In the past few years, the general interest in connected home, smart devices and appliances has risen significantly. New concepts like the Internet of Things have inspired new applications and research areas for sensors and gathering data from them. One important application that makes use of these new technologies is monitoring indoor air quality, which according to Directive 2010/31/EU of the European Parliament and of the Council, can “reduce mortality, morbidity, and health care costs”. In this context, we propose a solution for wireless monitoring of indoor air quality parameters including temperature, humidity, CO2 and TVOC levels using a low-power ARM Cortex-M micro-controller, an IEEE 802.15.4 sub-GHz transceiver and temperature, humidity and gas sensors and observing the changes in overall power consumption by implementing an adaptive transmit power technique.
On the 19th of May 2010, the European Parliament and Council have adopted Directive 2010/31/EU on the energy performance of buildings which among others, sets out the inspection rates for heating and air conditioning systems, guidelines for issuing the energy performance certificate, using renewable energy for heating and cooling and the adoption of national plans for increasing the number of nearly zero-energy buildings. Furthermore, on the 30th of November 2016, a new Directive was adopted amending Directive 2010/31/EU to include indoor air quality considerations. Poor indoor climate is, according to the European Parliament and Council, a cause for high mortality and morbidity.
Further on, we will present a possible solution to monitor indoor climate parameters including temperature, humidity, CO2 and TVOC levels as part of a low-power, low-rate, sub-GHz wireless network. To keep the power consumption to a minimum, we have used the Andustria codename “Hydrogen” development board designed specifically for low-power wireless communication. The board features the latest generation of an Arm Cortex-M4-based microprocessor from STMicroelectronics, namely the STM32L462RE which provides a good cost/performance ratio. The wireless communication is done using the Microchip AT86RF212B sub-GHz IEEE 802.15.4 low-power transceiver using the 868 MHz European ISM band. On the sensors side, the board features the Sensirion SHT21 temperature and humidity sensor and the ams CCS811 CO2 and TVOC sensor.
This type of application is a perfect scenario to test an adaptive transmit power technique to lower the overall power consumption of the wireless sensors.
Released on the market in 2015, the ams CCS811 CO2 and TVOC sensor integrates a metal oxide gas sensor with a micro-controller sub-system which enables indoor air quality monitoring, ease of design, extended battery life and reduced system cost for smartphones, wearables and connected home devices. It is based on ams’s unique Micro-hotplate technology which enables a highly reliable solution for gas sensors, very fast cycle times and a significant reduction in average power consumption compared with traditional metal oxide gas sensors.
CCS811 supports a standard I2C digital interface compatible with application processors and provides a highly integrated solution. Compared to using separate gas sensor and micro-controller chips, which typically require two or more additional components, the CCS811 can save on the device’s bill of materials (BOM) and up to 60 percent on the board footprint.
The measurements of relative humidity and temperature taken by the Sensirion SHT21 allows the system to adjust the digital output of the CCS811 by compensating for changes in the ambient environment.
To validate this solution, we have performed several tests including signal quality, signal strength and power consumption in different operating modes. The results show that the wireless sensor node based on the STM32L462RE, the AT86RF212B, the SHT21 and the CCS811 is a reliable solution for indoor air quality monitoring and by using adaptive transmit power, the overall consumption of the wireless sensor can be significantly reduced.
The IEEE 802.15.4 standard for low-rate wireless communication provides the flexibility in implementation required by custom applications like air quality monitoring. With support for various operating frequency ranges, it is the basis for most of the commercial and industrial wireless protocols available on the market.
We have implemented the mandatory features of this standard in the wireless indoor air quality application like scanning an operating channel, device association and disassociation, resetting, starting and maintaining a PAN and data transfer.
The requirements for a wireless network which monitors indoor air quality are not so restrictive:
- Sampling time – indoor air quality parameters are parameters that vary slowly with time so a sample acquisition interval of one minute is more than enough.
