Tag Archives: sensors

Sensor Technologies for Air Quality Monitoring

Although air is all around us, we breathe it in every minute, and our lives depend on it, yet we pay very little attention to the quality of air, unless when facing a problem. Whether it is indoors or outdoors, poor air quality can affect our health and well-being significantly. Two levels of air pollution measurement are significant here.

One is the presence of small PM2.5 or Particulate Matters measuring less than 2.5 microns in size—one micron being one-micrometer equal to one-millionth of a meter or one-thousandth of a millimeter. The other is the presence of VOCs or Volatile Organic Compounds.

Combustion processes emit PM2.5 type of pollutants, for instance, by fires burning in fireplaces and lit candles within the house. Cleaning textiles, furniture, and supplies can emit VOCs. Engineers and scientists are working on improving sensing technologies to enable monitoring PM2.5 and sensing VOC by personal air quality monitoring systems for improving the health and well-being of the people.

According to the WHO, PM2.5 enters our lungs easily causing serious health problems such as chronic and acute respiratory diseases, asthma, lung cancer, heart diseases, and stroke. A recent study by Harvard University links PM2.5 exposure to sensitivity to viral diseases such as SARS-CoV-2.

While one does receive averaged or consolidated data from official air quality monitoring stations, that data is for the outdoor environment only. For indoor air pollution monitoring, a portable air quality measuring device, also known as a dosimeter, is more appropriate—especially when incorporated within a wearable or a smartphone. So far, PM2.5 sensors were too large for mobile devices. Bosch Sensortec now has sensors that make it possible to incorporate them into personal devices.

The Bosch PM2.5 technology offers sensors small enough to incorporate within wearables and smartphones for measuring the daily exposure of a person to PM. The person can see data and trends of local pollution levels to which they are exposing themselves, and take appropriate actions to minimize their exposure for improving their health and well-being.

BreezoMeter uses PM2.5 sensor technology from Bosch Sensortec to make PM2.5 Dosimeters. They also offer an app for the Dosimeter that collates local data measured by the Bosch PM2.5 sensor and the air pollution data from the BreezoMeter to calculate and display the personal daily PM exposure.

Conventionally, PM sensors rely on a fan to draw air through a cell, where optical arrangements count the particulate matter and calculate the concentration per unit of volume. This arrangement requires the sensor to be the size of a matchbox, incapable of incorporating within a smartphone.

PM2.5 sensor technology that Bosch Sensortec has developed functions on natural ambient airflow. The principle is rather like a camera, with three lasers integrated behind a glass cover. To prevent damage to the user, Bosch uses Class 1 lasers that are eye-safe. The entire arrangement is flat enough like a smartphone camera is, making it easier to incorporate within one, and using only 0.2% of the volume of air that other solutions on the market typically use.

Coreless Magnetic Current Sensors

Modern industrial drives require accurate current measurement for effectively regulating the torque and ensuring maximization of operational efficiency levels. For achieving necessary efficiency levels along with the safety requirements, the measurement methodology must achieve a high degree of linearity and respond rapidly. This is especially true for detecting conditions such as short-circuit and over-current. For instance, it is necessary to arrest the fault condition from an over-current situation within 3us or less. The detection, evaluation, and triggering process must occur within 1 us or less. Therefore, it makes tremendous sense to include this capability within the current sensor.

A popular current measuring scheme involves using a shunt resistor in series with the current under measurement. However, this involves insertion loss, with the resistance of the PCB track, solder joints, and wiring contributing to the loss in addition to that from the shunt resistance. The design becomes more complex if the shunt resistor requires galvanic isolation between control electronics and power output stages.

A better alternative is the magnetic current sensor, primarily based on Hall effect and using core-based or core-less sensing. Being non-resistive, magnetic current sensors involve an insertion loss of a far lower amount. Moreover, magnetic current sensors are contact-less, thereby providing inherent isolation between low voltage and high voltage circuits.

A current flowing through a conductor generates a magnetic flux. A core-based sensor typically concentrates the flux in its ferromagnetic core. The open-loop configuration of the sensor typically uses a sensing element within the air-gap, where the flux concentration is the maximum. This arrangement can have hysteresis and temperature drift errors.

The closed-loop configuration has a compensation winding with current flowing in the opposite direction to minimize the hysteresis and temperature drift errors. Although providing very precise current measurements, the approach is complex and the introduction of the compensation winding generates additional power losses.

