Entering the wearable device market, Sensor Hub creates a digital sixth sense

Sensor Hubs are entering the wearable market. To create more diverse sensing applications, wearable electronic products have been equipped with an increasing number of sensors, which has caused increasingly serious power consumption issues. Therefore, semiconductor companies have developed ultra-low power consumption Sensor Hub solutions that consume only 1-2% of battery energy to help wearable device manufacturers achieve power-saving and accurate situational awareness functions, making wearable products the user's digital sixth sense.

　　Andy Pease, president and CEO of QuickLogic, said that high-end mobile phones from brands such as Samsung Galaxy S4, Apple iPhone 5S or Fujitsu all place great emphasis on novel smart sensing functions, including health monitoring, indoor navigation and positioning, etc.; future mobile devices will add more intelligent functions, including advertising prompts, natural disaster warnings, safe driving, etc., and all of the above functions must be realized through sensors such as gyroscopes, magnetometers, light sensors, and pressure gauges.

　　According to a market research report by Semico Research, smartphone applications will account for 57% of the nine-axis sensor market in the next five years. At the same time, the number of sensor hubs will also increase simultaneously to support the above-mentioned complex sensing solutions. Therefore, the sensor hub market size will reach US$2.7 billion in 2017, with a compound annual growth rate (CAGR) of 26% from 2013 to 2017.

　　Pease emphasized that sensor fusion is a key function of the sensor hub, and today's software developers focus more on providing more accurate sensing functions through advanced algorithms. For example, in the past, pedometers only recorded the number of steps and distance, but in the future, the function will be upgraded to record the distance between each step and whether the phone is held in the consumer's hand or in the pocket; on the other hand, the health management function of the mobile phone will also be upgraded from weight recording and step counting to identifying the type of exercise or the slope and direction of movement, so as to accurately calculate the user's calorie consumption.

　　However, the precise sensing function of mobile devices consumes considerable power. Since the situational awareness information changes hundreds of times a day, the always-on situational awareness solution requires real-time sensor management, ultra-low power sensor algorithms that consume only 1-2% of the battery capacity, minimal interference to the GHz-class application processor (AP), and the performance of processing high-speed and precise motion sensing.

　　Pease pointed out that sensor hubs must take into account both power consumption and the flexibility to operate various context-aware information. However, sensor hubs based on application-specific standard products (ASSPs) do not have adjustable flexibility and their power consumption ranges from 1 to 10 milliwatts (mW). Although microcontrollers (MCUs) or application processors are more flexible, their power consumption may be higher than 100 mW. In contrast, ultra-low power sensor hubs use software-enhanced programmable devices to have adjustable flexibility for new algorithms and can operate at less than 1 mW of power consumption, which is one-thirtieth of the MCU solution. Therefore, this solution will also have a clear advantage in the wearable electronics market in the future.

　　QuickLogic's ultra-low power sensor hub platform combines three major blocks: Communication Manager, Flexible Fusion Engine (FFE) and Sensor Manager, which can manage and calculate the sensor data of smartphone application processors in real time. Among them, FFE is specially designed by the company to process, filter and translate sensor data before transmitting it to the application processor. The microcode of FFE can be programmed, so it can realize complex algorithm functions such as sensor fusion, background sensor calibration and context change algorithm.