A Multi-Use Case Scientific Sensor Node

2021 ◽  
Author(s):  
Valarie Hamilton ◽  
Andrew Moores
Keyword(s):  
Sensor Node ◽  
Ambient Noise ◽  
Smart Sensors ◽  
Design Criteria ◽  
Use Case ◽  
Long Duration ◽  
Data Files ◽  
Critical Structure

<p>Nanometrics' Pegasus digitizer is the basis for a scientific grade node and is the latest development in many years of designing and building reliable seismic instruments for the scientific and monitoring community. Coupled in a grab-and-go quick deploy package with a variety of sensors enables responses to many types of events and environmental measurements. These types of systems are not only for hazards, such as earthquakes and volcanoes, but can form the basis of better tools used for critical structure and microzonation studies using ambient noise.  Pegasus takes advantage of a complete ecosystem of software, making planning, deploying and data harvesting very simple and straightforward as well as providing a dataset that includes automatically generated metadata in the form of StationXML and standard miniSEED data files.  Pegasus design criteria was based on optimal SWaP (Size, Weight and Power) and makes it unique in short to long duration deployments without swapping of units in the field, while its broad sensor compatibility enables many types of measurements and is completely compatible with the advantages of Nanometrics smart sensors.</p>

scholarly journals Efficient Processing of Geospatial mHealth Data Using a Scalable Crowdsensing Platform

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3456
Author(s):  
Robin Kraft ◽  
Ferdinand Birk ◽  
Manfred Reichert ◽  
Aniruddha Deshpande ◽  
Winfried Schlee ◽  
...  
Keyword(s):  
Architectural Design ◽  
Environmental Data ◽  
Common Interest ◽  
Sensor Data ◽  
Smart Sensors ◽  
Use Case ◽  
Sound Levels ◽  
Efficient Processing ◽  
Interactive Map ◽  
Technical Solutions

Smart sensors and smartphones are becoming increasingly prevalent. Both can be used to gather environmental data (e.g., noise). Importantly, these devices can be connected to each other as well as to the Internet to collect large amounts of sensor data, which leads to many new opportunities. In particular, mobile crowdsensing techniques can be used to capture phenomena of common interest. Especially valuable insights can be gained if the collected data are additionally related to the time and place of the measurements. However, many technical solutions still use monolithic backends that are not capable of processing crowdsensing data in a flexible, efficient, and scalable manner. In this work, an architectural design was conceived with the goal to manage geospatial data in challenging crowdsensing healthcare scenarios. It will be shown how the proposed approach can be used to provide users with an interactive map of environmental noise, allowing tinnitus patients and other health-conscious people to avoid locations with harmful sound levels. Technically, the shown approach combines cloud-native applications with Big Data and stream processing concepts. In general, the presented architectural design shall serve as a foundation to implement practical and scalable crowdsensing platforms for various healthcare scenarios beyond the addressed use case.

scholarly journals Accurate Indoor Sound Level Measurement on a Low-Power and Low-Cost Wireless Sensor Node

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2351 ◽  
Author(s):  
Vladimir Risojević ◽  
Robert Rozman ◽  
Ratko Pilipović ◽  
Rok Češnovar ◽  
Patricio Bulić
Keyword(s):  
Low Power ◽  
Sensor Node ◽  
Ambient Noise ◽  
Ieee 802.15.4 ◽  
Low Cost ◽  
Sound Level ◽  
Wireless Sensor ◽  
Sound Level Meter ◽  
Hardware Platform ◽  
Level Meter