In contrast, a core-less sensor does not use a ferromagnetic core, thereby avoiding the hysteresis and temperature drift errors altogether. Current measurement now depends totally on the magnetic field that the current-carrying conductor generates. Although the flux density that the wire generates is much lower, modern electronics design easily compensates for this.

Like the core-based sensor, the core-less sensor also has an open-loop and a closed-loop design. In closed-loop sensing, compensatory windings equalize the flux density and use Hall element sensing. The open-loop sensing uses highly linear Hall elements. Therefore, closed loop sensing does not depend on the linearity of its Hall elements.

With core-less sensors using very low levels of flux density, industrial environments with EMI often makes it difficult to measure the current accurately. Shielding improves the situation to a certain extent, but may not be totally adequate.

A differential measurement approach resolves the situation. This requires a suitable conductor structure along with the presence of at least two sensor elements arranged with their sensitivities in perpendicular. If the electrical connection has the polarities of the sensors opposing each other, and the positioning of the elements above the conductor is symmetrical, they effectively cancel the common-mode component of any external stray fields that may disturb the current measurement.

Contactless Magnetic Angle Sensing

Contactless magnetic angle position sensors are now giving optical encoders a run for their money. This was recently demonstrated by Monolithic Power Systems at Electronica 2018. They had on display a unique non-automotive-focused electric vehicle, mCar, with motion control and angular sensors. According to MPS, their mCar demos two main functions—motor control elements, and angular position sensors.

As Quitugua-Flores, the mechanical engineer and primary designer of the mCar at MPS explains, the steering of the car is a complete drive-by-wire concept, and there is no mechanical connection between the tires and the steering wheel. A magnetic angle sensor detects the angle of the steering wheel and converts the signal to control the tire angle necessary for the various steering modes. The magnetic angle sensor provides visible feedback via a blue LED mounted on the dashboard, with the LED lighting up when the driver turns the steering.

An electronic system takes in the magnetic angle sensor information and feeds it wirelessly to the rest of the car, thereby instructing the wheels to turn. The angular sensor, along with the board and antenna for sending the wireless signals is attached to the steering column.

The throttle and brake pedals use similar rotary magnetic angle sensors and send their signals wirelessly just as the sensor on the steering wheel does. Pivots on the brake and acceleration pedals house the angular sensors, and they measure the angle of depression of the pedals.

However, MPS has made the mCar as an R&D application, and they have not yet approached the National Highway Traffic Safety Administration (NHTSA) for compliance with their safety regulations.

According to Quitugua-Flores, another aspect of the mCar is its driver seat pivots freely. The front and rear suspension modules keep the seat suspended such that when the mCar enters a curve, the seat tilts into the turn just as it happens in a motorcycle or a plane. This keeps the driver firmly in the seat in a turn, rather than being literally pushed out of it.

An angle sensor attached to the seat detects the rotational position and sends the information to the suspension control. The shock absorbers in the mCar come with individual integrated BLDC motors that can change the length of the shock absorbers independently. Therefore, the suspension has complete control over camber or the vertical tilting of each wheel. As the frame of the mCar tilts when turning, the suspension changes such that each tire tilts in a corresponding direction—just as a four-wheeled motorcycle does.

Shafts suspending the driver cockpit also have angular sensors attached to them. This allows the driver to enjoy a smooth ride by controlling the behavior of the suspension.

According to MPS, the mCar is only a demonstration for the effective operation of a sensing and motion control for a demo Electric Vehicle but is not a high-precision application. For systems requiring high-precision applications, MPS has demonstrated a robotic arm that allows seven degrees of freedom.

With sixteen angular sensors inside it, the arm demonstrates the capabilities of the current generation of MPS angular sensors for precision applications.

Metamaterials Improve LIDAR

Light Detection and Ranging or LIDAR is a remote sensing method. The technique uses the time of flight of pulsed laser light to measure variable distances. Airborne systems record additional data, which, when combined with the data from the light pulses are able to generate three-dimensional information about the neighboring environment that offer precise surface characteristics.

In general, a LIDAR comprises a laser, a scanner, and a specialized receiver for Global Positioning System or GPS. Although so far, common platforms for LIDAR used helicopters and airplanes for acquiring data over broad areas, autonomous vehicles are now using Topographic LIDAR extensively for navigation through road traffic using a near-infrared laser to map the nearby area.

Using LIDAR systems help scientists and engineering professionals examine both artificial and natural environments with precision, accuracy, and flexibility. As the market for LIDAR is still in its nascent state and its technologies fragmented, there are only about 70 LIDAR companies worldwide, making it a hotbed of new technology.

