Tag Archives: sensors

What are Radar Sensors?

Autonomous driving requires the car to have radar sensors as its ears. Originally, the military and avionics developed radar for their applications. Automobiles typically use millimeter wave radar, with a working frequency range of 30-300 GHz, and wavelengths nearer to centimeter waves. These millimeter wave radar offer advantages of photoelectric and microwave guidance to automobiles, because of their significant penetration power.

Automobile collision avoidance mainly uses 24 GHz and 77 GHz radar sensors. In comparison with centimeter wave radar, millimeter-wave radar offers a smaller size, higher spatial resolution, and easier integration. Compared to optical sensors, infrared, and lasers, millimeter wave radar has a significantly stronger ability to penetrate smoke, fog, and dust, along with a good anti-interference ability. Although the millimeter band radar is essential for autonomous driving, heavy rain can significantly reduce the performance of radar sensors, as it produces a large interference. 

Automobiles first used radar sensors in a research project about 40 years ago. Commercial vehicle projects started using radar sensors only in 1998. Initially, they were useful only for adaptive cruise control. Later, radar sensors have developed to provide collision warnings also.

Radar sensors are available in diverse types, and they have a wide range of applications. Automobile applications typically use them as FMCW or frequency-modulated continuous wave radars. FMCW radars measure the air travel time and frequency difference between the transmitted and received signals to provide indirect ranging.

The FMCW radar transmits a frequency-modulated continuous wave. The frequency of this wave changes with time, depending on another triangular wave. After reflection from the object, the echo received by the radar has the same nature of frequency as the emitted wave. However, there is a time difference, and this tiny time difference represents the target distance.

Another radar in common use is the CW Doppler radar sensor. These sensors use the principle of the Doppler effect for measuring the speed of targets at various distances. The radar transmits a microwave signal towards the target, analyzing the frequency change of the reflected signal. The difference between the two frequencies accurately represents the target’s speed relative to the vehicle.

Autonomous vehicles use radar sensors as their basic but critical technical accessories. The radar sensor helps the vehicle to sense objects surrounding it, such as other vehicles, trees, or pedestrians, and determine their relative positions. Then the car can use other sensors to take corresponding measures. Radar sensors provide warnings like front vehicle collisions and the initial adaptive cruise. Vehicles with autopilot radars require more advanced radar sensors such as LIDARs that offer significantly faster response speeds.

Autonomous vehicles must develop technologically. Autonomous driving basically requires an autonomous vehicle to quickly understand and perceive its surrounding environment. This requires the coordination of various sensors, allowing the car to see six directions and hear all. Reliable and decisive driving by an autonomous vehicle requires timely and accurate sensing of roads, other vehicles, pedestrians, and other objects around the vehicle.

Automotive electronics mainly uses radar sensors to avoid forward collisions, sideways collisions, backward collisions, automatic cruises, automatic start and stop, blind spot monitoring, pedestrian detection, and automatic driving of vehicles.

What is Moisture Sensing?

In agriculture, where plants require watering, people often use time-controlled watering methods. While this method irrigates plants in fixed time intervals, there is no way to assess whether there is an actual need for watering. Most often, this leads to either over-watering or under-watering. Depending on weather conditions, over-watering may cause harmful water-logging, while under-watering may lead to dry stress for plants. People often mitigate the amount of water flow by using a rain sensor or controlling the water delivery based on online weather information.

Using a sensor to sense the amount of moisture in the soil and control the watering works much better. Not only does the latter method allow optimal water supply to the plants, but it also substantially reduces water consumption. Threshold levels can be set using various strategies. Any experienced gardener can recognize the start of dry stress when they notice the plants wilting slightly, or when the leaf edges start rolling.

Excessive watering does not increase the moisture in the soil, rather, it results in saturation. By delaying watering for a while, the excess water usually drains off into the subsoil. Most gardeners set the lower threshold to about 60% of the saturation level. They observe the plants and the moisture trend during the early phases to adjust the threshold levels to allow an economical and optimal automatic watering. It is necessary to position the sensor properly in the soil near the root area. For drip irrigation, it is possible to achieve a good soil moisture cycle by placing the sensor somewhere where it is neither too far nor too close to the drip location.

