Investigating Pathways to Minimize Sensor Power Usage for the Internet of Remote Things
The Internet of Remote Things (IoRT) offers an exciting landscape for the development and deployment of remote wireless sensing nodes (WSNs) which can gather useful environmental data. Low Power Wide Area Networks (LPWANs) provide an ideal network topology for enabling the IoRT, but due to the remot...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/21/8871 |
| _version_ | 1797631240540520448 |
|---|---|
| author | Tiana Cristina Majcan Solomon Ould Nick S. Bennett |
| author_facet | Tiana Cristina Majcan Solomon Ould Nick S. Bennett |
| author_sort | Tiana Cristina Majcan |
| collection | DOAJ |
| description | The Internet of Remote Things (IoRT) offers an exciting landscape for the development and deployment of remote wireless sensing nodes (WSNs) which can gather useful environmental data. Low Power Wide Area Networks (LPWANs) provide an ideal network topology for enabling the IoRT, but due to the remote location of these WSNs, the power and energy requirements for such systems must be accurately determined before deployment, as devices will be running on limited energy resources, such as long-life batteries or energy harvesting. Various sensor modules that are available on the consumer market are suitable for these applications; however, the exact power requirements and characteristics of the sensor are often not stated in datasheets, nor verified experimentally. This study details an experimental procedure where the energy requirements are measured for various sensor modules that are available for Arduino and other microcontroller units (MCUs). First, the static power consumption of continually powered sensors was measured. The impact of sensor warm-up time, associated with powering on the sensor and waiting for reliable measurements, is also explored. Finally, the opportunity to reduce power for sensors which have multiple outputs was investigated to see if there is any significant reduction in power consumption when obtaining readings from fewer outputs than all that are available. It was found that, generally, CO<sub>2</sub> and soil moisture sensors have a large power requirement when compared with temperature, humidity and pressure sensors. Limiting multiple sensor outputs was shown not to reduce power consumption. The warm-up time for analog sensors and digital sensors was generally negligible and in the order of 10–50 ms. However, one CO<sub>2</sub> sensor had a large overhead warm-up time of several seconds which added a significant energy burden. It was found that more, or as much, power could be consumed during warm-up as during the actual measurement phase. Finally, this study found disparity between power consumption values in datasheets and experimental measurements, which could have significant consequences in terms of battery life in the field. |
| first_indexed | 2024-03-11T11:21:01Z |
| format | Article |
| id | doaj.art-11668baa8a82420fbeebab218a760439 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T11:21:01Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-11668baa8a82420fbeebab218a7604392023-11-10T15:12:28ZengMDPI AGSensors1424-82202023-10-012321887110.3390/s23218871Investigating Pathways to Minimize Sensor Power Usage for the Internet of Remote ThingsTiana Cristina Majcan0Solomon Ould1Nick S. Bennett2Centre for Advanced Manufacturing, University of Technology Sydney, Broadway, Ultimo, Sydney, NSW 2007, AustraliaCentre for Advanced Manufacturing, University of Technology Sydney, Broadway, Ultimo, Sydney, NSW 2007, AustraliaCentre for Advanced Manufacturing, University of Technology Sydney, Broadway, Ultimo, Sydney, NSW 2007, AustraliaThe Internet of Remote Things (IoRT) offers an exciting landscape for the development and deployment of remote wireless sensing nodes (WSNs) which can gather useful environmental data. Low Power Wide Area Networks (LPWANs) provide an ideal network topology for enabling the IoRT, but due to the remote location of these WSNs, the power and energy requirements for such systems must be accurately determined before deployment, as devices will be running on limited energy resources, such as long-life batteries or energy harvesting. Various sensor modules that are available on the consumer market are suitable for these applications; however, the exact power requirements and characteristics of the sensor are often not stated in datasheets, nor verified experimentally. This study details an experimental procedure where the energy requirements are measured for various sensor modules that are available for Arduino and other microcontroller units (MCUs). First, the static power consumption of continually powered sensors was measured. The impact of sensor warm-up time, associated with powering on the sensor and waiting for reliable measurements, is also explored. Finally, the opportunity to reduce power for sensors which have multiple outputs was investigated to see if there is any significant reduction in power consumption when obtaining readings from fewer outputs than all that are available. It was found that, generally, CO<sub>2</sub> and soil moisture sensors have a large power requirement when compared with temperature, humidity and pressure sensors. Limiting multiple sensor outputs was shown not to reduce power consumption. The warm-up time for analog sensors and digital sensors was generally negligible and in the order of 10–50 ms. However, one CO<sub>2</sub> sensor had a large overhead warm-up time of several seconds which added a significant energy burden. It was found that more, or as much, power could be consumed during warm-up as during the actual measurement phase. Finally, this study found disparity between power consumption values in datasheets and experimental measurements, which could have significant consequences in terms of battery life in the field.https://www.mdpi.com/1424-8220/23/21/8871Internet of Remote Thingssensorlow power |
| spellingShingle | Tiana Cristina Majcan Solomon Ould Nick S. Bennett Investigating Pathways to Minimize Sensor Power Usage for the Internet of Remote Things Sensors Internet of Remote Things sensor low power |
| title | Investigating Pathways to Minimize Sensor Power Usage for the Internet of Remote Things |
| title_full | Investigating Pathways to Minimize Sensor Power Usage for the Internet of Remote Things |
| title_fullStr | Investigating Pathways to Minimize Sensor Power Usage for the Internet of Remote Things |
| title_full_unstemmed | Investigating Pathways to Minimize Sensor Power Usage for the Internet of Remote Things |
| title_short | Investigating Pathways to Minimize Sensor Power Usage for the Internet of Remote Things |
| title_sort | investigating pathways to minimize sensor power usage for the internet of remote things |
| topic | Internet of Remote Things sensor low power |
| url | https://www.mdpi.com/1424-8220/23/21/8871 |
| work_keys_str_mv | AT tianacristinamajcan investigatingpathwaystominimizesensorpowerusagefortheinternetofremotethings AT solomonould investigatingpathwaystominimizesensorpowerusagefortheinternetofremotethings AT nicksbennett investigatingpathwaystominimizesensorpowerusagefortheinternetofremotethings |