scholarly journals Integration and calibration of non-dispersive infrared (NDIR) CO<sub>2</sub> low-cost sensors and their operation in a sensor network covering Switzerland

2020 ◽  
Vol 13 (7) ◽  
pp. 3815-3834 ◽  
Author(s):  
Michael Müller ◽  
Peter Graf ◽  
Jonas Meyer ◽  
Anastasia Pentina ◽  
Dominik Brunner ◽  
...  
Keyword(s):  
Data Processing ◽  
Sensor Network ◽  
Low Cost ◽  
Significant Loss ◽  
Sensor Calibration ◽  
Data Filtering ◽  
Ambient Conditions ◽  
Term Operation ◽  
Reference Instrument

Abstract. More than 300 non-dispersive infrared (NDIR) CO2 low-cost sensors labelled as LP8 were integrated into sensor units and evaluated for the purpose of long-term operation in the Carbosense CO2 sensor network in Switzerland. Prior to deployment, all sensors were calibrated in a pressure and climate chamber and in ambient conditions co-located with a reference instrument. To investigate their long-term performance and to test different data processing strategies, 18 sensors were deployed at five locations equipped with a reference instrument after calibration. Their accuracy during 19 to 25 months deployment was between 8 and 12 ppm. This level of accuracy requires careful sensor calibration prior to deployment, continuous monitoring of the sensors, efficient data filtering, and a procedure to correct drifts and jumps in the sensor signal during operation. High relative humidity (> ∼85 %) impairs the LP8 measurements, and corresponding data filtering results in a significant loss during humid conditions. The LP8 sensors are not suitable for the detection of small regional gradients and long-term trends. However, with careful data processing, the sensors are able to resolve CO2 changes and differences with a magnitude larger than about 30 ppm. Thereby, the sensor can resolve the site-specific CO2 signal at most locations in Switzerland. A low-power network (LPN) using LoRaWAN allowed for reliable data transmission with low energy consumption and proved to be a key element of the Carbosense low-cost sensor network.

scholarly journals Integration and calibration of NDIR CO<sub>2</sub> low-cost sensors, and their operation in a sensor network covering Switzerland

2019 ◽  
Author(s):  
Michael Mueller ◽  
Peter Graf ◽  
Jonas Meyer ◽  
Anastasia Pentina ◽  
Brunner Dominik ◽  
...  
Keyword(s):  
Data Processing ◽  
Sensor Network ◽  
Low Cost ◽  
Significant Loss ◽  
Sensor Calibration ◽  
Data Filtering ◽  
Ambient Conditions ◽  
Term Operation ◽  
Reference Instrument

Abstract. More than 300 LP8 CO2 sensors were integrated into sensor units and evaluated for the purpose of long-term operation in the Carbosense CO2 sensor network in Switzerland. Prior to deployment, all sensors were calibrated in a pressure and climate chamber, and in ambient conditions co-located with a reference instrument. To investigate their long-term performance and to test different data processing strategies, 18 sensors were deployed at five locations equipped with a reference instrument after calibration. Their accuracy during 19 to 25 months deployment was between 8 to 12 ppm. This level of accuracy requires careful sensor calibration prior to deployment, continuous monitoring of the sensors, efficient data filtering, and a procedure to correct drifts and jumps in the sensor signal during operation. High relative humidity (> ∼85 %) impairs the LP8 measurements, and corresponding data filtering results in a significant loss during humid conditions. The LP8 sensors are not suitable for the detection of small regional gradients and long-term trends. However, with careful data processing, the sensors are able to resolve CO2 changes and differences with a magnitude larger than about 20 ppm. Thereby, the sensor can resolve the site-specific CO2 signal at most locations in Switzerland. A low power network (LPN) using LoRaWAN allowed reliable data transmission with low energy consumption, and proved to be a key element of the Carbosense low-cost sensor network.

License Renewal: Status of Long Term Operation in the U.S.

2008 ◽  
Author(s):  
Garry G. Young
Keyword(s):  
Public Opinion ◽  
Continuous Improvement ◽  
Renewal Process ◽  
Low Cost ◽  
Nuclear Plant ◽  
Plant Operation ◽  
Term Operation ◽  
License Renewal ◽  
The U.S

As of February 2008, the NRC has approved renewal of the operating licenses for 48 nuclear units and has applications under review for 15 more units. In addition, nuclear plant owners for at least 25 more units have announced plans to submit license renewal applications over the next few years. This brings the total of renewed licenses and announced plans for license renewal to over 80% of the 104 currently operating nuclear units in the U.S. This paper presents some of the factors that have made the U.S. license renewal process so successful. These factors include (1) the successful regulatory process and on-going continuous improvement of that process, (2) long-term safe plant operation trends, (3) stable low-cost generation of electricity, (4) high levels of plant reliability, and (5) improving public opinion trends.