For working with moisture sensors, it is necessary to consider sensor selection and integration. This is because moisture sensors have two functions in a watering system. The first is they provide information about the current status of the watering. The second is they help to economically use water as a resource. Many plants are intolerant to dry soil as they are to water-logging. Moreover, while there are numerous types of moisture sensors, they have different ways of working and their life spans vary widely.

The presence of moisture in the soil can have different definitions. There is the volumetric water content, which represents the amount of water in the total amount of soil. In natural soil, the maximum volumetric water content is about 50-60 % and represents the amount of water filling all the airspace in the soil. Organic materials and peat can hold more water.

The relative mass of water in the soil is its gravimetric water content. This is determined chiefly by weighing the soil sample before and after drying. As it requires a laboratory to do the measurement, this method is not suitable for continuous monitoring in the field.

A variety of principles of physical measurements form the basis of many types of electrical sensors for measuring soil moisture. The most inexpensive is the measurement of electrical conductivity. Next are low-frequency capacitive sensors. High-frequency capacitive sensors are more expensive. Then there are tensiometers that measure the soil moisture tension.

What are Floating Sensors?

Floating sensors support applications for environmental monitoring and agriculture. Designed by researchers from the University of Washington, floating sensors typically spread just like seeds of the dandelion plant do, when a drone drops them from a height. The sensors are battery-free devices, hovering over 100 meters. The sensors have electronics on board, including a capacitor for storing overnight charge, sensors, and a microcontroller for running the system. The entire structure resides in a flexible body.

The evolution of dandelions allows them to disperse their seeds further than a kilometer in the air. Although for valuable wireless sensors, it is not a good idea to drop them from great heights. However, the researchers did just that by creating a tiny device that can carry the sensor, with the wind blowing it at it tumbles towards the ground.

Just like the dandelion seeds do, the sensors too, float in the breeze. As the device is about 30 times heavier than a dandelion seed weighing one milligram is, it can travel only up to a distance of about 100 meters on a windy day. The researchers had to mimic the shape of the dandelion seeds as it was necessary to ensure that the device landed with its solar panels facing skywards.

The structure of dandelion seeds has a central point where little bristles stick out. These tend to slow down their fall. The researchers took a 2-D projection of the seed and used it to create the base design for the structure of their floating sensors. When they added more weight, the bristles started to bend inwards. The researchers then added a ring structure to make the bristles stiffer, and take up more area, allowing it to slow down the fall. The team tested more than 75 designs with various sizes and patterns using laser micro-machining.

The sensor can share data related to pressure, temperature, humidity, and light up to a distance of 60 meters. The researchers have added a capacitor to the design of their floating sensors, allowing it to store some charge for the night. As an experiment, the researchers used a drone to drop sensors from a height of 20 meters, sending the sensors sideways to about 100 meters towards a parking area.

According to the researchers, from an engineering point of view, imitating dandelion seeds allows for achieving some amazing capabilities. Although dandelion plants cannot move, they can disperse their seeds up to a kilometer away, provided the right conditions exist. The team has been trying for a similar achievement by automating the deployment of wireless sensors to create a network. Conventional methods of studying climate changes or monitoring the environment over really large geographic areas can be very expensive and time-consuming. Dandelion seeds and their dispersion methods provided the team with the necessary inspiration to create sensors that can disperse in the wind, and automate this process.

The team had to look at nature again to get good coverage over the area of interest. They mimicked the random process followed by plants to disperse their seeds. The researchers designed a large array of different structures to make them float for different periods.