For scanning a wide area, conventional LIDAR systems have to rely on electro-mechanical spinners to steer laser light beams. Not only does this method reduce the scan speed, but it also affects measurement accuracy. A Seattle-based, venture-backed startup, Lumotive, is now developing a new technology that will change the way LIDAR systems function.

According to Bill Colleran, co-founder, and CEO of Lumotive, they are developing a LIDAR system that can steer beams but has no moving parts. Rather, their patented technology uses the light-bending properties of metamaterials such as Liquid Crystal Metasurfaces or LCM to steer the laser beams. Bill calls the use of such metamaterials “pivotal technology.”

However, Lumotive is not the only player in the field to offer LIDAR systems that do not rely on mechanical scanning. Other rivals have used optical phased arrays or MEMS mirrors to claim their LIDARs use a lower number or no mechanical components.

According to Bill, Lumotive LIDAR systems use LCM semiconductor chips. The main advantages of LCM are it offers a large optical aperture of about 25 x 25 mm, resulting in a longer range for the LIDAR, along with a 120-degree field of view. The high performance of the LCM comes from its fast-random-access beam steering capability.

When a laser beam shines onto the Lumotive’s liquid crystal metasurface chip, programmed electrical signals can direct the reflected light into any direction within its 120-degree field of view.

Metamaterials are mostly artificially structured materials that allow unprecedented control over their properties, specifically in new ways for controlling the flow of electromagnetic radiation including light. For instance, Kymeta has a flat-panel satellite antenna technology based on metamaterials.

Kymeta’s antenna can move electronically. It does not require the conventional phase shifters, amplifiers, and related components on its surface. This not only cuts down the cost, it also consumes far less power and does not require cooling devices. Compared to conventional antenna systems, Kymeta is able to increase the density of their flat-panel antenna elements dramatically, while controlling the phase and amplitude simply by activating or deactivating individual antenna elements. Lumotive have adapted the Kymeta antenna’s metamaterial architecture to their LIDAR system.

What are Linear Image Sensors?

Fairchild Imaging makes CMOS 1421, a linear image sensor. This is an imaging device with a wide dynamic range of 94 dB or 52000:1, with excellent linearity. The device is a linear sensor, meaning it has 2048 x 1 high-resolution imaging sensors. Fairchild has designed this linear sensor for medical and scientific line scan applications such as optical inspection or fluorescent imaging that require wide dynamic range, high sensitivity, and low noise operation.

With several acquisition modes, this photodiode pixel has an optical area measuring 7 x 10 µm with a pitch of 7 µm and a fill factor of 85%, making the operation of this sensor very flexible:

  • Read after Integration: This mode is ideal for applications with high quality signals
  • Buffered Read after Integration: is a high speed mode that integrates the next line while reading the current line
  • Read on Integration: This is a non-CDS mode, allowing the highest speed of operation
  • Multiple Read during Integration: This mode is for low-light applications, permitting oversampling during integration

Other than the above, a programmed mode, accessible through JTAG interface, meets a wide range of specialized imaging requirements. Readout cycles in this mode are controllable through external signals.

CMOS 1421 has several features such as very low dark current, very low readout noise, and non-destructive readout for fowler sampling. Along with anti-blooming drain and electronic shutter, the CMOS 1421 also features two independent gain settings for each pixel. The entire device is enclosed in an RoHS compliant CLCC and PLCC package of 22.35 x 6.35 x 2.85 mm dimensions. The device consumes 40 mW of power while operating from 3.3 VDC. Major applications of linear image sensors are in microscopy, photon counting, and fluorescent imaging.

CMOS 1421 has a pixel array consisting of a photodiode, a pixel amplifier, and a sample and hold circuit. Along with the above, each pixel has a noise suppression circuitry and a gain register. While the pixel-level gain affects the device sensitivity, it also has a bearing on the noise and conversion factor of the sensor.

Linear image sensors from Fairchild use thinned back-illuminated large area arrays. Fairchild offers custom capabilities such as extreme spectral band detection, low noise active reset CMOS architecture, and high-resolution X-ray imagery using these sensors.

These linear image sensors are ideal for visible, ultra violet to visible, and visible to near infrared spectrometers, and their enhancement makes them suitable for spectroscopy applications. The design of their pixels being tall and narrow helps light distribution from a spectrometer’s grating. If provided with UV sensitivity, these sensors do not need extra UV coating.

CMOS 1421 displays superior linearity, which is of extreme benefit to spectroscopy measurements. The device also includes an electronic shutter along with a built-in timing generator, which are useful in spectroscopy. The device is suitable for several applications involving scientific, industrial, and commercial activities.

