scholarly journals Investigation of the Spatio-Temporal Behaviour of Submarine Groundwater Discharge Using a Low-Cost Multi-Sensor-Platform

2021 ◽  
Vol 9 (8) ◽  
pp. 802
Author(s):  
Christoph Tholen ◽  
Iain Parnum ◽  
Robin Rofallski ◽  
Lars Nolle ◽  
Oliver Zielinski
Keyword(s):  
Spatial Distribution ◽  
Submarine Groundwater Discharge ◽  
Minimum Distance ◽  
Low Cost ◽  
Environmental Parameters ◽  
Environmental Sensors ◽  
Temporal Behaviour ◽  
Sensor Platform ◽  
Data Points ◽  
Spatio Temporal

Submarine groundwater discharge (SGD) is an important pathway of nutrients into coastal areas. During the last decades, interest of researchers in SGDs has grown continuously. However, methods applied for SGD research usually focus on the aquifer or on the mixing processes on larger scales. The distribution of discharged water within the water column is not well investigated. Small remotely operated vehicles (ROV) equipped with environmental sensors can be used to investigate the spatial distribution of environmental parameters in the water column. Herein, a low-cost multi-sensor platform designed to investigate the spatial distribution of water quality properties is presented. The platform is based on an off-the-shelf underwater vehicle carrying various environmental sensors and a short-baseline localisation system. This contribution presents the results of SGD investigations in the area of Woodman Point (Western Australia). Various potential SGD plumes were detected using a skiff equipped with a recreational echo sounder. It was demonstrated that this inexpensive equipment could be used to detect and investigate SGDs in coastal areas. In addition, the low-cost multi-sensor platform was deployed to investigate the spatial distribution of environmental parameters including temperature (T), electric conductivity (EC), dissolved oxygen (DO), oxidation-reduction potential (ORP), pH, and dissolved organic matter fluorescence (FDOM). Three ROV surveys were conducted from different skiff locations. Analyses of the spatial distribution of the environmental parameters allowed the identification of nine potential SGD plumes. At the same locations, plumes were identified during the sonar surveys. In addition, fuzzy logic was used for the fusion of salinity, DO, and FDOM readings in order to enhance SGD detection capability of the designed multi-sensor system. The fuzzy logic approach identified 293 data points as potential within a SGD plume. Average minimum-distance between these points and the identified SGD plumes was 0.5 m and 0.42 m smaller than the minimum-distance average of the remaining data points of survey one and three respectively. It was shown that low-cost ROVs, equipped with environmental sensors, could be an important tool for the investigation of the spatio-temporal behaviour of SGD sites. This method allows continuous mapping of environmental parameters with a high spatial and temporal resolution. However, to obtain deeper insights into the influence of SGDs on the nearshore areas, this method should be combined with other well-established methods for SGD investigation, such as pore water sampling, remote sensing, or groundwater monitoring.

scholarly journals Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3617 ◽  
Author(s):  
Hoochang Lee ◽  
Jiseock Kang ◽  
Sungjung Kim ◽  
Yunseok Im ◽  
Seungsung Yoo ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Low Cost ◽  
Sensor Nodes ◽  
Lookup Table ◽  
Calibration Model ◽  
Statistical Parameters ◽  
Sensor Platform ◽  
Calibration Algorithm ◽  
Term Evaluation ◽  
Spatio Temporal

