Category Archives: Sensors

What are Digital Pressure Sensors?

Various industrial systems use pressurized air, water, and other fluids. They use sensors to regulate and maintain proper pressure at different points in their activities. Although many systems continue using analog pressure sensors, digital versions are fast replacing them. A few examples serve to illustrate why pressure sensors are important.

Industrial icemakers need water at minimum pressure between 20 and 40 psi at the inlet—this allows the water inlet valve to function properly—although the exact water pressure requirement is dependent on the particular make and model of the refrigerator.  Pressure sensors with media isolation (waterproofing) provide a quick method of determining whether the water pressure is adequate for making ice.

Corporate Average Fuel Economy (CAFE) regulations demand that by 2025, the average fuel economy should be 54.5 MPG fleet-wide. Although popular belief is, each car maker’s fleet should have a significant presence of electric and hybrid vehicles to meet CAFE requirements, manufacturers are working towards advanced diesel and gasoline engines that should be able to meet the standards by themselves. One model of such advanced engines is the Achates Power Opposed-Piston engine. It exhibits fuel economy gains of 30-50% with significant reduction of emission, and is more cost effective compared to other solutions. The Achates engine requires a fuel injection system capable of a 2000 bar injection pressure.

For cutting different types of very hard, heat-sensitive, or delicate materials, industrial machines often make use of a water-jet cutting system. This avoids heat damages to the workplace edges or surface. An ultra-high-pressure pump operating at 40,000-100,000 psi produces a high velocity, high-pressure stream of water at 30,000-90,000 psi. Special MEMS pressure sensors are necessary to achieve the desired accuracy, resolution, and repeatability in such high-pressure measurement systems.

All Sensors makes the DLVR Series of mini digital output pressure sensors based on their patented CoBeam2 TM Technology, providing overall long-term stability by reducing susceptibility to package stress. Compared to single die systems, the DVLR differential pressure sensor technology improves the position sensitivity.

The DC supply voltage option of 3.3 or 5 V eases the integration of the sensors into a wide range of measurement and process control systems. I2C or SPI interface options allow direct connection to serial communication channels. The sensor goes into very low-power modes between readings, thereby minimizing load to power supply for battery operated systems.

With a pressure range of 0.5 to 60 inH2O and a common mode pressure of 10 psig, the DLVR pressure sensors offer better than 0.5% accuracy over temperature. While the storage temperatures range from -40 to +125°C, the sensors can operate from -25 to +85°C, under non-condensing humidity limits between 0 and 95%. The sensors are available in ten types of device packages including E1NS, E1ND, E1NJ, E1BS, E1BD, E2NS, E2ND, E2NJ, E2BS, and E2BD.

The DLVR series of digital output sensors are compensated and calibrated by the manufacturer and provide a stable and accurate output over a wide range of temperature. Intended use for this series involves non-ionic and non-corrosive working fluids such as dry gases, air, and similar. Moisture or harsh media protection is also available in the form of an optional parylene protective coating.

A Rain Alert for the Raspberry Pi

This Raspberry Pi (RBPi) rain alert will let you know when it starts to rain, so you can reel in the clothes you had let out to dry after washing. Although the kit uses an RBPi3, any model of the RBPi family can easily handle this project. A later extension can make it send tweets as well, but for now, it simply triggers a buzzer.

The primary sensor in this project senses falling raindrops. This raindrop sensor is actually a printed circuit board with two traces running across the entire board in an inter-meshed dual comb pattern. As the two sets of teeth of the comb traces remain separated by about a millimeter, they show high resistance when dry. Their resistance decreases when a drop of water falls across the traces, shorting them.

A sensor controller tracks the resistance between the traces, the resistance reducing as more drops of water fall on the sensor. A potentiometer on the controller allows the user to adjust the level of detection when the normally high digital out pin will go low. When the sensor detects rain, it changes the status of the pin. The RBPi, monitoring the status, sets off the buzzer.

Since it is essential to detect the start of rainfall, setting the potentiometer to trigger when a couple of raindrops have fallen on the sensor is adequate. Adjusting it is easy, which you can do when you have two or three raindrops collected on the sensor. Turn the potentiometer until the buzzer just stops, and turn back until you hear it going again.

Since it has to detect raindrops, placing the sensor such that it is always under an open sky is important. However, as electronics and rain do not work satisfactorily together, it is very important the rest of the circuitry remains protected from rain. The best way to achieve this is to have the RBPi and rest of the electronics inside a waterproof plastic case, with only the raindrop sensor hanging out. Run the Python program here and wait for the beeps to inform you everything is working properly.