- Data rates – to keep the radio as less time possible deactivated, we have chosen the maximum data rate of 250 kbps. Lower data rates increase the transmission range, but in these kinds of applications, the range between two wireless sensors, or between a wireless sensor and the PAN coordinator is just a few meters.
- Power consumption – the application should be optimized to obtain the lowest power consumption possible. The wireless sensor nodes will be likely to run on batteries, so changing them frequently is not acceptable.
The CO2 sensor measurement range should cover the known indoor CO2 level ranges in terms of health concerns, found in the table below.
|< 400||Normal background concentration in outdoor air|
|400 – 1000||Concentrations typical of occupied indoor spaces with good air exchange|
|1000 – 2000||Complaints of drowsiness and poor air|
|2000 – 5000||Headaches, sleepiness and stagnant, stale, stuffy air. Poor concentration, loss of attention, increased heart rate and slight nausea may also be present|
|5000||Workplace exposure limit in most jurisdictions|
|> 40000||Exposure may lead to serious oxygen deprivation resulting in permanent brain damage, coma, even death|
As mentioned above, the controllers and the wireless components of the control loops are implemented in two Andustria Hydrogen boards. Andustria designed these boards having in mind the features and requirements needed for a wireless low-power control loop: latest generation of Arm-based micro-controllers, best in class power consumption, IEEE 802.15.4 radio and power amplifier and precise crystals and oscillators. The board also features one CO2 sensor and one temperature and humidity sensor which can be used in wireless indoor air quality applications.
By using the radio transceiver’s configurable power level, ranging from -25 to +11 dBm with a 1 dBm step, we could implement an adaptive transmit power algorithm to optimize the overall power consumption of the development board.
The power switching logic of the algorithm is quite simple: we decrease the power of the transceiver by 1 dBm if the RSSI level of the data frame received by the concentrator is above -83 dBm. The RSSI level of the received data frame is sent back to the field device in the enhanced acknowledgment frame sent by the PAN coordinator according to IEEE 802.15.4-2015. The ETSI EN 300 220 standard states that if the noise on a specific channel is above the sensitivity level of the transceiver minus 15 dBm, the channel is considered busy. Having the sensitivity of the transceiver of -98 dBm for O-QPSK modulation, we have set the CCA and adaptive power threshold to -83 dBm. The signal quality of frames with RSSI below -83 dBm is considered poor.
The indoor tests were performed in an apartment with the layout below. The total length of the apartment is 8 meters and the width 12 meters. We have mapped the RSSI levels throughout the apartment and color-coded the values as displayed in the figure below. Red (0xFF0000) was assigned to RSSI level -83 dBm and green (0x00FF00) was assigned to RSSI level -11 dBm, the maximum level achieved with this transceiver. The PAN coordinator is marked on the heat map with a black circle. First, we have set the transceiver power to maximum allowed by the ETSI standard: 14 dBm. The result of the RSSI level are show in the figure below.
We can see how the signal strength deteriorates as we move away from the PAN coordinator, with a RSSI of -23.6 dBm in the same room as the coordinator, and a RSSI of -67 dBm at the other side of the apartment. Next, we configured the transceiver to use the adaptive transmit power algorithm. In this case, the transceiver set the power to the minimum supported: -25 dBm. The results of the RSSI mapping in this case, is found in the figure below.
The effective transmit power in this case is around 5 dBm considering the gain of +30 dBm of the power amplifier. Even though we are using the minimum power setting of the transceiver, the signal strength of the data frames is above -79 dBm. The current consumption decreases in this case from 80 mA to around 60 mA, a 25 % decrease.
The full study about using adaptive transmit power in wireless indoor air quality has been submitted and accepted by the ICSTCC 2019 IEEE conference which will be held in Sinaia, Romania between the 9th and 11th of October 2019.
Conference webpage: http://icstcc2019.cs.upt.ro/