New sensors based on CMOS match features with those of CCDs. Featuring simpler external circuit design, and simpler operation, CMOS 1421 linear image sensors are suitable for spectroscopy, displacement measurement, barcode scanning, and imaging.

What are 3-D Image Sensors?

3-D image sensors from Infineon are perfect for use in mobile consumer devices. These new REAL3 image sensors measure the time-of-flight of infrared signals, enabling sensing gestures the user makes in front of the screen. Infineon has designed the sensors with a perfect combination of power consumption, performance, functionality, cost, and size. The IRS238xC 3-D image sensors work in any kind of ambient light conditions and this makes them indispensable for reliable use in mobile applications.

The IRS238xC has high-performance pixel arrays that are highly sensitive to infrared light of 850 and 940 nm wavelength. This allows the device to perform unparalleled in any outdoor environment. Combined with this, Infineon has provided its patented SBI or suppression of background illumination circuitry in every pixel. The combination extends the nominal dynamic range of each pixel by nearly 20 times.

As the single-chip design has a high integration level, it allows the user to optimize the bill of material. Apart from this, it also reduces the design complexity and offers a small form factor. There are other advanced features as well, such as integrated high-performance ADCs, illumination control logic, a modulation unit with high flexibility, and circuitry for eye-safety that enables it to work as a laser-class-1 device. Interfacing is through a high-speed CSI-2 data interface.

The IRS238xC operates from an optimized in-built voltage supply unit, and it can self-boot as it has a full SPI master memory interface. Among the new features available on the sensor are, coded modulation and enhanced configuration flexibility. This allows the device to perform flexibly and robustly in multi-camera scenarios and similar use-cases.

The time of flight technology from Infineon works with stability, as high assembly yields prove, and this is a great boon for camera module manufacturers, as the IRS238xC not only simplifies calibration efforts, it also simplifies the camera module design. In short, IRS238xC combines the benefits of reliability, cost, size, functionality, and power consumption, making it indispensable for mobile 3-D sensing applications in all kinds of ambient light conditions.

For instance, the IRS238xC has the smallest module size giving 224 x 172 pixels, each of size 14 µm and with their own individual micro-lens. The suppression of background illumination or SBI provides each pixel with a 20-time gain in dynamic expansion against strong sunlight, but at minimum power consumption. The robust high-volume assembly of the device and its low calibration efforts offer an easy design and low system bill of materials for the designer.

IRS238xC offers time-of-flight technology for directly measuring the amplitude and depth of information in every pixel. It does this using a single modulated infrared light source that the chip emits to the whole scenery. The TOF imager captures the reflected light. The unit measures the phase difference between the emitted and the reflected light along with their amplitude values, thereby calculating the distance information and producing a grayscale picture of the entire scene all in one sweep.

Infineon provides algorithms that feature unique multiple benefits compared to other depth sensing technologies such as stereovision or structured light.

Raspberry Pi and Traffic Lights

Although we come across traffic lights almost every time we step out of our homes, we rarely stop to think about how they work. However, Gunnar Pelpman has done just that, and he has put the hugely popular single board computer, Raspberry Pi to good use. While most of the tutorials introduce turning on and off LEDs, he has prepared a somewhat more complex tutorial, one that teaches how to program traffic lights. Moreover, he has done this with the Raspberry Pi (RBPi) running the Windows 10 IoT Core.

Traffic Lights may look very complicated installations, but they are rather simple in operation. They mostly comprise a controller, the signal head, and the detection mechanism. The controller acts as the brains behind the installation and controls the information required to light up the lights through their various sequences. Depending on location and time of the day, traffic signals run under a variety of modes, of which two are the fixed time mode and the vehicle actuation mode.

Under the fixed time mode, the traffic signal will repeatedly display the three colors in fixed cycles, regardless of the traffic conditions. Although adequate in areas with heavy traffic congestion, this mode is very wasteful for a side road with light traffic—if for some cycles there are no waiting vehicles, the time could be more efficiently allocated to a busier approach.

The second most common mode of operation of the traffic signal is the vehicle actuation. As its name suggests, the traffic signal adjusts the cycle time according to the demands of vehicles on all approaches.

Sensors, installed in the carriageway or above the signal heads, register the demands of the traffic. After processing these demands, the controller allocates the cycle time accordingly. However, the controller has a preset minimum and maximum cycle time, and it cannot violate them.

