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47 results for “cost monitoring”
The potential of low-cost UAVs and open-source photogrammetry software for high-resolution monitoring of alpine glaciers: A case study from the Kanderfirn (Swiss Alps)
<p>This dataset contains high-resolution orthophotos (5 x 5 cm) and digital surface models (25 x 25 cm) of the Kandernfirn Glacier located in the Swiss Alps. Aerial images were aquired with a self-developed fixed-wing Unmanned Aerial Vehicle during ten surveys on five different days in 2017 and 2018. The open-source photogrammetry software OpenDroneMap (version 0.4.1) was used for image processing.</p> <p>The orthophotos and digital surface models were validated through dGNSS point measurements of ground control points. Please refer to the corresponding paper for information on the horizontal and vertical accuracy of the files.</p>
Low-Cost Sensors and Multitemporal Remote Sensing for Operational Turbidity Monitoring in an East African Wetland Environment - Measurements and Locations
<p>Many wetlands in East Africa are farmed and wetland reservoirs are used for irrigation, livestock, and fishing. Water quality and agriculture have a mutual influence on each other. Turbidity is a principal indicator of water quality and can be used for, otherwise, unmonitored water sources. Low-cost turbidity sensors improve in situ coverage and enable community engagement. The availability of high spatial resolution satellite images from the Sentinel-2 multispectral instrument and of bio-optical models, such as the Case 2 Regional CoastColor (C2RCC) processor, has fostered turbidity modeling. However, these models need local adjustment, and the quality of low-cost sensor measurements is debated. We tested the combination of both technologies to monitor turbidity in small wetland reservoirs in Kenya. We sampled ten reservoirs with low-cost sensors and a turbidimeter during five Sentinel-2 overpasses. Low-cost sensor calibration resulted in an R² of 0.71. The models using the C2RCC C2X-COMPLEX (C2XC) neural nets with turbidimeter measurements (R² = 0.83) and with low-cost measurements (R² = 0.62) performed better than the turbidimeter-based C2X model. The C2XC models showed similar patterns for a one-year time series, particularly around the turbidity limit set by Kenyan authorities. This shows that both the data from the commercial turbidimeter and the low-cost sensor setup, despite sensor uncertainties, could be used to validate the applicability of C2RCC in the study area, select the better-performing neural nets, and adapt the model to the study site. We conclude that combined monitoring with low-cost sensors and remote sensing can support wetland and water management while strengthening community-centered approaches.</p> <p>The provided dataset includes a point shapefile with the studied reservoirs in central Kenya and a data table with the sampling date (Sentinel-2 overpass plus/minus one day), low-cost sensor setup number, reservoir ID, sampling location within the reservoir, the voltage measurements of the three respective low-cost sensor heads for sensor setups A and B, the averaged voltage, and the turbidimeter measured turbidity value in nephelometric turbidity units (NTU).</p> <p>The study is available in (please cite):</p> <div> <div>Steinbach, S., Rienow, A., Chege, M.W., Dedring, N., Kipkemboi, W., Thiong’o, B.K., Zwart, S.J., Nelson, A., 2024. Low-Cost Sensors and Multitemporal Remote Sensing for Operational Turbidity Monitoring in an East African Wetland Environment. <em>IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing</em> <em>17</em>, 8490–8508. <a href="https://doi.org/10.1109/JSTARS.2024.3381756">https://doi.org/10.1109/JSTARS.2024.3381756</a></div> </div> <p>This research was supported in part by the German Federal Ministry of Education and Research (BMBF) through the Project “Participatory Approach to Environmental Conservation of the Muringato Catchment Area for Sustainable Management and Enhanced Ecosystem Health” (CITGI4Muringato) under Grant Agreement No. 01DG20022.</p>
Software and data for: VGWatch: A low-cost stand-alone monitor to measure the valve gape of bivalves in the field
