Scalable IoT Architecture for Monitoring IEQ Conditions in Public and Private Buildings
2. Related work
2.1. IEQ Monitoring Systems
2.2. Communication Technologies for IoT Applications
3. Scalable IoT Architecture for IEQ Systems
3.1. Architecture Overview
- Centralized configuration: The configuration of the whole IEQ monitoring system is centralized at the cloud. However, IEQ Concentrators hold the local configuration of a set of smart IEQ sensor nodes. This approach introduces higher flexibility for changing the configuration of the smart IEQ sensor nodes since it is not necessary to reprogram them. In addition, it is possible to check the integrity of the IEQ monitoring system before its operation. At powering-up time, smart IEQ sensor nodes send a message that includes their identifier to the closest IEQ Concentrator, requesting configuration. Upon reception of the configuration, smart IEQ sensor nodes self-configure accordingly. The configuration of every smart sensor includes several parameters including location, quantity of attached sensors, and the characteristics of all specific sensors connected.
- Variable sampling times: IEQ Concentrators use a local clock to interrogate IEQ sensor nodes accordingly. This clock is synchronized for all devices in the IEQ monitoring system (cloud and fog layers) by means of the NTP protocol, executed at the cloud. The proposed approach is adequate for sampling times in the range of minutes, which the authors consider adequate for IEQ monitoring systems since IEQ variables do not change abruptly. The IEQ Concentrators are responsible for sending MQTT messages to the smart IEQ sensors, indicating when they have to take the measures of the IEQ variables. Thus, upon reception of the corresponding MQTT topic, the smart IEQ sensor nodes take new measurements from the attached sensors and send the captured values to the next IEQ Concentrator by means of MQTT topics. This approach allows for synchronizing of the measures taken at different areas of the building, even when several IEQ Concentrators are in operation. In addition, it is possible to dynamically change the sampling time while the system is in operation, if necessary.
- Local collection of data: The IEQ concentrator collects the data for on-line and off-line analysis from the attached smart IEQ sensor nodes. These nodes hold the selected sensors for measuring the IEQ parameters. Collected data are stored locally at the IEQ concentrator, which is responsible for sending them periodically to the cloud, where they are stored and analyzed for different purposes. IEQ concentrators allow both on-line and off-line basic analysis of the captured data, by means of an HMI application. This application allows different operations such as plotting the data of selected sensors, the calculation of typical values such as maximum, minimum, and mean values and standard deviations, and the percentage of valid measurements of each node and sensor for a selected day or time period.
- Cloud services: IEQ concentrators act as gateways between fog and cloud services, by means of MQTT connectivity. Typically, the adoption of edge and fog paradigms allow dealing with the massive amounts of raw data of IoT applications. Cloud services allow for scaling the IEQ monitoring system to reach every corner of very large buildings or areas, such as a whole campus, centralizing all the information. This layer is composed by different services, e.g., the global time for all devices at the system, data storage for all devices, advanced data analytics and visualization, and usage recommendations for IEQ resources based on weather forecast and measured parameters, such as opening/closing the windows for better ventilation or switching off the heaters. Finally, these services are responsible for sending alarm messages to operators if the measured values are out of the specified bounds.
3.2. Communication Technologies
Message Model at the Edge/Fog Layer
- Configuration of smart IEQ sensor nodes: The configuration of one smart IEQ node is initiated at startup time, which requests its configuration by means of a topic, conf/ni, where i represents the node identifier number, fixed for every IEQ sensor node. Upon the reception of this topic, the IEQ concentrator sends the available configuration for that specific node. Smart IEQ sensor nodes have specific sensors attached in different layouts. So, the IEQ concentrator sends the configuration for a specific node by means of several published topics; the config/ni/nsens topic indicates the number of attached sensors, whereas the specific configuration for each sensor is sent by the config/ni/sj topic, which specifies the type of sensor attached to the pin j in the node i. These topics are received by the smart IEQ sensor nodes, which self-configure accordingly.