Low-cost light scattering particulate matter (PM) sensors have been widely researched and deployed in order to overcome the limitations of low spatio-temporal resolution of government-operated beta attenuation monitor (BAM). However, the accuracy of low-cost sensors has been questioned, thus impeding their wide adoption in practice. To evaluate the accuracy of low-cost PM sensors in the field, a multi-sensor platform has been developed and co-located with BAM in Dongjak-gu, Seoul, Korea from 15 January 2019 to 4 September 2019. In this paper, a sample variation of low-cost sensors has been analyzed while using three commercial low-cost PM sensors. Influences on PM sensor by environmental conditions, such as humidity, temperature, and ambient light, have also been described. Based on this information, we developed a novel combined calibration algorithm, which selectively applies multiple calibration models and statistically reduces residuals, while using a prebuilt parameter lookup table where each cell records statistical parameters of each calibration model at current input parameters. As our proposed framework significantly improves the accuracy of the low-cost PM sensors (e.g., RMSE: 23.94 → 4.70 μ g/m 3 ) and increases the correlation (e.g., R 2 : 0.41 → 0.89), this calibration model can be transferred to all sensor nodes through the sensor network.

scholarly journals Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3319
Author(s):  
Stuart A. Bagley ◽  
Jonathan A. Atkinson ◽  
Henry Hunt ◽  
Michael H. Wilson ◽  
Tony P. Pridmore ◽  
...  
Keyword(s):  
High Throughput ◽  
Low Cost ◽  
Time Lapse ◽  
Plant Phenotyping ◽  
Environmental Sensors ◽  
Controlled Conditions ◽  
Sensor Platform ◽  
High Throughput Phenotyping ◽  
Controlled Environments ◽  
Time Lapse Imaging

High-throughput plant phenotyping in controlled environments (growth chambers and glasshouses) is often delivered via large, expensive installations, leading to limited access and the increased relevance of “affordable phenotyping” solutions. We present two robot vectors for automated plant phenotyping under controlled conditions. Using 3D-printed components and readily-available hardware and electronic components, these designs are inexpensive, flexible and easily modified to multiple tasks. We present a design for a thermal imaging robot for high-precision time-lapse imaging of canopies and a Plate Imager for high-throughput phenotyping of roots and shoots of plants grown on media plates. Phenotyping in controlled conditions requires multi-position spatial and temporal monitoring of environmental conditions. We also present a low-cost sensor platform for environmental monitoring based on inexpensive sensors, microcontrollers and internet-of-things (IoT) protocols.

scholarly journals Measurement of spatial and temporal fine sediment dynamics in a small river

2012 ◽  
Vol 16 (5) ◽  
pp. 1501-1515 ◽  
Author(s):  
Y. Schindler Wildhaber ◽  
C. Michel ◽  
P. Burkhardt-Holm ◽  
D. Bänninger ◽  
C. Alewell
Keyword(s):  
Spatial Distribution ◽  
Water Level ◽  
Low Cost ◽  
Spatial Dynamics ◽  
Fine Sediment ◽  
Sediment Dynamics ◽  
Published Data ◽  
Temporal And Spatial Distribution ◽  
Temporal Behaviour ◽  
Temporal And Spatial

Abstract. Empirical measurements on fine sediment dynamics and fine sediment infiltration and accumulation have been conducted worldwide, but it is difficult to compare the results because the applied methods differ widely. We compared common methods to capture temporal and spatial dynamics of suspended sediment (SS), fine sediment infiltration and accumulation and tested them for their suitability in a small, canalized river of the Swiss Plateau. Measurement suitability was assessed by data comparison, relation to hydrological data and in the context of previously published data. SS concentration and load were assessed by optical backscatter (OBS) sensors and SS samplers. The former exhibit a better temporal resolution, but were associated with calibration problems. Due to the relatively low cost and easy mounting of SS samplers, they can provide a higher spatial distribution in the river's cross section. The latter resulted in a better correlation between sediment infiltration and SS load assessed by SS samplers than SS concentrations measured with OBS sensors. Sediment infiltration baskets and bedload traps capture the temporal and spatial distribution of fine sediment infiltration. Data obtained by both methods were positively correlated with water level and SS. In contrast, accumulation baskets do not assess the temporal behaviour of fine sediment, but the net accumulation over a certain time period. Less fine sediment accumulated in upwelling zones and within areas of higher mean water level due to scouring of fine sediments. Even though SS and sediment infiltration assessed with the bedload traps increased from up- to downstream, less fine sediment accumulated downstream. This is probably also attributable to more scouring downstream.