<p>Software and data abstract:</p> <p>This archive includes an Arduino script for utilizing the valve gape monitor outlined in the paper. Additionally, it provides an R script for calibrating the monitor and magnet. Finally, it contains valve gape data from three mussels, collected using the described monitor, along with a script for the analysis.</p> <p> </p> <p>Paper abstract:</p> <p>Valve gape monitors are utilised to measure the extent of bivalve’s shell openings. This measurement is correlated with their filter-feeding activity, and valve closure can serve as an indicator of various environmental stressors, including poor water quality, the presence of predators, and human disturbance. We developed an inexpensive, stand-alone, and reusable valve gape monitor; enabling collection of sufficient and independent spatial replication <em>in situ</em>. The monitor is made using Arduino hardware and software, and we share the design and code. We tested it in the field with three mussels as a proof of concept. The mussels were likely actively feeding most of the time. Two of the mussels were in close vicinity and demonstrated similar valve gape patterns. The monitor enables to measure valve gape in high resolution, providing insights into bivalve biology, ecosystem functioning, and the effects of environmental conditions, including anthropogenic stressors.</p>
Supplementary Data for "Development of a General Calibration Model and Long-Term Performance Evaluation of Low-Cost Sensors for Air Pollutant Gas Monitoring" (abridged version)
<p>This is a supplementary data set associated with the publication "Development of a General Calibration Model and Long-Term Performance Evaluation of Low-Cost Sensors for Air Pollutant Gas Monitoring" from the Center for Atmospheric Particle Studies, submitted to Atmospheric Measurement Techniques. This is an abbreviated version which does not include the calibrated models; these models must be re-generated by running the codes contained with the data set.</p> <p> </p>
ScintPi: A low-cost, easy-to-build GPS ionospheric scintillation monitor for DASI studies of space weather, education, and citizen science initiatives
<p>These data sets contain ionospheric scintillation (GPS L1) observations (S4 indices) collected by a ScintPi prototype during 2018 at a low magnetic latitude station (Presidente Prudente). ScintPi is a low-cost, easy-to-build GPS ionospheric scintillation monitor for DASI studies of space weather, education, and citizen science initiatives.</p> <p>The file named "ScintPi_PPR_S4_2018.mat" contains S4 values (s4mat) for 2018 as a function of universal time (utmat), day-of-year (doymat), GPS satellite identifier number (prnmat), GPS satellite elevation (elmat) and azimuth (azmat) angles.</p> <p>The file named "ScintPi_PPR_20180211.mat" contains example raw (10 Hz) measurements made by ScintPi on February 11, 2018. The file contains values of receiver's altitude, latitude and longitude (variables alt,lat, and lon), GPS satellite azimuth and elevation (variables el and az), GPS identifier number (prn), signal-to-noise ratio (snr), and day-of-year (doy).</p>
ScintPi 2.0 and 3.0: low-cost GNSS-based monitors of ionospheric scintillation and total electron content
<p> </p> <p>This data set provides measurements made by PolaR5x and ScintPi3.0 receivers in Presidente Prudente, Brazil for two consecutive days.</p>
NOBEL-BOX: A Ship-Based Low-Cost Instrument for Real-Time Ocean Monitoring and Analysis
<p>This data is the measurement result obtained from the NOBEL-BOX instrument. The principle of NOBEL-BOX is to attach sensors in a container connected to a microcontroller and then measure directly. This data results from measurements using fresh water and sea water mixed to see the response from NOBEL BOX. Furthermore, data was also obtained from sea measurements in Pangandaran, West Java, Indonesia. These measurements include pH, water and water temperature, dissolved oxygen, TDS, and salinity. The use of this parameter is to see the condition of the sea so that it becomes a reference in mitigating and managing the ocean.</p>
Figure 3. A in A Low-Cost Trap to Monitor Parasitism of Macadamia Felted Coccid (Hemiptera: Eriococcidae) and Other Scale Insects
Figure 3. A. Encarsia lounsburyi parasitizing an MFC adult. B. A circular parasitoid emergence hole on an adult male MFC host, indicating parasitism.
Figure 2 in A Low-Cost Trap to Monitor Parasitism of Macadamia Felted Coccid (Hemiptera: Eriococcidae) and Other Scale Insects
Figure 2. The parasitoid emergence trap installed on a macadamia tree branch infested with macadamia felted coccid.