- Reset of one/all IEQ sensor nodes: Occasionally, several issues may induce operating problems at the IEQ monitoring system. For this reason, the authors designed a procedure for resetting one or all attached sensors. This operation is initiated by the IEQ concentrator when it detects one of these problems. The reset/ni topic, published by the concentrator, is received by one specific smart IEQ node, triggering the reset procedure. The reset/all topic was also included to simultaneously reset all connected smart IEQ nodes.
- Monitoring IEQ sensor nodes: The IEQ concentrator holds the local clock and is responsible for monitoring the IEQ variables periodically according to the specified configuration. The IEQ concentrator publishes the MQTT take/# topic to indicate to all smart IEQ sensors to take measures of all the attached sensors according to their configuration. This approach allows for simultaneously taking the measures at all distributed IEQ nodes. Since IEQ parameters change slowly, monitoring periods in the range of minutes may be adequate. Smart IEQ nodes send the IEQ values taken by publishing the corresponding values/ni topics, where i is the number identifier for every node. The IEQ concentrator subscribes to all the topics published by the connected smart IEQ sensor nodes.
3.3. Prototype of the IEQ Monitoring System
3.4. Power Consumption Analysis of the Smart IEQ Sensor Node
3.5. HMI Application
4. Validation of the Prototype
- In a staff office
- In a laboratory during several laboratory classes
- In a classroom during an exam
4.1. In a Staff Office
4.2. In a Laboratory during Several Laboratory Classes
4.3. In a Classroom during an Exam
5. Conclusions and Future Work
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|CO2||Less than 1000 ppm||ASHRAE|
|VOC||Less than 250 ppb||RESET Air|
|Temperature (1.2 m)||Between 23.3 and 27.8 °C||ASHRAE|
|Relative humidity||Less than 65%||ASHRAE|
|TCP/IP Layers||IoT Protocols|
|Data Link||IEEE802.11 (WiFi)|
|LM74||Temperature||Digital (SPI)||Texas Instruments|||
|SHT85||Temperature and humidity||Digital (I2C)||Sensirion|||
|CCS811||eCO2 and TVOC||Digital (I2C)||AMS|||
|Component||Unit Cost (€)|
|Raspberry Pi 3B+||30|
|Raspberry Pi Case||7|
|SD Card 32 GB||13|
|RPi Power adapter||10|
|TOTAL cost for IEC Concentrator||60|
|Smart IEC sensor nodes|
|Arduino MKR WiFi 1010||30|
|Battery 10,000 mAh||15|
|PCB and component assembly (including TMP37, LM74 and CSS811 sensors)||90|
|TOTAL cost for basic Smart IEC sensor node||135|
|CSS811 (CO2 and VTOC)||10|
|SHT85 (Temperature and relative humidity)||25|
|Operation State||Current [mA]|
|Run mode, no transmission||42|
|Deep sleep mode||30|
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Calvo, I.; Espin, A.; Gil-García, J.M.; Fernández Bustamante, P.; Barambones, O.; Apiñaniz, E. Scalable IoT Architecture for Monitoring IEQ Conditions in Public and Private Buildings. Energies 2022, 15, 2270. https://doi.org/10.3390/en15062270
Calvo I, Espin A, Gil-García JM, Fernández Bustamante P, Barambones O, Apiñaniz E. Scalable IoT Architecture for Monitoring IEQ Conditions in Public and Private Buildings. Energies. 2022; 15(6):2270. https://doi.org/10.3390/en15062270Chicago/Turabian Style
Calvo, Isidro, Aitana Espin, Jose Miguel Gil-García, Pablo Fernández Bustamante, Oscar Barambones, and Estibaliz Apiñaniz. 2022. "Scalable IoT Architecture for Monitoring IEQ Conditions in Public and Private Buildings" Energies 15, no. 6: 2270. https://doi.org/10.3390/en15062270