scholarly journals Biomechanics of Trail Running Performance: Quantification of Spatio-Temporal Parameters by Using Low Cost Sensors in Ecological Conditions

2021 ◽  
Vol 11 (5) ◽  
pp. 2093
Author(s):  
Noé Perrotin ◽  
Nicolas Gardan ◽  
Arnaud Lesprillier ◽  
Clément Le Goff ◽  
Jean-Marc Seigneur ◽  
...  
Keyword(s):  
Heart Rate ◽  
Low Cost ◽  
Step Length ◽  
Measurement Unit ◽  
Ecological Conditions ◽  
Sports Science ◽  
Ground Contact Time ◽  
Spatio Temporal ◽  
Performance Results ◽  
Trail Running

The recent popularity of trail running and the use of portable sensors capable of measuring many performance results have led to the growth of new fields in sports science experimentation. Trail running is a challenging sport; it usually involves running uphill, which is physically demanding and therefore requires adaptation to the running style. The main objectives of this study were initially to use three “low-cost” sensors. These low-cost sensors can be acquired by most sports practitioners or trainers. In the second step, measurements were taken in ecological conditions orderly to expose the runners to a real trail course. Furthermore, to combine the collected data to analyze the most efficient running techniques according to the typology of the terrain were taken, as well on the whole trail circuit of less than 10km. The three sensors used were (i) a Stryd sensor (Stryd Inc. Boulder CO, USA) based on an inertial measurement unit (IMU), 6 axes (3-axis gyroscope, 3-axis accelerometer) fixed on the top of the runner’s shoe, (ii) a Global Positioning System (GPS) watch and (iii) a heart belt. Twenty-eight trail runners (25 men, 3 women: average age 36 ± 8 years; height: 175.4 ± 7.2 cm; weight: 68.7 ± 8.7 kg) of different levels completed in a single race over a 8.5 km course with 490 m of positive elevation gain. This was performed with different types of terrain uphill (UH), downhill (DH), and road sections (R) at their competitive race pace. On these sections of the course, cadence (SF), step length (SL), ground contact time (GCT), flight time (FT), vertical oscillation (VO), leg stiffness (Kleg), and power (P) were measured with the Stryd. Heart rate, speed, ascent, and descent speed were measured by the heart rate belt and the GPS watch. This study showed that on a ≤10 km trail course the criteria for obtaining a better time on the loop, determined in the test, was consistency in the effort. In a high percentage of climbs (>30%), two running techniques stand out: (i) maintaining a high SF and a short SL and (ii) decreasing the SF but increasing the SL. In addition, it has been shown that in steep (>28%) and technical descents, the average SF of the runners was higher. This happened when their SL was shorter in lower steep and technically challenging descents.

scholarly journals Wearable Sensors for Human Environmental Exposure in Urban Settings

2021 ◽  
Author(s):  
Carolin Helbig ◽  
Maximilian Ueberham ◽  
Anna Maria Becker ◽  
Heike Marquart ◽  
Uwe Schlink
Keyword(s):  
Acoustic Noise ◽  
Wearable Sensors ◽  
Environmental Parameters ◽  
Urban Structure ◽  
Protective Behavior ◽  
Urban Settings ◽  
Current Trends ◽  
Spatio Temporal ◽  
Smart Technologies ◽  
Study Designs