Wireless sensor networks can provide a cheap and flexible infrastructure to support the measurement of noise pollution. However, the processing of the gathered data is challenging to implement on resource-constrained nodes, because each node has its own limited power supply, low-performance and low-power micro-controller unit and other limited processing resources, as well as limited amount of memory. We propose a sensor node for monitoring of indoor ambient noise. The sensor node is based on a hardware platform with limited computational resources and utilizes several simplifications to approximate more complex and costly signal processing stage. Furthermore, to reduce the communication between the sensor node and a sink node, as well as the power consumed by the IEEE 802.15.4 (ZigBee) transceiver, we perform digital A-weighting filtering and non-calibrated calculation of the sound pressure level on the node. According to experimental results, the proposed sound level meter can accurately measure the noise levels of up to 100 dB, with the mean difference of less than 2 dB compared to Class 1 sound level meter. The proposed device can continuously monitor indoor noise for several days. Despite the limitations of the used hardware platform, the presented node is a promising low-cost and low-power solution for indoor ambient noise monitoring.

scholarly journals Accurate Indoor Sound Level Measurement on a Low-Power and Low-Cost Wireless Sensor Node

2018 ◽  
Author(s):  
Vladimir Risojević ◽  
Robert Rozman ◽  
Ratko Pilipović ◽  
Rok Češnovar ◽  
Patricio Bulic
Keyword(s):  
Low Power ◽  
Sensor Node ◽  
Ambient Noise ◽  
Ieee 802.15.4 ◽  
Low Cost ◽  
Sound Level ◽  
Wireless Sensor ◽  
Sound Level Meter ◽  
Hardware Platform ◽  
Level Meter

Wireless sensor networks can provide a cheap and flexible infrastructure to support the measurement of noise pollution. However, the processing of the gathered data is challenging to implement on resource-constrained nodes, because each node has its own limited power supply, low-performance and low-power micro-controller unit and other limited processing resources, as well as limited amount of memory. We propose a sensor node for monitoring of indoor ambient noise. The sensor node is based on a hardware platform with limited computational resources and utilizes a number of simplifications to approximate more complex and costly signal processing stage. Furthermore, to reduce the communication between the sensor node and a sink node, as well as the power consumed by the IEEE 802.15.4 (ZigBee) transceiver, we perform digital A-weighting filtering and non-calibrated calculation of the sound pressure level on the node. According to experimental results, the proposed sound level meter can accurately measure the noise levels of up to 100~dB, with the mean difference of less than 2~dB compared to Class 1 sound level meter. The proposed device can continuously monitor indoor noise for several days. Despite the limitations of the used hardware platform, the presented node is a promising low-cost and low-power solution for indoor ambient noise monitoring.

The LDE-Type Flare Occurrence (1969-1993)

1994 ◽  
Vol 144 ◽  
pp. 279-282
Author(s):  
A. Antalová
Keyword(s):  
Time Series ◽  
Fourier Analysis ◽  
Sunspot Cycle ◽  
List Type ◽  
Type Number ◽  
Solar Cycles ◽  
Type Iv ◽  
Long Duration ◽  
Cycle Maximum ◽  
Flare Index

AbstractThe occurrence of LDE-type flares in the last three cycles has been investigated. The Fourier analysis spectrum was calculated for the time series of the LDE-type flare occurrence during the 20-th, the 21-st and the rising part of the 22-nd cycle. LDE-type flares (Long Duration Events in SXR) are associated with the interplanetary protons (SEP and STIP as well), energized coronal archs and radio type IV emission. Generally, in all the cycles considered, LDE-type flares mainly originated during a 6-year interval of the respective cycle (2 years before and 4 years after the sunspot cycle maximum). The following significant periodicities were found:• in the 20-th cycle: 1.4, 2.1, 2.9, 4.0, 10.7 and 54.2 of month,• in the 21-st cycle: 1.2, 1.6, 2.8, 4.9, 7.8 and 44.5 of month,• in the 22-nd cycle, till March 1992: 1.4, 1.8, 2.4, 7.2, 8.7, 11.8 and 29.1 of month,• in all interval (1969-1992):a)the longer periodicities: 232.1, 121.1 (the dominant at 10.1 of year), 80.7, 61.9 and 25.6 of month,b)the shorter periodicities: 4.7, 5.0, 6.8, 7.9, 9.1, 15.8 and 20.4 of month.Fourier analysis of the LDE-type flare index (FI) yields significant peaks at 2.3 - 2.9 months and 4.2 - 4.9 months. These short periodicities correspond remarkably in the all three last solar cycles. The larger periodicities are different in respective cycles.