Microwave Motion Sensor

For detection of motion and direction of motion, the most common sensor was the Passive Infrared sensor or PIR. The presence of a human radiates infrared rays, and the sensor detects this along with variations in infrared rays to sense motion. Now, Infineon offers a fully integrated microwave motion sensor that includes antennas in the package along with built-in detectors for motion and its direction. The BGT60LTR11AIP, from Infineon, does not need an external microcontroller, as it has a built-in state machine to enable its operation. When operating in the autonomous mode, the sensor can detect the presence of a human being at a distance of 7 m at low power consumption.

To use the BGT60LTR11AIP, one does not need any know-how in Radio Frequencies, radar signal processing, or antenna design. Therefore, this sensor brings radar technology to all. Moreover, the small-sized radar unit has special features that provide a compelling cost-effective, and smart replacement for the traditional PIR sensors, providing low power operation for battery-powered applications.

The BGT60LTR11AIP microwave motion detector system makes the traditional motion-sensing applications smarter. For instance, the motion detector is useful in applications like screen-based systems (tablets, notebooks, TVs), automated door openers, security systems including IP cameras, smart lighting systems, smart appliances like kitchen appliances and vacuum cleaners, smart building appliances like proximity sensors, occupancy sensors, and contact-less switches, and smart home devices like smart speakers, smoke detectors, and thermostats.

Infineon has designed the BGT60LTR11AIP sensor as a low-power Doppler radar sensor working in the 60 GHz ISM-band. The tiny 3.3 x 6.7 x 0.56 mm package has a transmitter and a receiver antenna built into the package. It also has the built-in direction of motion detector along with a built-in motion detector. It can operate in multiple modes of operation, including a completely autonomous mode. The user can adjust performance parameters like detection sensitivity, frequency of operation, and hold time. The PCB design of the sensor uses FR-4 material.

In the autonomous mode, the BGT60LTR11AIP can detect up to a range of 7 m while consuming less than 2 mW of power. For this mode of operation, the BGT60LTR11AIP uses minimum external circuitry like crystal, LDO, along with some passive resistors and capacitors, and a shield.

The user can extend the flexibility of the BGT60LTR11AIP by adding an M0 MCU. This improves the detection range up to 10 m in SPI mode. The addition of an MCU offers advanced capabilities through configuration and signal processing via the SPI mode.

The user can incorporate the BGT60LTR11AIP sensor into systems to wake them up when required and put them to sleep or in auto-lock condition when it detects no motion for a specified time period. It has the capability to trigger additional functionality when it detects motion or senses a change in the direction of motion.

The BGT60LTR11AIP can thus add smart power-saving for many devices. Also, as microwaves can operate through non-metallic materials, the sensor can be placed out of sight in the end product. Therefore, the BGT60LTR11AIP sensor enables smooth integration of radar technologies in systems of daily use.

Radar Sensors for Smart Homes Enable Energy Efficiency

With the increase in the application of smart homes, the number of connected devices is also growing. Although this is making the lives of users more convenient, it is also resulting in an increase in energy consumption. This is due to the devices being either permanently active or in standby mode, ready for use at all times, even when there is no one home. Now Infineon is offering their radar sensor, the XENSIV, to make smart homes become more energy-efficient.

By an estimate, at present, there are more than 200 million smart homes around the world. This number is forecast to exceed 500 million by the end of a few years in the future.

The use of digital devices with increasingly ingenious functionalities helps to make houses smarter. However, there is a flip side to this—the increase in energy consumption—despite most modern devices showing a trend of steadily decreasing standby power consumption. This is because most smart devices need power even when they are in standby mode, to be capable of reacting instantaneously to user input. On many occasions, it is not at all necessary for a device to run in standby mode, consuming energy, primarily when there is no one present.

The radar sensor from Infineon aims to solve this issue while meeting the requirements of both digitization and energy efficiency. Capable of operating in almost all smart home systems, radar sensors are highly sensitive devices. They can detect the presence of a person and whether a device needs to be ready. This action is similar to that of the screensaver that kicks-in in on the monitor of a personal computer, when there is no activity from the mouse or keyboard after a certain time but reactivates the monitor as soon as the mouse or keyboard detects a new input. The truly smart and energy-saving device from Infineon, operating at 60 GHz, performs a reliable detection of the absence or presence of a human.