AbstractGlobal population growth, urbanization, and climate change worsen the immediate environment of many individuals. Elevated concentrations of air pollutants, higher levels of acoustic noise, and more heat days, as well as increasingly complex mixtures of pollutants pose health risks for urban inhabitants. There is a growing awareness of the need to record personal environmental conditions (“the human exposome”) and to study options and implications of adaptive and protective behavior of individuals. The vast progress in smart technologies created wearable sensors that record environmental as well as spatio-temporal data while accompanying a person. Wearable sensing has two aspects: firstly, the exposure of an individual is recorded, and secondly, individuals act as explorers of the urban area. A literature review was undertaken using scientific literature databases with the objective to illustrate the state-of-the-art of person-based environmental sensing in urban settings. We give an overview of the study designs, highlight and compare limitations as well as results, and present the results of a keyword analysis. We identify current trends in the field, suggest possible future advancements, and lay out take-home messages for the readers. There is a trend towards studies that involve various environmental parameters and it is becoming increasingly important to identify and quantify the influence of various conditions (e.g., weather, urban structure, travel mode) on people’s exposure.

scholarly journals Spatio-temporal distribution patterns of Plutella xylostella (Lepidoptera: Plutellidae) in a fine-scale agricultural landscape based on geostatistical analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jian-Yu Li ◽  
Yan-Ting Chen ◽  
Meng-Zhu Shi ◽  
Jian-Wei Li ◽  
Rui-Bin Xu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Plutella Xylostella ◽  
Agricultural Landscape ◽  
Seasonal Pattern ◽  
Distribution Patterns ◽  
Geostatistical Analysis ◽  
Distribution Model ◽  
Detailed Knowledge ◽  
Fine Scale ◽  
Spatio Temporal

AbstractA detailed knowledge on the spatial distribution of pests is crucial for predicting population outbreaks or developing control strategies and sustainable management plans. The diamondback moth, Plutella xylostella, is one of the most destructive pests of cruciferous crops worldwide. Despite the abundant research on the species’s ecology, little is known about the spatio-temporal pattern of P. xylostella in an agricultural landscape. Therefore, in this study, the spatial distribution of P. xylostella was characterized to assess the effect of landscape elements in a fine-scale agricultural landscape by geostatistical analysis. The P. xylostella adults captured by pheromone-baited traps showed a seasonal pattern of population fluctuation from October 2015 to September 2017, with a marked peak in spring, suggesting that mild temperatures, 15–25 °C, are favorable for P. xylostella. Geostatistics (GS) correlograms fitted with spherical and Gaussian models showed an aggregated distribution in 21 of the 47 cases interpolation contour maps. This result highlighted that spatial distribution of P. xylostella was not limited to the Brassica vegetable field, but presence was the highest there. Nevertheless, population aggregations also showed a seasonal variation associated with the growing stage of host plants. GS model analysis showed higher abundances in cruciferous fields than in any other patches of the landscape, indicating a strong host plant dependency. We demonstrate that Brassica vegetables distribution and growth stage, have dominant impacts on the spatial distribution of P. xylostella in a fine-scale landscape. This work clarified the spatio-temporal dynamic and distribution patterns of P. xylostella in an agricultural landscape, and the distribution model developed by geostatistical analysis can provide a scientific basis for precise targeting and localized control of P. xylostella.

scholarly journals Micro-Landscape Dependent Changes in Arbuscular Mycorrhizal Fungal Community Structure

2021 ◽  
Vol 11 (11) ◽  
pp. 5297
Author(s):  
Stavros D. Veresoglou ◽  
Leonie Grünfeld ◽  
Magkdi Mola
Keyword(s):  
Community Structure ◽  
Mycorrhizal Fungi ◽  
Root Colonization ◽  
Environmental Parameters ◽  
Arbuscular Mycorrhizal ◽  
Fungal Community Structure ◽  
High Connectivity ◽  
Spatio Temporal ◽  
Arbuscular Mycorrhizal Fungal ◽  
Colonization Rates

