Air quality monitoring is at a crossroads. Traditional solutions, mostly the government sponsored monitoring stations, are large and expensive, and they usually analyze limited samples of air. Meanwhile, home and industrial air monitoring systems have long used incumbent gas sensing technologies for both environmental quality monitoring and leak detection.
However, these gas sensors have a relatively large footprint and typically consume a lot of power. They also lack the processing capabilities, connectivity, and security required for upgrades to perform the self-diagnosis and reporting routines that are fundamental to modern Internet of Things (IoT) and Industrial IoT (IIoT) applications.
To address these issues, highly integrated and flexible gas sensor solutions are emerging from vendors such as Cypress Semiconductor, Gas Sensing Solutions, IDT, Renesas, and Sensirion. These bring higher integration, processing power, security, and connectivity, and promise more accurate measurements to detect environmental changes at homes, buildings, cars, hospitals, and factories.
This article will introduce some recent examples and will show how they address the needs of designers using pre-calibrated designs and pre-compiled firmware. It will also look at how calibration and memory features facilitate different sensor configurations with the help of reference designs and hardware kits.
What to look for in gas sensors for IoT
Advances in microelectromechanical systems (MEMS) have become a fundamental enabler of miniature, low-cost gas sensors. As MEMS technology improves, so too do the sensors’ accuracy and reliability. Along with fast response time, these are vital characteristics that determine a gas sensor’s ability to monitor the environment.
However, while the underlying gas sensing technology is important, they are not the sole determinant of a sensor’s performance. Instead, improvements in calibration capabilities provide designers with choices regarding the gas type, concentration range, and cost. The firmware improvements also go hand-in-hand with calibration features to help designers quickly integrate gas sensors into a variety of IoT applications.
Also, gas sensors on a single chip can be quickly integrated into air quality monitoring IoT designs using pre-calibrated sensing devices with pre-compiled firmware. These compact sensors are electrically calibrated with gas to ensure consistency from lot to lot. Moreover, the built-in non-volatile memory (NVM) in the sensor device stores the configuration and provides space for other data.
Besides pre-calibration, pre-compiled firmware further bolsters integration and accuracy, while significantly lowering the power consumption of gas sensors. The pre-compiled firmware also simplifies the overall development work, allowing designers to add new sensing capabilities without changing the hardware, while allowing system updates after deployment.
Pre-calibrated gas sensors
Take the example of IDT’s ZMOD4510IA1R gas sensor module that can quantify concentrations as low as 20 parts per billion (ppb). It’s optimized for the detection of trace atmospheric gases such as nitrogen oxides (NOx) and ozone (O3), two major causes of unhealthy outdoor air quality. The digital gas sensor is designed to monitor outdoor air quality according to the Air Quality Index (AQI) of the US Environmental Protection Agency (EPA). The sensor module has dimensions of 3.0 mm x 3.0 mm x 0.7 millimeters (mm) and comprises a gas sensing element and a signal conditioning IC (Figure 1).
Figure 1: The ZMOD4510IA1R gas sensor module employs algorithms to calculate the concentrations of outdoor gases. (Image source: IDT)
In the ZMOD4510IA1R, the sensing element consists of a heater element on a silicon-based MEMS structure and a metal-oxide (MOx) chemiresistor. The signal conditioning IC controls the sensor temperature and measures the MOx conductivity, which is a function of the gas concentration.
Besides calibration features, the ZMOD4510IA1R, based on proven MOx material, is highly resistant to siloxanes for reliability in harsh environments. For faster prototyping and development, it is supported by the ZMOD4510-EVK-HC gas sensor evaluation kit that allows the gas sensor module to be tested and evaluated via a bi-directional USB connection to a Windows® PC. A microcontroller-based module on the EVK controls the I²C communication interface to show the measured output of ozone and nitrogen oxides (Figure 2).
Figure 2: The ZMOD4510-EVK lets designers quickly evaluate the ZMOD4510 gas sensor using its built-in evaluation software. (Image source: Digi-Key Electronics)
IDT’s HS300x series of humidity and temperature sensors also features integrated calibration and temperature-compensation logic to provide fully corrected relative humidity (RH) and temperature values via standard I2C output. RH is the ratio of the partial pressure of water vapor to the equilibrium vapor pressure of water at a given temperature.
No user calibration of the output data is required, and the measured data is internally corrected and compensated for accurate operation over a wide range of temperature and humidity levels. The HS3001, HS3002, HS3003, and HS3004 MEMS sensors measure 3 x 2.41 x 0.8 mm and differ only in terms of accuracy of relative humidity and temperature measurements.
Cloud-based air monitoring
Designers can use gas sensors for logging air quality either by locally processing the data or by developing insight over time using a cloud-based platform over an IP connection. Here, hardware kits facilitate secure cloud connectivity and monitoring control through a dashboard.
For instance, the YSAECLOUD2 AE-Cloud2 kit from Renesas is a reference design built around the company’s Synergy S5D9 microcontrollers. It allows developers to connect devices such as the ZMOD4510IA1R gas sensor and HS3001 humidity sensor to cloud services via W-Fi, cellular, and other communication channels. The IoT kit also allows developers to visualize the sensor data on a dashboard in real time.