Devices like smart speakers, thermostats, and digital assistants consume very little power when in their normal standby mode. However, their energy consumption can reduce still further if they are forced into a deep sleep mode, especially when no one is around. Doing this can save a few more watts of power.

Other devices like a TV, laptop, sound system, or the air-conditioner can consume several 100 Watts when they are on. Switching them off when no one is likely to use them soon, such as when no one is present at home, can therefore save a lot of energy.

The radar-based smart device continuously checks to sense if there is anyone present or is moving about. If it detects there is no one present, it can switch other devices to a deep-sleep mode or switch them off entirely, thereby helping to save energy. The radar module consumes only about 0.1 W, and this is significantly lower than the energy demands of many other devices, even when they are in their standby mode.

Smart Sensors from Sensirion

Sensirion is offering three smart sensors that make it easy for electronic system designers to incorporate them into their applications. These are the AMT4x Smart Gadget, the SCD30 Sensor Module, and the STC31 Thermal Conductivity Sensor for CO2.

As a simple circuit board for a reference design, the AMT4x Smart Gadget from Sensirion is a demonstration kit for the SHT4x temperature and humidity sensors. The gadget displays information for temperature and humidity on an LCD screen. The built-in BLE or Bluetooth Low Energy module allows communication with smartphones and other Bluetooth-enabled devices.

The kit for the Smart Gadget includes an SHT40 sensor for temperature and humidity, a liquid crystal display, a push button, a Bluetooth MCU module, batteries, and other supports. Sensirion also provides detailed resources for the hardware design and information for an app download.

The Smart Gadget offers designers a simple reference design along with a circuit board. They can use it for measuring temperature and humidity while displaying it on an LCD, The MyAmbiance app for iOS and Android phones enables remote access and export capabilities along with data logging.

To sense CO2, Sensirion is offering their SCD30 Sensor Module. SCD30 uses the NDIR sensor technology for sensing CO2. It also has an integrated humidity and temperature sensor. The sensor measures the humidity and temperature in the ambient atmosphere while monitoring and compensating for external heat sources, without using any additional components. The height of the sensor module is low, and this allows easy integration in systems for various applications. The SCD30 achieves high accuracy and superior stability with its dual-channel capability.

The SCD30 sensor, with its NDIR CO2 sensor technology, and integrated humidity and temperature sensor, offers outstanding stability owing to the compensation from long-term drifts provided by its dual-channel capability. The sensor has a small form factor of 35 x 23 x 7 mm. Its measurement range covers 400 to 10,000 ppm, with an accuracy of ±30 ppm +3%. Apart from measuring the absolute concentration of carbon dioxide, the sensor can also measure temperature and relative humidity.

Applications of the SCD30 sensor include IoT devices, Smart Homes, Air purifiers, Air conditioners, HVAC equipment, and demand-controlled ventilation systems.

Sensirion also offers the STC31, a thermal conductivity sensor for the detection and measurement of Carbon dioxide. The gas concentration sensor is chip-sized, offers 16-bit resolution for high range, and is accurate for high volume production CO2 measurement.

Sensirion has based the sensor on an innovative principle of thermal conductivity measurement, which results in long-term stability and superb repeatability. With a digital I2C interface, the STC31 sensor can directly interface with a microprocessor. Working from a voltage ranging from 2.7 to 5 VDC, and a 5 mA maximum current rating, the STC31 sensor operates ideally from batteries while delivering top performance at minimal power budgets.

The STC31 is RoHS and REACH compliant, and its measurement range covers 20 to +85 °C. At a measurement rate of 1 reading per minute, the sensor consumes only 15 µW of power. With a track record of above 15 years, the STC31 sensor is an industry-proven technology.