The hardware for the project could not be simpler. Gunnar has used three LEDs—red, orange, and green—to represent the three in a traffic light. The LEDs have an appropriate resistor in series for current limiting, and three ports of the RBPi drive them on and off. The rest of the project is the software, for which Gunnar uses the UWP application.

According to Gunnar, there are two options for writing UWP applications—the first a blank UWP application and the second a background application for IoT—depending on your requirement. The blank UWP is good for trying things out as a start, as, at a later point of time, you can build a User Interface for your application.

After creating the project with the blank UWP application, Gunnar added a reference to Windows IoT Extensions for the UWP. Next, he opened the file MainPage.xaml and added his own code, which begins with a test for the wiring. He uses the init() function to initialize the GPIO pins and stop() to turn all LEDs off. Then the code turns on all LEDs for 10 seconds to signal everything is working fine.

According to Gunnar, the primitive code mimics the traffic lights. He uses a separate code for the cycling of the traffic lights, and another for blinking them on and off. He uses the play() function for running ten cycles of the traffic light.

Sensors, IoT, and Medical Health

Increasingly, people are looking for preventive care outside of a hospital setting. Medical providers, startups, and Fortune 500 technology companies are all trying out new products and devices for revolutionizing medical care and streamlining costs. While this reduces hospital readmission rates, patients in remote areas are getting the care they need.

The evolving trend is towards remote patient monitoring, which is fundamentally improving the quality of care and patient outcomes right across the medical arena. Moreover, this is happening not only in clinics, onsite in hospitals, and at-home care, but also in remote areas, less populated areas, and in developing countries.

New technologies, new devices, and better results are driving healthcare nowadays. There are several examples of this. For instance, cardiovascular patients can have their heart rates and blood pressure monitored regularly from their homes, with the data feeding back to the cardiologists to allow them to track their patients better. Similarly, doctors are able to track respiration rates, oxygen and carbon dioxide levels, cardiac output, and body temperature of their patients.

Sensors are able to track the weight of patients who are suffering from obstructive heart diseases. This allows doctors to detect fluid retention, and decide if the patient requires hospitalization. Similarly, sensors can monitor the asthma medication of a child to be sure family members are offering it the right dosage. This can easily cut down the number of visits to the ER.

IoT can wirelessly link a range of sensors to measure the vitals in intensive care and emergency units. The first step consists of sensors that generate the data. When tools such as artificial intelligence combine with the sensors, it becomes easy to analyze large amounts of data, helping to improve clinical decisions.

Technological advances such as telemedicine offer advantages in rural hospitals that constantly need more physicians. This often includes remote specialist consultations, remote consultations, outsourced diagnostic analysis, and in-home monitoring. With telemedicine, remote physicians can offer consultations more quickly, making the process cheaper and more efficient compared to that offered by traditional healthcare appointments.

Sensor networks within practices and hospitals are helping to monitor patient adherence, thereby optimizing healthcare delivery. The healthcare industry is increasingly focusing on value-based, patient-centric care, and their outcomes.

This is where the new technology and devices are making a big impact. For instance, data sensors are helping health care providers detect potential issues in the prosthetic knee joint of a patient. The use of sensors allows them to summarize the pressure patterns and bilateral force distribution across the prosthetic. This is of immense help to the patient, warning them to the first indication of strain. The provider can monitor the situation 24/7 and adjust the treatment accordingly, while the payer saves additional expenses on prolonged treatment or recovery.

Integration of IoT features into medical devices has improved the quality and effectiveness of healthcare tremendously. It has made high-value care possible for those requiring constant supervision, those with chronic conditions, and for elderly patients. For instance, wearable medical devices now feature sensors, actuators, and communication methods with IoT features that allow continuous monitoring and transmitting of patient data to cloud based platforms.

Condition Monitoring with MEMS Accelerometers

In the market today, several condition-monitoring products are available as easy to deploy and highly integrated devices. A vast majority of them contain a microelectromechanical system or MEMS accelerometer as their core sensor. Not only are these economical, they also help in reducing the cost of deployment and ownership. In turn, this expands the facilities and the number of equipment benefitting from a condition monitoring program.

Compared to the legacy mechanical sensors, solid state MEMS accelerometers offer several attractive attributes. So far, their low bandwidth had restricted their application for use in condition monitoring. For instance, the noise performance of MEMS accelerometers was found to be not sufficiently low to cater to diagnostic applications requiring low noise levels over bandwidths beyond 10 KHz and over high frequency ranges.