Apart from the raindrop sensor and its control board, you need only a few other parts to get the kit working. A few jumper wires, an active piezo buzzer, and a mini breadboard are all you need. You can start by connecting the output of the control board to the GPIO18 port of the RBPi to read its status, and set off the buzzer from the RBPi’s GPIO13 port, while the sensor detects raindrops.

If you do not like sounding a buzzer, you can activate some LEDs instead when it rains. Else, program the RBPi to send an email, an sms, a push notification, or tweets a photo warning when it detects rain. Since the continuous sounding of the buzzer will become tiring after a while, you can tweak the code to stop it after a while.

Since the sensor is out in the open, you will have to run out and wipe it dry as soon as it stops raining, to prepare it for detecting the next shower.

Motion Tracking through the MC3672

This year, the MSEC or MEMS & Sensors Executive Congress had mCube exhibiting their incredibly small and low-power MC3672, an inertial sensor product. This is a three-axis accelerometer, and its size is only 1.1 x 1.3 mm. This tiny WLCSP packaged device is a low parasitic unit, with enormous possibilities of unobtrusive use as low power motion tracking in wearable design, and in a completely new set of applications in future.

Recently, mCube acquired Xsens and they were able to couple a sensor fusion software to their tiny accelerometer. This gave them the ability to sense body motion and capture solutions for health, entertainment, and fitness. The combination also allows them to control and stabilize inertial measurement units in industrial applications.

Almost all are aware of MEMS motion sensors, as tablets, smartphones, and wearables use them popularly. Use of the MC3672 accelerometer will generate more applications for these devices in the future. This could include new areas such as in the medical world, related to prevention and diagnostics of illness. For instance, when visually inspecting the throat, stomach, or intestines of a patient, physicians often need to perform invasive and unpleasant procedures.

In future, patients would be able to swallow a camera-pill that can wirelessly beam images from the inside of the body to a display for the physician to view. Miniature motion sensing incorporated within the camera-pill could allow medical practitioners to navigate the pill effectively by actuating and controlling it. This would allow them to monitor its location and orientation in real-time as it passed through the body. Images captured by the camera would enable precise diagnosis and investigation of any problems.

According to Dr. Sanjay Bhandari, Senior VP of mCube, a plethora of new applications will come into life based on the granular, precise measurement of motion, orientation, tilt, and heading of the sensor. For instance, some applications will be able to capture motion data to communicate it to cloud software services, and ultimately sharing it with networked systems for monitoring and analysis.

Achieving most of the envisaged applications is only possible with motion-sensing systems that are extremely small and drain very little power from an arrangement of energy harvesting or a battery.

Along with the low power consumption and small system size, all components in the system must adhere to the design features. The sensor interface uses Silicon and CMOS-based circuits that filter, amplify, and fit the analog to digital processors to work its magic.

The monolithic, single-chip design by mCube integrates both the CMOS and the MEMS within a clever extension using a standard CMOS-base process. This is a reliable procedure for handling high volumes and produces excellent yields. Within the chip, mCube has interconnected the MEMS and the CMOS very efficiently.

In future, mCube plans to integrate BLE or Bluetooth Low Energy into the MCU in its SIP package—they want to realize IoMT-on-a-Chip. They have protected their technology by 100 approved patents.

The acquisition of Xsens brought to mCube the 3D technology to track motion in the sensor world—a high-precision module for sensing motion in 9 degrees of freedom.

Using Hall-Effect Type Sensors Effectively

We are familiar with appliances such as wine coolers, freezers, and refrigerators. They keep out beverages and food cold, extending their useful life. Most often, these appliances have lights that illuminate the insides when the user opens their doors. Since the lights only need to be on when the user opens the door, usually, the designer of such appliances place a sensor to detect the opening and closing of the door.

A sensor of the Hall-effect type can detect the position of the door. In refrigerators, the position of the sensor is within the frame, while a permanent magnet is placed on the door directly opposite the Hall-effect type sensor. For refrigerators with multiple doors, each door needs a magnet and for the detection, each magnet must have a corresponding sensor placed in the frame. The adjustment of proximity of each Hall-effect type sensor and magnet pair is such that the Hall-effect type sensor detects the magnet only as the door closes completely.

