Two-to-One Trigger Mechanism for Event-Based Environmental Sensing
Environmental monitoring systems often operate continuously, measuring various parameters, including carbon dioxide levels (CO<sub>2</sub>), relative humidity (RH), temperature (T), and other factors that affect environmental conditions. Such systems are often referred to as smart system...
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MDPI AG
2025-06-01
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| author | Nursultan Daupayev Christian Engel Sören Hirsch |
| author_facet | Nursultan Daupayev Christian Engel Sören Hirsch |
| author_sort | Nursultan Daupayev |
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| description | Environmental monitoring systems often operate continuously, measuring various parameters, including carbon dioxide levels (CO<sub>2</sub>), relative humidity (RH), temperature (T), and other factors that affect environmental conditions. Such systems are often referred to as smart systems because they can autonomously monitor and respond to environmental conditions and can be integrated both indoors and outdoors to detect, for example, structural anomalies. However, these systems typically have high energy consumption, data overload, and large equipment sizes, which makes them difficult to install in constrained spaces. Therefore, three challenges remain unresolved: efficient energy use, accurate data measurement, and compact installation. To address these limitations, this study proposes a two-to-one threshold sampling approach, where the CO<sub>2</sub> measurement is activated when the specified <i>T</i> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>H</mi></mrow></semantics></math></inline-formula> change thresholds are exceeded. This event-driven method avoids redundant data collection, minimizes power consumption, and is suitable for resource-constrained embedded systems. The proposed approach was implemented on a low-power, small-form and self-made multivariate sensor based on the PIC16LF19156 microcontroller. In contrast, a commercial monitoring system and sensor modules based on the Arduino Uno were used for comparison. As a result, by activating only key points in the <i>T</i> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>H</mi></mrow></semantics></math></inline-formula> signals, the number of CO<sub>2</sub> measurements was significantly reduced without loss of essential signal characteristics. Signal reconstruction from the reduced points demonstrated high accuracy, with a mean absolute error (MAE) of 0.0089 and root mean squared error (RMSE) of 0.0117. Despite reducing the number of CO<sub>2</sub> measurements by approximately 41.9%, the essential characteristics of the signal were saved, highlighting the efficiency of the proposed approach. Despite its effectiveness in controlled conditions (in buildings, indoors), environmental factors such as the presence of people, ventilation systems, and room layout can significantly alter the dynamics of CO<sub>2</sub> concentrations, which may limit the implementation of this approach. Future studies will focus on the study of adaptive threshold mechanisms and context-dependent models that can adjust to changing conditions. This approach will expand the scope of application of the proposed two-to-one sampling technique in various practical situations. |
| format | Article |
| id | doaj-art-7beef41697894bb8906be98665a0b42f |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-7beef41697894bb8906be98665a0b42f2025-08-20T02:36:30ZengMDPI AGSensors1424-82202025-06-012513410710.3390/s25134107Two-to-One Trigger Mechanism for Event-Based Environmental SensingNursultan Daupayev0Christian Engel1Sören Hirsch2Department of Engineering, Brandenburg University of Applied Sciences, Magdeburger Str. 50, 14770 Brandenburg an der Havel, GermanyDepartment of Engineering, Brandenburg University of Applied Sciences, Magdeburger Str. 50, 14770 Brandenburg an der Havel, GermanyDepartment of Engineering, Brandenburg University of Applied Sciences, Magdeburger Str. 50, 14770 Brandenburg an der Havel, GermanyEnvironmental monitoring systems often operate continuously, measuring various parameters, including carbon dioxide levels (CO<sub>2</sub>), relative humidity (RH), temperature (T), and other factors that affect environmental conditions. Such systems are often referred to as smart systems because they can autonomously monitor and respond to environmental conditions and can be integrated both indoors and outdoors to detect, for example, structural anomalies. However, these systems typically have high energy consumption, data overload, and large equipment sizes, which makes them difficult to install in constrained spaces. Therefore, three challenges remain unresolved: efficient energy use, accurate data measurement, and compact installation. To address these limitations, this study proposes a two-to-one threshold sampling approach, where the CO<sub>2</sub> measurement is activated when the specified <i>T</i> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>H</mi></mrow></semantics></math></inline-formula> change thresholds are exceeded. This event-driven method avoids redundant data collection, minimizes power consumption, and is suitable for resource-constrained embedded systems. The proposed approach was implemented on a low-power, small-form and self-made multivariate sensor based on the PIC16LF19156 microcontroller. In contrast, a commercial monitoring system and sensor modules based on the Arduino Uno were used for comparison. As a result, by activating only key points in the <i>T</i> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>H</mi></mrow></semantics></math></inline-formula> signals, the number of CO<sub>2</sub> measurements was significantly reduced without loss of essential signal characteristics. Signal reconstruction from the reduced points demonstrated high accuracy, with a mean absolute error (MAE) of 0.0089 and root mean squared error (RMSE) of 0.0117. Despite reducing the number of CO<sub>2</sub> measurements by approximately 41.9%, the essential characteristics of the signal were saved, highlighting the efficiency of the proposed approach. Despite its effectiveness in controlled conditions (in buildings, indoors), environmental factors such as the presence of people, ventilation systems, and room layout can significantly alter the dynamics of CO<sub>2</sub> concentrations, which may limit the implementation of this approach. Future studies will focus on the study of adaptive threshold mechanisms and context-dependent models that can adjust to changing conditions. This approach will expand the scope of application of the proposed two-to-one sampling technique in various practical situations.https://www.mdpi.com/1424-8220/25/13/4107structural health monitoringmultivariate sensorsevent-driven activationdata reductionenergy efficiency |
| spellingShingle | Nursultan Daupayev Christian Engel Sören Hirsch Two-to-One Trigger Mechanism for Event-Based Environmental Sensing Sensors structural health monitoring multivariate sensors event-driven activation data reduction energy efficiency |
| title | Two-to-One Trigger Mechanism for Event-Based Environmental Sensing |
| title_full | Two-to-One Trigger Mechanism for Event-Based Environmental Sensing |
| title_fullStr | Two-to-One Trigger Mechanism for Event-Based Environmental Sensing |
| title_full_unstemmed | Two-to-One Trigger Mechanism for Event-Based Environmental Sensing |
| title_short | Two-to-One Trigger Mechanism for Event-Based Environmental Sensing |
| title_sort | two to one trigger mechanism for event based environmental sensing |
| topic | structural health monitoring multivariate sensors event-driven activation data reduction energy efficiency |
| url | https://www.mdpi.com/1424-8220/25/13/4107 |
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