The above situation is changing. Although still restricted of a few KHz of bandwidth, MEMS accelerometers with low noise are now available allowing the designers of condition monitoring products to use them in their new product concepts. This is because the use of MEMS brings several valuable and compelling advantages to the designer.

For instance, the size and weight of the MEMS accelerometers are of the utmost importance to airborne applications in health and usage monitoring systems, especially as they employ multiple sensors on a platform. MEMS devices in surface mount packages in a triaxial formation provide very high performance, while their footprints are only 6 x 6 mm, and weigh less than one gram. This shrinks the final package, while the interface of a typical MEMS device uses a single supply, which makes it easier to use in digital applications by saving on cost and weight of cables.

The triaxial arrangement is simpler with solid-state electronics and the small size of the transducers. They offer a small form factor enabling mounting on a printed circuit board, with the assembly hermetically sealed in housing suitable for fitting on a machine. MEMS devices require very low levels of power from single voltage supply and simple signal conditioning electronics, suitable for battery-powered wireless products.

Designers are able to use MEMS accelerometers in industrial settings for easy transition to digital interfaces now common. This is because the topology of the signal conditioning circuit for MEMS devices is common with both analog and digital output variations, allowing them to adapt the sensors to a wider variety of situations.

For instance, designers can load open protocols such as the Modbus RTU into a micro-controller, while using them with easily available RS-485 transceiver chips. Using surface mount chips, designers can lay out the complete solution for a transmitter with small footprint and fit them within relatively small board areas. They can insert these assemblies into packages, hermetically sealing them for supporting intrinsically safe characteristics or for conforming to environmental robustness certifications.

Although the current generation of MEMS devices can safely withstand 10,000 g of shock according to their specifications, in reality they can tolerate much higher levels without affecting sensitivity specifications. For instance, automatic test equipment can trim the sensitivity of a high-resolution sensor to remain stable over time and temperature to 0.01°C.

What is Raspberry Shake and BOOM?

The Earth below our feet is never still. Although we feel tremors only when they are substantially strong, such as during earthquakes, we can use the highly popular single board computer, the Raspberry Pi or RBPi to monitor what is happening just under us. This tiny seismograph, with an appropriate name of Raspberry Shake, is the smallest one can find.

Although small, Raspberry Shake can record earthquakes of all magnitudes, even those no human senses can detect. It is also capable of recording those huge destructive quakes that occur regularly around the globe. Raspberry Shake has a companion, the Raspberry Boom, and it detects infrasonic sounds given off when the Earth shakes.

During earthquakes, the Earth gives off low frequency sounds that are below the threshold of human hearing, but infrasound travels large distances. Other objects also generate such infrasound, including traffic, trains, airplanes, wind farms, weather systems, meteorites, and many more. The Raspberry Boom is the perfect companion to the Raspberry Shake for detecting and studying infrasound.

You only have to snap the Raspberry Shake and Boom on to an RBPi. The two together form a super capable Earth monitoring network. Plugging their output into a Station View then allows creating a powerful array for monitoring and discovering several fascinating events from around the world in real time.

The Raspberry Shake and Boom combine several technologies. The Raspberry Shake has a powerful processor on its main board, and a digitizer with built-in sensors including a geophone or super-sensitive motion sensor for detecting Earth movements. You can plug this Shake board right into the RBPi board, which will power it. The data from the Shake board uses miniSEED for processing, as this is a standard data format the industry uses. The output is also compatible with jAmaSeis, and that makes it easy to learn, monitor, and analyze.

Other advanced options on the Raspberry Shake allow experienced users to use it by programming their own protocols such as the IFTTT. They can also laser print their own enclosures. Other users, especially novices, can also use the Raspberry Shake easily, as the design of the devices allows them to be plug-n-play. Their design is professional and anyone can use them on home monitors.

Anyone can use the Raspberry Shake range. For instance, Educational facilities, consumer interest groups, professional institutes, makers, RBPi enthusiasts, citizen scientists, hobbyists, and more can simply plug into the network of Raspberry Shakes to start watching the planet vibrate.

It is very easy for any school or university to access data from any Raspberry Shake anywhere in the world, allowing them to monitor seismic activity of any active earthquake area as well as of quiet regions anywhere. They can view any event such as those demonstrated in IRIS Teachable Moments, including micro-tremors or other larger events.

The Raspberry Shakes are compatible with SWARM analytical software and jAmaSeis. This made the Oklahoma Geological Survey acquire 100 units for expanding their network. They rolled these units to schools and educational institutional facilities for raising the awareness and providing valuable educational tools.