Figure 1. A. A low-cost 100 in A Low-Cost Trap to Monitor Parasitism of Macadamia Felted Coccid (Hemiptera: Eriococcidae) and Other Scale Insects
Figure 1. A. A low-cost 100 ml PET bottle can be used to construct a parasitoid emer- gence trap to study parasitism of MFC in the field. B. Basic components of the parasitoid emergence trap showing the PET bottle with modifications allowing for attachment to the tree branch and insertion of a glass collection vial. C. A fully assembled trap.
Data for "ChickenSense: A low-cost deep learning-based solution for real-time poultry feed intake monitoring using sound technology"
<p>The dataset includes two types of data: scale and audio. The scale data is recorded using a hanging scale and measures the feeders' weight with a 5 Hz frequency. The audio data contains 1824 hours of recorded audio using a piezo-electric sensor attached to a bucket feeder to capture vibrations as audio signals with a sampling rate of 48 kHz. Each .wav file contains 15 minutes of audio recording.<br> Along with the raw data, a part of the dataset containing 36 30-second audio recordings was sampled and labeled in four classes, including pecking, singing, anomaly, and silence, resulting in 3319 labeled events. </p>
Data from high throughput SNP-chip as cost effective new monitoring tool for assessing invasion dynamics in the comb jelly Mnemiopsis leidyi
<p class="MsoNormal"><span>High throughput low-density SNP arrays provide a cost-effective solution for population genetic studies and monitoring of genetic diversity as well as population structure commonly implemented in real time stock assessment of fish species. However, the application of high throughput SNP arrays for monitoring of invasive species has so far not been implemented. We developed a species-specific SNP array for the invasive comb jelly <em>Mnemiopsis leidyi</em> based on whole genome resequencing data. Initially, </span><span>a total of</span><span> </span><span>1,</span><span>395</span><span> </span><span>high quality </span><span>SNPs</span><span> were identified</span><span> </span><span>u</span><span>sing stri</span><span>ngent</span><span> filtering criteria</span><span>. From those, 192 assays were designed and validated, resulting in the final panel of 116 SNPs. Markers were diagnostic between the northern and southern <em>M. leidyi</em> lineages and highly polymorphic to distinguish populations. Despite using a reduced representation of the genome, our SNP panel yielded comparable results to using a whole genome resequencing approach (832,323 SNPs), recovering similar values of genetic differentiation between samples and detecting the same clustering groups when performing Structure analyses. The resource presented here provides a cost-effective, high throughput solution for population genetic studies, allowing to routinely genotype large number of individuals. Monitoring of genetic diversity and effective population size estimations in this highly invasive species will allow for the early detection of new introductions from distant source regions or hybridization events. Thereby, this SNP chip represents an important management tool in order to understand invasion dynamics and </span><span>opens the door for implementing such methods for a wider range of alien invasive species.</span></p> <div></div>
Integrated Health Monitoring and Reinforcement of Transportation Structures with Optimized Low-Cost Multifunctional Braided Cables
<p>Corresponding data set for Tran-SET Project No. 17STTAM04. Abstract of the final report is stated below for reference:</p> <p>"The objective of this research study is to design, fabricate, and characterize multifunctional high strength and self-sensing braided cables and structures using novel Fe-based shape memory alloys (SMAs). The system exploits unique properties of recently developed low-cost super-elastic FeMnAlNi SMAs, which enables excellent super-elastic properties, high strength, and self-sensing in structural health monitoring (SHM) systems. This novel material technology can be coupled with modeling efforts that allow for accurate prediction of both the materials and structural response during sensing. At the conclusion of the project, we have demonstrated that with careful design of processing parameters, it is possible to control the yield strength and superleastic properties of FeMnAlNi SMAs. We have fabricated, for the first time in the world, a large diameter wires and bars from these inexpensive iron based SMAs which are expected to help with scaling up the fabrication of these materials. In addition, we were able to develop a method for fabricating braided cables from the fabricated Fe-SMA wires and a lab scale experimental setup has been designed and built. Prototype design for the braiding weave was created and tested. Finally, an experimental setup has been designed and