Sensors for Structural Health Monitoring

Public bridges and roads require their structural health to be monitored, and engineers use sensors for continuous measurement. To power these embedded sensors, they exploit several sources of ambient energy. This can include vibrational energy obtained from vehicular traffic, which can generate adequate power for sensor nodes that engineers have built into the infrastructure. Off-the-shelf devices make it easier for engineers to design structural monitoring devices. Many manufacturers now provide such sensors.

Drivers are rather well-acquainted with potholes on the bridges and roads on which they frequently travel. However, apart from the surface damage, there are more insidious structural damages that may be less obvious. One of them is stress corrosion cracks in structural components that may lead to a bridge collapse.

Therefore, engineers are rightly concerned about existing infrastructure developing similar defects. The rise in vehicular traffic over bridges and roads, often going beyond the original design specifications, together with rapid aging from the stress, can lead to their continual wear and tear and deterioration. Engineers use Structural Health Monitoring or SHM based on continuous monitoring of infrastructure. This is critical for identifying structures at risk.

Monitoring the system through wireless means is more practical, as this avoids the expenses of using wired system monitoring. Wireless monitoring also leads to the simpler placement of sensors within the existing infrastructure. Powering the wireless sensors with energy harvesting techniques further enables avoiding the cost and maintenance concerns related to using batteries and their periodic replacement.

Engineers use various ambient sources for powering the nodes of SHM wireless sensors. This includes vibrational, thermal, and solar sources. Ultimately, the optimum choice depends less on the technical requirements but rather on the logistics, cost, and maintenance requirements related to the target structure. For instance, noise barriers may be necessary for roads in urban areas with heavy traffic. These noise barriers may double as solar panels for energy harvesting.

Some situations may offer alternative sources of energy for powering sensors. These could be thermoelectric generators or TECs, which generate power based on the temperature differential across them. Such differentials often exist between the subgrade layers and the pavement surface of a road. Although using TECs in new constructions may be quite effective, retrofitting in existing roads may involve prohibitive costs.

Engineers often use a heavier tip mass to augment the mechanical loading of a piezoelectric device. Such loading helps to reduce the natural frequency of the device, bringing it closer to the predominant frequencies from the ambient vibrational energy source, enabling maximization of power generation.

In some cases, the ambient vibrational energy source may have frequencies well below the tunable range of the piezoelectric devices available. Engineers then turn to alternative low-frequency vibrational energy transducers like electromagnetic generators. The low-frequency vibrations cause a spring-mounted magnetic core to move through a coil, thereby converting the energy of vibrations to a current following Faraday’s law of induction.

Ambient-powered wireless sensors also require power conditioning and management. Power management circuits monitor the energy harvested, regulate the voltage applied to the load, and use the excess energy to charge external energy storage devices like a rechargeable battery or a supercapacitor.

 Important Sensors

Engineers use two important types of sensors—superstar sensors and workhorse sensors. The superstar sensors usually provide information in high-profile applications such as advanced driver assistance systems, and engineers update them regularly for improving their performance. On the other hand, the workhorse sensors are more reliable, providing consistent information on more common applications. These workhorse sensors are simple to use, and meet the necessary performance specifications at reasonable price tags.

For instance, sensors have been readily available for detecting particulate matter in a dusty environment. However, in recent times, governments have tightened their regulations and have changed the definition of the acceptable levels of particulate matter. Advancement in technology has led to the development of small commodity dust sensors capable of being incorporated into mobile devices. This makes it easier for air monitors, air conditioners, and air purifiers to detect airborne dust particles in all types of environments.

Sharp Microelectronics offers a compact optical dust sensor, the GP2Y1010AU0F. It consists of an infrared light-emitting diode and a phototransistor placed in a diagonal position within the device. The phototransistor picks up infrared light reflected by dust particles. As the system is based on optical sensing, the device is thin and compact with dimensions of 46 x30 x 17.6 mm. The sensor from Sharp Microelectronics is sensitive enough to detect very fine particles such as those in cigarette smoke.