An electronic control unit inside the electronics assembly of the refrigerator monitors the output from the Hall-effect type sensors and turns the lights on or off as necessary. Hall-effect type sensors can detect a variety of proximity- and position-sensing applications such as when there is a need to discover the proximity of a moving part relative to a sensor placed in a fixed location.

For instance, Hall-effect type sensors can help to stop the motor opening or closing a garage door once the door has reached its desired position. Typically, this needs a system of two Hall-effect type sensors to detect the two dominant positions of the door—open or closed. Each sensor also needs a corresponding magnet to trigger it.

The position of one of the magnets on the drive chain of the garage door opener places it directly next to the sensor that detects a closed door. The position of the other magnet, also on the drive chain, is such that the drive chain brings it next to the other Hall-effect type sensor as the door opens completely.

Hall-effect type sensors are preferable to other sensors such as reed relays, as the former has no moving electrical contacts, resulting in long life and improved reliability. Other applications that use Hall-effect type sensors effectively are vending machines, security locks on doors, vacuum cleaners, washing machines, dishwashers, and similar applications requiring door- and lid-position sensing.

A flow switch is another application that benefits from the use of a Hall-effect type sensor, which detects the motion of a piston, paddle wheel, or a valve fitted with a permanent magnet. For instance, this arrangement suits tankless water heater units, where the flow sensor has a permanent magnet fixed to a piston. The increasing presence of water pressure in the system moves the piston and its associated magnet near to a permanently positioned Hall-effect type sensor. This causes the output of the Hall-effect type sensor to change and it signals the presence of flowing water.

Similarly, a turbine can have a magnet attached to its blades. As the blades rotate, the magnet passes by a fixed Hall-effect type sensor. The speed at which the blades rotate is proportional to the fluid flowing through the turbine.

What are Depth Sensors?

Ocean going ships typically use depth sensing techniques mainly for locating underwater objects to prevent running into them. This included gauging the distance of the sea floor. The principle involves measuring the time a burst of sound directed into the water takes to return after reflecting off an object. This time of flight gives a measure of its distance from the source of the sound, as the speed of sound traveling in water is fairly constant, depending on the water density and its temperature.

With the advent of peizo electronic devices it was possible to use ultrasonic sound frequencies to measure distance, using the same principle of measuring the time of flight. As better electronic components improved, engineers used the same technique for measuring distances using light waves in place of sound, as using light waves resulted in greater measuring accuracy as well as the ability to measure smaller distances.

Smartphone manufacturers are using depth-sensing techniques to enable facial detection, recognition, and authentication in their devices. However, this technology has far more potential, as Qualcomm is demonstrating. In collaboration with Himax Technologies, Qualcomm is promoting its Spectra image signal processor technology along with a 3-D depth-sensing camera module for Android systems. Very soon, we will be witnessing the emergence of a depth-sensor ecosystem, complete with firmware and apps.

Himax has expertise in module integration, drivers, sensing, and wafer optics. Qualcomm has combined their Spectra imaging technology with the technology from Himax and created the SLiM depth sensor suitable for mobiles. This has ample applications in surveillance, automobiles, virtual reality, and augmented reality. It took more than four years for developing the 3-D sensing solution.

The camera module from Qualcomm senses depth in real-time, and simultaneously generates a 3-D point-cloud of data in both indoor and outdoor situations. Qualcomm expects smartphone manufacturers to begin incorporating the computer vision camera module in their products in the first quarter of 2018.

Using infrared light, the camera module uses the well-known time of flight technique based on speed of light for resolving the distance from an object. The camera projects dots of infrared light onto the object, creating a cloud of points, which the sensor reads for the time of fight, thereby gathering depth information.

Approaches based on depth sensing techniques are gradually moving towards mobile handsets and head-mounted displays. Although mobile platforms may not be able to supply adequate power for room-scale 3-D sensing, they are certainly capable of managing the power required by the sensor and the image signal processor for running the complex software necessary for translating the point-cloud into an interactive and useful input.

The sensor packages use sub-half-watt range active laser illumination for providing high-quality point-clouds for short distances with structured-light solutions for applications involving facial and gesture recognition. However, for serving longer distances such as applications involving room-scale sensing involving a sensing range of 2-10 meters, the sensor packages will have to use high power lasers in the 5-W range.

As the power requirements for longer ranges are beyond those available from average mobile phones, designers are forced to adopt purely camera-based approaches for applications involving longer-distance image recognition.

