since the beginning of the portable consumer electronics, improving batter life and reducing chip power consumption have been parallel efforts, a trend we expect to continue. However, we expect a greater focus on the overall system power reduction with sensors managing the power, turning on and off microcontrollers, radios (including GPS) and displays in wearable devices.7. What do you expect from European MEMS Sensors Summit 2018 and why do you recommend attending in Grenoble?The European MEMS Sensors Summit is a very important platform for us. It is an opportunity to meet partners, customers, industry leaders, to exchange ideas and to get new insights and thus to ultimately refine our solutions for our global customer base. Our ultimate goal is to improve people’s individual lifestyle and well-being.Serena Birschetto is a marketing communications manager in SEMI Europe.