Long-term structural monitoring of the damaged Basilica S. Maria di Collemaggio through a low-cost wireless sensor network

2015 ◽  
Vol 5 (5) ◽  
pp. 655-676 ◽  
Author(s):  
Francesco Potenza ◽  
Fabio Federici ◽  
Marco Lepidi ◽  
Vincenzo Gattulli ◽  
Fabio Graziosi ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Low Cost ◽  
Wireless Sensor ◽  
Structural Monitoring

scholarly journals Design of an ozone and nitrogen dioxide sensor unit and its long-term operation within a sensor network in the city of Zurich

2017 ◽  
Author(s):  
Michael Mueller ◽  
Jonas Meyer ◽  
Christoph Hueglin
Keyword(s):  
Air Quality ◽  
Sensor Network ◽  
Data Transfer ◽  
Low Cost ◽  
Effective Procedure ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Monitoring Networks ◽  
Term Operation ◽  
Diffusion Tubes

Abstract. This study focuses on the investigation and quantification of low-cost sensor performance in application fields such as the extension of traditional air quality monitoring networks or the replacement of diffusion tubes. For this, sensor units consisting of two boxes featuring NO2 and O3 low-cost sensors and wireless data transfer were engineered. The sensor units were initially operated at air quality monitoring sites for three months for performance analysis and initial calibration. Afterwards, they were relocated and operated within a sensor network consisting of six locations for more than one year. Our analyses show that the employed O3 and NO2 sensors can be accurate to 2–5 and 5–7 ppb, respectively, during the first three months of operation. This accuracy, however, could not be maintained during their operation within the sensor network related to changes in sensor behaviour. Hence, the low-cost sensors in our configuration do not reach the accuracy level of NO2 diffusion tubes. Tests in the laboratory revealed that changes in relative humidity can impact the signal of the employed NO2 sensors similarly as changes in ambient NO2 concentration. All the employed low-cost sensors need to be individually calibrated. Best performance of NO2 sensors is achieved when the calibration models include also time dependent parameters accounting for changes in sensor response over time. Accordingly, an effective procedure for continuous data control and correction is essential for obtaining meaningful data. It is demonstrated that linking the measurements from low-cost sensors to the high quality measurements from routine air quality monitoring stations is an effective procedure for both tasks provided that time periods can be identified when pollutant concentrations can be accurately predicted at sensor locations.

scholarly journals A Protocol for The Effective Utilization of Energy in Wireless Sensor Network

2018 ◽  
Vol 7 (3.3) ◽  
pp. 93 ◽  
Author(s):  
Santosh Anand ◽  
Akarsha RR
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Low Cost ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life ◽  
Effective Utilization ◽  
Multiple Paths

Energy utilization is an important aspect in any Wireless Sensor Network .The data transmission from various components connected over real-time networks consumes more energy in Wireless Sensor Network. Mainly the task of any network engineer lies in performing an energy efficient, so to reserve the nonrenewable energy supply to sensor nodes. The research convey out effective utilization of energy in wireless sensor networks. It is important to comprise long-term and low-cost monitoring in different WSN application. The network algorithms separated mainly in two parts, first to generate multiple paths and second to switch paths from generated list of paths .Which is implemented as multi-hop-communication so that the battery life of the sensor node may live for long term and low cost of monitoring, which achieve the high lifetime of WSN. 

scholarly journals A High-Resolution Open Source Platform for Building Envelope Thermal Performance Assessment Using a Wireless Sensor Network

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1755 ◽  
Author(s):  
Romwald Lihakanga ◽  
Yuan Ding ◽  
Gabriela M. Medero ◽  
Samuel Chapman ◽  
George Goussetis
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Low Cost ◽  
Weather Conditions ◽  
Building Envelope ◽  
Wireless Sensor ◽  
Variation Analysis ◽  
Heat Flows

This paper presents an in-situ wireless sensor network (WSN) for building envelope thermal transmission analysis. The WSN is able to track heat flows in various weather conditions in real-time. The developed system focuses on long-term in-situ building material variation analysis, which cannot be readily achieved using current approaches, especially when the number of measurement hotspots is large. This paper describes the implementation of the proposed system using the heat flow method enabled through an adaptable and low-cost wireless network, validated via a laboratory experiment.

scholarly journals Mobile sensor network noise reduction and recalibration using a Bayesian network