Working with Gas Sensors and the Raspberry Pi

Many devices predicted by earlier science fiction stories and movies have come true. Among them are gas detectors as envisaged by the TV series Star Trek. If you have a single board computer such as the Raspberry Pi (RBPi), you can use it to detect the type of gas and air quality around you. Of course, you will need to couple the RBPI with a gas sensor, and among the popular gas sensors available are the BME680 from Bosch, and the CCS811 from AMS.

Gas sensors are helpful in sniffing out volatile organic compounds, many of them not only poisonous but also flammable. Volatile organic compounds may be natural or manmade, including paints and coatings that require solvents to spread in a protective or decorative coating. Where earlier the paint and coating industry used toxic chemicals, they are now shifting towards aqueous solvents. Natural volatile organic compounds may come from direct use of fossil fuels such as gasoline or as indirect byproduct such as automobile exhaust gas.

Some volatile organic compounds may also be carcinogenic to humans. Among them are chemicals such as benzene, methylene chloride, perchloroethylene, MTBE, Formaldehyde, and more.

BME680

Bosch developed this tiny sensor BME680 specifically for applications involving mobiles and wearables that require low power consumption. This one sensor has high linearity, and measures temperature, humidity, pressure, and gas with high accuracy. This 8-pin LGA package is only 3 X 3 X 0.95 mm, and Bosch has optimized its power consumption based on the specific operating mode.

With high EMC robustness and long-term stability, the BME680 measures indoor air quality, while detecting a broad range of gases and volatile organic compounds. For instance, the BME680 can detect formaldehyde from paints, and other volatile organic compounds from paint strippers, lacquers, furnishings, cleaning supplies, glues, office equipment, alcohol, and adhesives.

Apart from applications for indoor air quality measurement, BME680 is also useful for applications such as personalized weather station, measuring skin moisture, detecting change in rooms, monitoring fitness, warning for dryness or high temperatures, measuring volume and air flow, altitude tracking, and more.

CCS811

Compared to the BME680, the CCS811 is only a digital gas sensor. It is meant for monitoring indoor air quality using a metal oxide gas sensor. The gas sensor can detect a wide range of volatile organic compounds. The CCS811 includes a micro-controller unit, an analog to digital converter, and an I2C interface.

With optimized low-power modes, AMS has designed the CCS811 for high volume and reliability. It has a tiny form-factor that saves more than 60% in PCB footprint, while producing stable and predictable behavior regardless of air quality at power up.

Similar to the BME680, the CCS811 also measures the total volatile organic compounds and the equivalent of calculated carbon di oxide. However, the consumption of CCS811 being about 60 mW, it may be necessary to have to supply it with an external supply of 3.3V.

Both sensors need the working I2C bus on the RBPi to interface and function. The software library for the two sensors are available here for the BME680 and here for the CCS811.

Sensing Movement in Three Axes

All modern vehicles must sense the position and movement of automotive control functions such as turn signal indicators and gear selectors. However, engineers face challenges here with conventional sensor technologies as the requirement is for sensing movement in the three axes simultaneously. The challenge lies in the physical size of the device, its reliability, power consumption, and its cost. However, 3-D magnetic sensing technology, recently introduced, could be helping engineers to address these challenges.

It is well known that electro-mechanical switching is a common source of failures in the several applications, including in automobiles. Contacts usually corrode or burn out over a period, causing inconveniences and failure to the owner of the vehicle, also potentially damaging the reputation of the manufacturer of the car. Therefore, most car manufacturers prefer using solid-state technology, such as switching based on Hall-Effect detection of magnetic signals. This method increases the reliability, saves space, and is inexpensive.

When driving a car, among the most common things people do is to signal for a turn and change gears. In the past, most cars used heavy current wiring harnesses around the vehicle for transmitting signals and power. Lately, using a turn indicator or a gearshift is more likely to send a high-impedance signal to a central processing unit rather than physically switching something over.

Vehicular control is becoming more sophisticated and multi-functional, with the trend moving towards sensing in more than one plane. For instance, most modern cars using automatic gearboxes now have sequential controls and move the gear lever into a different plane. That makes the task of sensing position more complex than ever.

Magnetic 3-D Sensing

Hall Effect sensing for implementing 3-D position sensing is actually possible in several ways. One can place individual Hall sensors at the multiple fixed positions where the movement has to be sensed—just as in the case of a turn signal or a gear lever. This may result in as many as seven sensor elements, and the controller will know the position by locating the live sensor.