manufactured to measure changes in the magnetic response of the SMA braided cables under load in order to directly correlate the magnetic response with deflection and strain. Clearly, the successful fabrication of wires and braided cables of the inexpensive iron based SMAs with superelastic strains comparable to nickel-titanium SMAs and with favorable magnetic sensing capabilities have significant implications for transportation infrastructure as these materials can provide structural health monitoring capability while also mitigating large shape changes during natural disasters. Future work needs to focus on revealing the coupling between mechanical properties (in particular damage) and the changes in magnetic properties in order to provide guidance on how these materials can be utilized in structural health monitoring."</p>
Development, Training, Education, and Implementation of Low-Cost Sensing Technologies for Bridge Structural Health Monitoring (SHM)
<p>Corresponding data set for Tran-SET Project No. 17STUNM02. Abstract of the final report is stated below for reference:</p> <p>"Transportation infrastructure needs continuous monitoring. However, traditional inspections cost money and are conducted visually. New technologies for bridge monitoring are expensive and complex. This project involved developing cost-effective sensor technologies that can be applied towards the maintenance of railroad bridges by recording reference-free transverse displacement. More specifically, this project developed new applications of new technologies (Arduino, wireless smart sensors, drones, Hololens) and promoted workforce development with an emphasis on outreach of high-school students. This project was carried out in three main phases: (1) development and validation of technologies, (2) education and outreach to students, and (3) outreach to industry consisting in one professional workshop. The findings from the first phase showed that the data gathered by these new low-cost sensing systems were comparable to the data collected using traditional sensors. Researchers collected the findings of the second phase of the project through surveys conducted from Middle school, High school and college students during and after outreach activities. these surveys showed that many of the participant students got more interested in the use of new technologies after getting familiar with them. Finally, researchers collected the findings of the third phase of the project through a workshop collecting the interest and challenges of the owners of railroad infrastructure. The top interest of railroad owners is to explore the use of new technologies to increase safety in the field. The conclusions of this research include prioritization on developing low-cost technologies that can measure simple parameters in the field of interest to existing inspectors."</p>
Phytoplankton Dataset: Supporting HAB monitoring based on cost-effective open-hardware solutions
<p>ASTRAL Phytoplankton monitoring dataset which has supported technology validation based on images from single-specie phytoplankton sample and prototype deployment within IMTA labs</p>
Microplastic Dataset: Supporting microplastic monitoring based on cost-effective open-hardware solutions
<p>ASTRAL Dataset related to microplastic monitoring based on the open-hardware initiative PlanktoScope</p>
Use of High Cost Monitoring During Letrozole Ovulation Induction
ClinicalTrials.gov study NCT01279200. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Data from high throughput SNP-chip as cost effective new monitoring tool for assessing invasion dynamics in the comb jelly Mnemiopsis leidyi
Open the record for dataset details and reuse information.
Monitoring of cow location in barn by an open source low cost low energy Bluetooth tag system
<p>Supplementary materials for: Bloch, V., Pastell, M., 2020. Monitoring of Cow Location in a Barn by an Open-Source, Low-Cost, Low-Energy Bluetooth Tag System. Sensors 20, 3841. <a href="https://doi.org/10.3390/s20143841">https://doi.org/10.3390/s20143841</a></p>
Deep learning low-cost photogrammetry for 4D short-term glacier dynamics monitoring - Supplementary material
<p>This repository contains the supplementary material for the paper "Deep learning low-cost photogrammetry for 4D short-term glacier dynamics monitoring".</p><p>The paper is currently under revision. This repository will be updated once the paper will be published.</p><p>In particular the repository includes:</p><ol><li>The datasets used for performing the multi-temporal stereoscopic analysis of the Belvedere Glacier during the summer season 2022.</li><li>The code of ICEpy4D v1.9.0 used for processing the stereoscopic data. An updated version of ICEpy4D can be found in the Github repository https://github.com/franioli/icepy4d </li></ol><p> </p><p><br> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.