2016 ◽  
Vol 9 (2) ◽  
pp. 347-357 ◽  
Author(s):  
Y. Xiang ◽  
Y. Tang ◽  
W. Zhu
Keyword(s):  
Air Quality ◽  
Bayesian Network ◽  
Sensor Network ◽  
Real World ◽  
Low Cost ◽  
Ground Truth ◽  
Bayesian Belief Network ◽  
Sensor Calibration ◽  
Belief Network ◽  
Network Applications

Abstract. People are becoming increasingly interested in mobile air quality sensor network applications. By eliminating the inaccuracies caused by spatial and temporal heterogeneity of pollutant distributions, this method shows great potential for atmospheric research. However, systems based on low-cost air quality sensors often suffer from sensor noise and drift. For the sensing systems to operate stably and reliably in real-world applications, those problems must be addressed. In this work, we exploit the correlation of different types of sensors caused by cross sensitivity to help identify and correct the outlier readings. By employing a Bayesian network based system, we are able to recover the erroneous readings and recalibrate the drifted sensors simultaneously. Our method improves upon the state-of-art Bayesian belief network techniques by incorporating the virtual evidence and adjusting the sensor calibration functions recursively.Specifically, we have (1) designed a system based on the Bayesian belief network to detect and recover the abnormal readings, (2) developed methods to update the sensor calibration functions infield without requirement of ground truth, and (3) extended the Bayesian network with virtual evidence for infield sensor recalibration. To validate our technique, we have tested our technique with metal oxide sensors measuring NO2, CO, and O3 in a real-world deployment. Compared with the existing Bayesian belief network techniques, results based on our experiment setup demonstrate that our system can reduce error by 34.1 % and recover 4 times more data on average.

scholarly journals Application of permeable reactive barrier in groundwater remediation

2019 ◽  
Vol 136 ◽  
pp. 06021
Author(s):  
Qianfeng He ◽  
Shihui Si ◽  
Jun Yang ◽  
Xiaoyu Tu
Keyword(s):  
Groundwater Remediation ◽  
Low Cost ◽  
Structure Type ◽  
Permeable Reactive Barrier ◽  
Term Operation ◽  
Reactive Barrier ◽  
External Power ◽  
Remediation Design

As a new in-situ remediation of groundwater, compared with the traditional “pump and treat” technology, the permeable reactive barrier (PRB) has the advantages of low cost, no external power, the small disturbance to groundwater, small secondary pollution and long-term operation, this paper introduces the basic concept of PRB, technical principle, structure type, the principle of active materials selection and mechanisms of remediation, design and installation factors, it provides ideas for further research and application of PRB technology in groundwater remediation projects in China.

scholarly journals Design of an ozone and nitrogen dioxide sensor unit and its long-term operation within a sensor network in the city of Zurich

2017 ◽  
Vol 10 (10) ◽  
pp. 3783-3799 ◽  
Author(s):  
Michael Mueller ◽  
Jonas Meyer ◽  
Christoph Hueglin
Keyword(s):  
Air Quality ◽  
Sensor Network ◽  
Low Cost ◽  
Effective Procedure ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Monitoring Networks ◽  
Term Operation ◽  
Diffusion Tubes ◽  
Over Time

Abstract. This study focuses on the investigation and quantification of low-cost sensor performance in application fields such as the extension of traditional air quality monitoring networks or the replacement of diffusion tubes. For this, sensor units consisting of two boxes featuring NO2 and O3 low-cost sensors and wireless data transfer were engineered. The sensor units were initially operated at air quality monitoring sites for 3 months for performance analysis and initial calibration. Afterwards, they were relocated and operated within a sensor network consisting of six locations for more than 1 year. Our analyses show that the employed O3 and NO2 sensors can be accurate to 2–5 and 5–7 ppb, respectively, during the first 3 months of operation. This accuracy, however, could not be maintained during their operation within the sensor network related to changes in sensor behaviour. For most of the O3 sensors a decrease in sensitivity was encountered over time, clearly impacting the data quality. The NO2 low-cost sensors in our configuration exhibited better performance but did not reach the accuracy level of NO2 diffusion tubes (∼ 2 ppb for uncorrected 14-day average concentrations). Tests in the laboratory revealed that changes in relative humidity can impact the signal of the employed NO2 sensors similarly to changes in ambient NO2 concentration. All the employed low-cost sensors need to be individually calibrated. Best performance of NO2 sensors is achieved when the calibration models also include time-dependent parameters accounting for changes in sensor response over time. Accordingly, an effective procedure for continuous data control and correction is essential for obtaining meaningful data. It is demonstrated that linking the measurements from low-cost sensors to the high-quality measurements from routine air quality monitoring stations is an effective procedure for both tasks provided that time periods can be identified when pollutant concentrations can be accurately predicted at sensor locations.

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