Another method could be to use flux concentrators. Although this method also uses Hall sensors, the number of sensors used is lower. This is because two pairs of orthogonal sensing elements are integrated into a CMOS IC, whose surface has a deposit of a ferromagnetic film to enhance the magnetic field, increase the sensitivity, and increase the signal-to-noise ratio.

Several algorithms in subtraction and addition make it possible to accurately sense the magnetic field components present in the horizontal (X and Y) and the vertical (Z) directions to the IC. Analog to digital converters then convert these analog voltages from the sensors to digital values and the digital signal processors then compute the final, absolute position.

However, none of the above is a viable solution in the automotive sector, as these are not suitable for mass production, because multiple sensors are involved. However, there is another alternative, also based on Hall-Effect sensors—the TLE493D-A1B6 3-D sensor. This simultaneously determines the x, y, and z coordinates of the magnetic source, while building a 3-D image of the magnetic field that surrounds the sensor.

Is Chirp Microsystems Usurping UI?

User Interface (UI) is on the verge of a major shakeup as it was evident at the Mobile World Congress (MWC) this year. Leaving behind other UI interfaces such as motion, touch, and voice, touch-less is now looming large and lucrative as the new UI of choice for consumer devices. Touch-less means you can operate your device simply by waving your hands near it, without actually touching it.

The CEO of Chirp Microsystems, Michelle Kiang is of the opinion that the UI revolution has been bringing on constant consumer electronics breakthroughs. Chirp is offering a single-chip sensor working as a time-of-flight (ToF) ultrasonic unit, to allow users to interact with wearable devices even without actually touching their screens, or interacting with devices that work without screens.

Although the touch-less technology, based on ultrasonic sensing, is not yet ready to replace other existing UIs, Kiang is of the view that it will certainly add another level of modality to automotive, smartphones, AR/VR, and wearables.

Chirp Microsystems is a startup from Berkeley, California, with a UC Berkeley and Davis heritage. At the MWC, they presented the company’s first high-accuracy ultrasonic sensing development platform. As they have especially targeted the platform for wearables, it has ultra-low power consumption. The breakthrough by the team of engineers and researchers at the University of Berkeley and Davis—miniaturization of the MEMS-based ultrasonic sensor—formed the foundation of the startup.

According to Kiang, most smartwatches and other wearables suffer from small screen sizes that have limited surface, and do not work well with fat fingers. The MEMS-based ToF ultrasonic sensors embedded inside the smartwatch helps users with any type of fingers to use gestures. They can control the functions of the watch, even without touching the screen.

For instance, the wearable wristband has no space for a screen on it. That makes it powerless to interface with its wearer directly. However, the ToF ultrasonic sensor is tiny enough to be embedded within the band or even in a ring. Now, all popular wearable bands can interact with their wearers.

The ToF ultrasonic sensor from Chirp comes in a 3.5 mm package called Land Grid Array (LGA). According to the company, the chip operates on a 1.8 V supply, and is similar to a MEMS based microphone. Integration into consumer electronics products is simple, as the IC has an I2C interface.

Along with the MEMS ultrasound transducer, Chirp has also developed an accompanying mixed-signal CMOS ASIC. Then they combined both into a system-in-package, making it easier to use.

The on-board microprocessor with the ToF sensor works in an always-on mode for applications requiring wake-up sensing. According to the company, the pulse-echo sensing range is greater than a meter, but consumes only 9 µA, working at 1 Hz sampling rate.

After the transfer of the IP and the key researchers from the University to Chirp, including David Horsley, several PhD students and postdocs from the University have also joined Chirp. David Horsley was a professor at the University of California and Davis, in the department of mechanical and aerospace engineering, and is now the CIO at Chirp Microsystems.

Moving 3-D Sensing Into Smartphones and Vehicles

Chirp Microsystems, a new startup from Berkeley, California, has developed a new Time of Flight (ToF) ultrasonic sensing platform for use in wearables and Virtual and Augmented Reality (VR/AR) systems. They have selected some big customers to whom they have made available their development platform.

At present, the high-end VR/AR systems are typically confined to a prescribed space, or tethered to a base station. The limit comes from the requirements of additional equipment in the space for creating better tracking experience. Usually, the additional equipment is often a magnetic sensor or a camera-based system that can correct drifting by using the inertial measurement unit (IMU) within the head units of the VR/AR system.