The roots of most plants host diverse assemblages of arbuscular mycorrhizal fungi (AMF), which benefit the plant hosts in diverse ways. Even though we understand that such AMF assemblages are non-random, we do not fully appreciate whether and how environmental settings can make them more or less predictable in time and space. Here we present results from three controlled experiments, where we manipulated two environmental parameters, habitat connectance and habitat quality, to address the degree to which plant roots in archipelagos of high connectivity and invariable habitats are colonized with (i) less diverse and (ii) easier to predict AMF assemblages. We observed no differences in diversity across our manipulations. We show, however, that mixing habitats and varying connectivity render AMF assemblages less predictable, which we could only detect within and not between our experimental units. We also demonstrate that none of our manipulations favoured any specific AMF taxa. We present here evidence that the community structure of AMF is less responsive to spatio-temporal manipulations than root colonization rates which is a facet of the symbiosis which we currently poorly understand.

scholarly journals A Person-to-Person and Person-to-Place COVID-19 Contact Tracing System Based on OGC IndoorGML

2020 ◽  
Vol 10 (1) ◽  
pp. 2 ◽  
Author(s):  
Soroush Ojagh ◽  
Sara Saeedi ◽  
Steve H. L. Liang
Keyword(s):  
Data Model ◽  
Low Cost ◽  
Large Body ◽  
Contact Tracing ◽  
Trajectory Data ◽  
Sequential Order ◽  
Human Contact ◽  
Wide Availability ◽  
Data Points ◽  
The Impact

With the wide availability of low-cost proximity sensors, a large body of research focuses on digital person-to-person contact tracing applications that use proximity sensors. In most contact tracing applications, the impact of SARS-CoV-2 spread through touching contaminated surfaces in enclosed places is overlooked. This study is focused on tracing human contact within indoor places using the open OGC IndoorGML standard. This paper proposes a graph-based data model that considers the semantics of indoor locations, time, and users’ contexts in a hierarchical structure. The functionality of the proposed data model is evaluated for a COVID-19 contact tracing application with scalable system architecture. Indoor trajectory preprocessing is enabled by spatial topology to detect and remove semantically invalid real-world trajectory points. Results show that 91.18% percent of semantically invalid indoor trajectory data points are filtered out. Moreover, indoor trajectory data analysis is innovatively empowered by semantic user contexts (e.g., disinfecting activities) extracted from user profiles. In an enhanced contact tracing scenario, considering the disinfecting activities and sequential order of visiting common places outperformed contact tracing results by filtering out unnecessary potential contacts by 44.98 percent. However, the average execution time of person-to-place contact tracing is increased by 58.3%.

scholarly journals The Role of Spatio-Temporal Information to Govern the COVID-19 Pandemic: A European Perspective

2021 ◽  
Vol 10 (3) ◽  
pp. 166
Author(s):  
Hartmut Müller ◽  
Marije Louwsma
Keyword(s):  
European Union ◽  
Spatial Distribution ◽  
Spatial Information ◽  
National Level ◽  
Temporal Information ◽  
The European Union ◽  
Member States ◽  
Heavy Burden ◽  
Spatio Temporal

The Covid-19 pandemic put a heavy burden on member states in the European Union. To govern the pandemic, having access to reliable geo-information is key for monitoring the spatial distribution of the outbreak over time. This study aims to analyze the role of spatio-temporal information in governing the pandemic in the European Union and its member states. The European Nomenclature of Territorial Units for Statistics (NUTS) system and selected national dashboards from member states were assessed to analyze which spatio-temporal information was used, how the information was visualized and whether this changed over the course of the pandemic. Initially, member states focused on their own jurisdiction by creating national dashboards to monitor the pandemic. Information between member states was not aligned. Producing reliable data and timeliness reporting was problematic, just like selecting indictors to monitor the spatial distribution and intensity of the outbreak. Over the course of the pandemic, with more knowledge about the virus and its characteristics, interventions of member states to govern the outbreak were better aligned at the European level. However, further integration and alignment of public health data, statistical data and spatio-temporal data could provide even better information for governments and actors involved in managing the outbreak, both at national and supra-national level. The Infrastructure for Spatial Information in Europe (INSPIRE) initiative and the NUTS system provide a framework to guide future integration and extension of existing systems.

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