Spectraplot: A PC-based spectrum translation and display program

1988 ◽  
Vol 46 ◽  
pp. 918-919
Author(s):  
H. O. Colijn
Keyword(s):  
Low Cost ◽  
Transfer Program ◽  
File Transfer ◽  
Transfer Data ◽  
Error Checking ◽  
Data Files ◽  
The University

Many labs today wish to transfer data between their EDS systems and their existing PCs and minicomputers. Our lab has implemented SpectraPlot, a low- cost PC-based system to allow offline examination and plotting of spectra. We adopted this system in order to make more efficient use of our microscopes and EDS consoles, to provide hardcopy output for an older EDS system, and to allow students to access their data after leaving the university.As shown in Fig. 1, we have three EDS systems (one of which is located in another building) which can store data on 8 inch RT-11 floppy disks. We transfer data from these systems to a DEC MINC computer using “SneakerNet”, which consists of putting on a pair of sneakers and running down the hall. We then use the Hermit file transfer program to download the data files with error checking from the MINC to the PC.

Relation Between Level of Prefrontal Activity and Subject's Performance

1999 ◽  
Vol 13 (2) ◽  
pp. 117-125 ◽  
Author(s):  
Laurence Casini ◽  
Françoise Macar ◽  
Marie-Hélène Giard
Keyword(s):  
Brain Activity ◽  
Sensory Information ◽  
Practice Phase ◽  
Trained Subjects ◽  
Anagram Task ◽  
Economic Information ◽  
Long Duration ◽  
Level Of Activity ◽  
The Brain ◽  
Processing Mechanism

Abstract The experiment reported here was aimed at determining whether the level of brain activity can be related to performance in trained subjects. Two tasks were compared: a temporal and a linguistic task. An array of four letters appeared on a screen. In the temporal task, subjects had to decide whether the letters remained on the screen for a short or a long duration as learned in a practice phase. In the linguistic task, they had to determine whether the four letters could form a word or not (anagram task). These tasks allowed us to compare the level of brain activity obtained in correct and incorrect responses. The current density measures recorded over prefrontal areas showed a relationship between the performance and the level of activity in the temporal task only. The level of activity obtained with correct responses was lower than that obtained with incorrect responses. This suggests that a good temporal performance could be the result of an efficacious, but economic, information-processing mechanism in the brain. In addition, the absence of this relation in the anagram task results in the question of whether this relation is specific to the processing of sensory information only.

Effects of Fatigue on Cognitive Performance in Long-Duration Simulated Flight Missions

2020 ◽  
Vol 10 (2) ◽  
pp. 82-93
Author(s):  
Eduardo Rosa ◽  
Ola Eiken ◽  
Mikael Grönkvist ◽  
Roger Kölegård ◽  
Nicklas Dahlström ◽  
...  
Keyword(s):  
Executive Functions ◽  
Task Performance ◽  
Cognitive Performance ◽  
Cognitive Tasks ◽  
Fatigue Index ◽  
Fighter Aircraft ◽  
Long Duration ◽  
Metacognitive Accuracy

Abstract. Fighter pilots may be exposed to extended flight missions. Consequently, there is increasing concern about fatigue. We investigated the effects of fatigue and cognitive performance in a simulated 11-hr mission in the 39 Gripen fighter aircraft. Five cognitive tasks were used to assess cognitive performance. Fatigue was measured with the Samn–Perelli Fatigue Index. Results showed that performance in the non-executive task degraded after approximately 7 hr. Fatigue ratings showed a matching trend to the performance in this task. Performance in tasks taxing executive functions did not decline. We interpreted that fatigue can be overridden by increased attentional effort for executive tasks but not for non-executive components of cognition. Participants underestimated their performance and metacognitive accuracy was not influenced by fatigue.

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