Chirp has demonstrated they can embed their miniaturized MEMS ultrasound sensors within the AR/VR head unit. With the sensors in place, the user has a 360-degree immersive experience, as the tracking system moves along with the user. Supporting inside-out tracking, the ultrasound sensors from Chirp can have controllers or input devices working with six-degrees of freedom—offering 3-D sensing.

VR/AR systems already use the optical or camera-based system for tracking. However, the camera is only a 2-D device, incapable of providing any sort of depth information. Even to detect if objects have shifted from one frame to another, a camera needs to use the point cloud, while applying very complicated calculations.

On the other hand, ToF ultrasound sensors can easily detect 3-D movement. This is because the technology is adept at triangulating data easily, and simpler calculations demand much less power.

Although it is another option for 3-D sensing, infrared technology has limited use when the sensor is outdoors—the heat outdoors tends to wash out infrared sensing. However, ultrasound sensors are robust and consume low power, and able to perform well in VR/AR systems outdoors, even in the presence of a bright sun.

While using the ToF ultrasound sensors in VR/AR systems, Chirp hopes the low-end VR/AR systems will improve the interactive experience, and smartphones and vehicles can start using the untethered high-end VR/AR systems.

For instance, smartphones use infrared technology currently as a proximity sensor. This actually prevents the user’s cheek from dialing the phone by itself. However, this requires the smartphone to have a tiny hole for the infrared sensor embedded on the face of the smartphone.

According to Chirp, some smartphone vendors have shown interest in replacing infrared with ultrasound. This would improve the aesthetics of the smartphone by removing the tiny hole on the face of the phone. Additionally, the ultrasound sensors can also add features such as autofocus when taking selfies, and add simple gesture functions to the phone.

At present, vehicles use bulky ultrasound sensors, for say, backing up. Chirp hopes to replace them with its ToF ultrasound sensors. They can also use the sensors as a User Interface (UI) inside cars for infotainment systems. However, as automotive applications tend to use long design-in cycles, Chirp is keeping this in low-priority for the time being. Chirp is planning to ramp up production of its ultrasound MEMS sensors and accompanying ASICS later this year.

Piq: This Ski-sensor Measures Details of your Skiing

Most skiers want feedback about their skiing, for improving their technique. The ski sensor from Rossignol offers one that not only does what skiers want in unprecedented detail, but also light and tiny enough to be unobtrusive. For instance, you get details about edge-to-edge transition time, in-air rotation, g-force, airtime and more. The sensor is slick enough and low profile, so you may not even notice that you have it on you.

This multi-sport ski sensor, Piq, measures just 44 x 38 x 5.4 mm. In the three-piece setup, the largest is the AA-battery sized charging unit. When not in use, you can simply plug this into the USB port of your computer and leave it for charging. It has a steel clamp to allow the Piq sensor to snap under it when you are resting. This gives the Piq sensor a quick recharge during say, lunchtime. In real use, the Piq sensor stays in a small pocket on the ankle strap that you strap around your ankle. You must be careful when you wrap and strap the ankle strap to prevent the Piq sensor from flying out during some of the most aggressive sessions.

Once you have had it on securely, you can forget about the Piq. Those who tried it on for multiple days, say the Piq never budged, even when the skier straight-lined it at over 100 kmph, jumped, skied corn snow, groomers, hard pack, and deep powder. In general, whether you slash, thrash, and even smash a few gates, this tiny, light, and secure Piq sensor will stay with you.

The Piq sensor has its own battery, powering it on for continuous tracking for about three hours, according to the manufacturer. In actual practice, the battery lasts longer than the manufacturer’s claim, before needing a recharge. This is indeed a big plus for the Piq, as it is very rare for the battery performance in a device to exceed the manufacturer’s claims.

While you are on the snow, the Piq sensor will track and record several statistics such as your speed, rotation time in the air, total airtime, G-force when you land, and the G-force when you take a turn. It will record your edge-to-edge transition time and the angulation of your ski in a turn, generally known as the carving degree. You can time your skiing time, as against standing or riding the chair, etc., your total run, and all your motions including the turns and jumps during the session. Piq will even count the turns per minute when you are skiing.

A free Android or iOS app companion allows the user to get access to the data the Piq sensor has acquired. No cable connection is necessary, as the smartphone connects to the sensor via Bluetooth 4.0. However, the app does not give you the data in real-time. Rather, it synchronizes your session when you trigger the specific function within the app.

An interactive, info-graphic style interface displays the data you pulled in and allows you to look at topline data for the session. You can then drill down to specifics about your turns and jumps.