There are many alternatives available to developers needing to monitor indoor and outdoor air quality using cloud-based platforms. Digi-Key’s own Next-Gen Smart Air Quality Monitoring
cloud-enabled gas sensor platform combines Cypress Semiconductor’s PSoC 6 microcontrollers with gas and dust sensors from Sensirion (Figure 3). The PSoC 6 microcontrollers provide programmable peripherals to interface with any Sensirion sensor.
Figure 3: Shown is an air quality monitoring design for smart homes and buildings that sends data to the cloud through Wi-Fi links for presentation on a dashboard. (Image source: Digi-Key Electronics)
It’s important to note that most IoT nodes monitoring air quality—both indoor and outdoor—are energy constrained, often running off a battery. For these applications, the PSoC 6 extends the battery life due to its low power consumption. It is based on a dual-core Arm® Cortex®-M architecture built on a 40 nanometer (nm) process technology. The active power consumption is 22 μA/MHz for the M4 core, and 15 μA/MHz for the M0+ core. Additionally, the microcontroller supports secure boot, secure firmware updates, and hardware-accelerated cryptography for gas sensors in smart home and industrial environments, where data security and user privacy are always a concern.
PSoC 6 microcontrollers, along with gas sensing solutions from Sensirion, can help create applications for air purifiers, demand-controlled ventilation, and other indoor air quality monitoring applications. The connected monitoring devices can precisely control the environment by quickly responding to environmental feedback.
For example, take Sensirion’s SGP30 gas sensor, which combines multiple metal-oxide sensing elements, or pixels, on a single chip to measure both total volatile organic compounds (TVOC) and a CO2 equivalent signal (CO2eq). VOCs originate from new products and building materials such as carpets, furniture, paints, and solvents; tVOC refers to the total concentration of VOCs present in the air and is a quick way to assess indoor air quality.
The SGP30 can measure tVOC and CO2eq on a common membrane in a tiny package measuring 2.45 x 2.45 x 0.9 mm. Furthermore, unlike traditional gas sensors that lose stability and accuracy after a few months due to chemical compounds called siloxanes, the sensing elements in this multi-gas sensor are resistant to this type of contamination. This feature lowers drift to ensure long-term stability.
The sensing elements in the SGP30 gas sensor are made of a heated film of MOx nanoparticles. Sensirion has also embedded the other sensor components—heater and electrodes—within the chip to shrink the sensor footprint (Figure 4).
Figure 4: The SGP30 multi-gas sensor integrates four sensing elements, or pixels, into a single chip that features a temperature-controlled microplate and an I2C interface. (Image source: Sensirion)
To further raise the bar on integration, Sensirion has combined the SGP30 gas sensor with its SHTC1 humidity and temperature sensor to create a sensor combo module, the SVM30. Along with multiple sensing elements, it includes analog and digital signal processing, an analog-to-digital converter (ADC), calibration and data memory, and a digital communication interface supporting I2C standard mode.
Gas sensing speed
Sensing speed is another stumbling block when it comes to the rapidly changing CO2 levels in breath analysis and other real-time air monitoring applications. There is a need for gas sensors to significantly increase the sampling rate, especially for battery-powered indoor air quality sensors.
Gas Sensing Solutions has built the SprintIR-WF-20 gas sensor around indium antimonide LED technology and optical designs. As such, it avoids both moving parts (MEMS) and heated filaments (Figure 5). It captures 20 readings per second and comes with an optional flow-through adapter. Additionally, the SprintIR-WF-20 features three measurement ranges: 0 – 5%, 0 – 20% and 0 – 100% CO2 concentrations. Its accuracy is ±70 ppm (+5% of reading).
Figure 5: The SprintIR-WF-20 CO2 sensor is available with options to support either flow-through or diffusion structures. (Image source: Digi-Key Electronics)
The sensor communicates via a simple UART interface with a variety of wireless IoT networks such as Zigbee, LoRaWAN, Sigfox, and EnOcean. At 35 milliwatts (mW), the SprintIR-WF-20 needs far less power than typical non-disruptive infrared (NDIR) CO2 sensors; it runs off 3.25 to 5.5 volts and draws an average current of under 15 milliamps (mA) (100 mA, peak). These figures make the SprintIR-WF-20 suitable for battery-powered devices, such as wearables. The new firmware changes further improve battery life and boost CO2 sensing accuracy.
The gas sensor comes with an evaluation kit, the EVKITSWF-20, so all designers have to do is connect the CO2 sensor to a computer via a USB stick and start logging the sensor data. The USB stick contains the self-installing evaluation software. It’s worth mentioning that auto-calibration works for most air quality monitoring applications, though the evaluation kit allows developers to zero-calibrate for specific environments.
Designers of gas sensing devices for IoT and IIoT devices and systems are moving away from traditional, large, standalone designs. As they do so, they need to look for gas sensing solutions that allow them to improve accuracy, reliability and response time, and lower cost and power consumption; all while fully leveraging the capabilities of the IoT and cloud-based data gathering and analysis platforms. Other core features to watch for are interface design, sensing speed, and concentration range
As shown, there are many solutions available that not only meet designers’ needs, but also simplify the integration of these enhanced sensing capabilities in small form factors that are a must for battery-operated devices. They also include calibration capabilities and updatable firmware that are critical for the efficient configuration—and reconfiguration—of air quality monitoring designs. Using these gas sensors, coupled with cloud connectivity, designers can work within highly supportive hardware and software ecosystems to cater to current and future IoT and IIoT design requirements.