Honeywell offers their LLE Series of sensors for sensing liquid levels. Their technology uses a phototransistor trigger. The sensor can detect the presence or absence of liquid and presents the output in digital format. The sensor uses an LED and a phototransistor that Honeywell has placed inside a plastic dome at the head of the device. In the absence of liquid, light from the LED reaches the phototransistor after total internal reflections from the dome. As liquid fills up, it covers the dome, changing the refractive index at the liquid-dome boundary. This prevents light from the LED from reflecting back to the phototransistor, instantaneously switching the output and indicating the presence of liquid.

Omron offers their digital differential pressure-type mass-flow sensor, the D6F-PH. The sensor has an I2C output and uses a mass-flow MEMS chip, a proprietary of Omron. The company has redesigned the internal flow path such that it produces a high-velocity low flow for an impedance sensor to produce differential pressure. Users can buy these sensors in three models—for measuring a specific pressure range while being calibrated for several types of gases.

Measurement Specialties offers their compression load cell, the FC22. This is a low-cost, high-performance, medium compression force sensor. The sensor offers normalized zero and span, and thermal compensation for changes in span and zero as the temperature changes. The sensor is based on the Microfused technology of Measurement Specialties. It uses several micromachined piezoresistive strain gauges made of silicon fuzed with high-temperature glass to a stainless-steel substrate. While competitive designs suffer from lead-die fatigue, the FC22 sensor does not and can measure the direct force with unlimited life cycle expectancy, while offering superior resolution, and high over-range capabilities.

Smart Batteries with Sensors

Quick-charging batteries are in vogue now. Consumers are demanding more compact, quick-charging, lightweight, and high-energy-density batteries for all types of electronic devices including high-efficiency vehicles. Whatever be the working conditions, even during a catastrophe, batteries must be safe. Of late, the Lithium-ion battery technology has gained traction among designers and engineers as it satisfies several demands of consumers, while at the same time being cost-efficient. However, with designers pushing the limits of Li-ion battery technology capabilities, several of these requirements are now conflicting with one another.

While charging and discharging a Li-ion battery, many changes take place in it, like in the mechanics of its internal components, in its electrochemistry, and its internal temperature. The dynamics of these changes also affect the pressure in its interface within the housing of the battery. Over time, these changes affect the performance of the battery, and in extreme cases, can lead to reactions that are potentially dangerous.

Battery designers are now moving towards smart batteries with built-in sensors. They are using piezoresistive force and pressure sensors for analyzing the effects charging and discharging have on the batteries in the long run. They are also embedding these sensors within the battery housing to help alert users to potential battery failures. Designers are using thin, flexible, piezoresistive sensors for capturing relative changes in pressure and force.

Piezoresistive sensors are made of semi-conductive material sandwiched between two thin, flexible polyester films. These are passive elements acting as force-sensitive resistors within an electrical circuit. With no force or pressure applied, the sensors show a high resistance, which drops when the sensor has a load. With respect to conductance, the response to a force is a linear one as long as the force is within the range of the sensor’s capabilities. Designers arrange a network of sensors in the form of a matrix.

When two surfaces press on the matrix sensor, it sends analog signals to the electronics, which converts it into a digital signal. The software displays this signal in real-time to offer the activity occurring across the sensing area. The user can thereby track the force, locate the region undergoing peak pressure, and identify the exact moment of pressure changes.

The matrix sensors offer several advantages. These include about 2000-16000 sensing nodes, element spacing as low as 0.64 mm, capable of measuring pressure up to 25,000 psi, temperature up to 200 °C, and scanning speeds up to 20 kHz.

Designers also use single-point piezoresistive force sensors for measuring force within a single sensing area. They integrate such sensors with the battery as they are thin and flexible, and they can also function as a feedback system for an operational amplifier circuit in the form of a voltage divider. Depending on the circuit design, the user can adjust the force range of the sensor by changing its drive voltage and the resistance of the feedback. This allows the user complete control over measuring parameters like maximum force range, and the measurement resolution within the range. As piezoresistive force sensors are passive devices with linear response, they do not require complicated electronics and work with minimum filtering.

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.