scholarly journals Design and development of a novel acoustic rain sensor with automated telemetry

2018 ◽  
Vol 201 ◽  
pp. 03003
Author(s):  
Maria Leonora Guico ◽  
Gemalyn Abrajano ◽  
Prince Aldrin Domer ◽  
Jose Paulo Talusan

This paper presents the recent results of the design of a novel acoustic rainfall sensing system that is low-cost, portable, and easily deployable, which makes use of the recorded sound produced by the impact of the raindrops on the sensor surface. The sensor design allows the gathering of acoustic signal power and sending it to a server after a specified time interval, either through SMS or mobile internet connection. It exists in a weather-proof, standard-conformant, standalone system with its own power supply and telemetric capabilities. These acoustic point sensors can gather rainfall data at high spatial and temporal resolutions. Such deployments can show the variations of rainfall intensities in sub-kilometer areas, particularly in the tropical regions. Since it is low-cost, it can also improve the density of rainfall measuring devices in an area. Moreover, the reliability is improved by providing near-real time data, as opposed to tipping buckets with manual data retrieval. The prototype sensor system was placed next to standard rain measuring devices and observed during the rainy season. The paper will discuss the design and deployment of the system, as well as initial results of data analysis and comparison with standard rain measuring devices.

2018 ◽  
Vol 7 (2.7) ◽  
pp. 444 ◽  
Author(s):  
Samir Yerpude ◽  
Dr Tarun Kumar Singhal

Objectives: To study the impact of Internet of things (IoT) on the Customer Relationship Management process and evaluate the benefits in terms of customer satisfaction and customer retention. Methods: An extensive literature review was conducting wherein the constructs of CRM and IoT are studied. Various preliminary information on IoT and CRM system along with the components of Digital enablers have been evaluated. References from research papers, journals, Internet sites, statistical data sites and books were used to collate the relevant content on the subject. The study of all the relevant scenarios where there is a possible impact of IoT origin real time data on CRM was undertaken. Findings: Customer demands are continuously evolving and it is very relevant for all the organizations to align and keep pace with the change. Organizations need to be customer centric and agile to the changing market scenarios. Evaluation of the trends in mobile internet vs desktop internet was also conducted to validate the findings. Application: The usage of real time data emerging out of the IoT landscape has become a reality with the data transmitted over the Internet and consumed by the CRM system. It improves the control on the customer relationship function helping the organizations to operate within healthy and sustained profit  


2018 ◽  
Vol 146 (1) ◽  
pp. 199-211 ◽  
Author(s):  
Will McCarty ◽  
Mohar Chattopadhyay ◽  
Austin Conaty

Abstract The Rapid Scatterometer (RapidScat) was built as a low-cost follow-on to the QuikSCAT mission. It flew on the International Space Station (ISS) and provided data from 3 October 2014 to 20 August 2016. These data allowed for the retrieval of surface wind vectors derived from surface roughness estimates measured from multiple coincident azimuth angles. These measurements were unique to the historical scatterometer record in that the ISS flies in a low inclination, non-sun-synchronous orbit. Scatterometry-derived wind vectors have been routinely assimilated in both forward processing and reanalysis systems run at the Global Modeling and Assimilation Office (GMAO). As the RapidScat retrievals were made available in near–real time, they were assimilated in the forward processing system, and the methods to assimilate and evaluate these retrievals are described. Time series of data statistics are presented first for the near-real-time data assimilated in GMAO forward processing. Second, the full data products provided by the RapidScat team are compared passively to the MERRA-2 reanalysis. Both sets of results show that the root-mean-square (RMS) difference of the observations and the GMAO model background fields increased over the course of the data record. Furthermore, the observations and the backgrounds are shown to be biased for both the zonal and meridional wind components. The retrievals are shown to have had a net forecast error reduction via the forecast sensitivity observation impact (FSOI) metric, which is a quantification of 24-h forecast error reduction, though the impact became neutral as the signal-to-noise ratio of the instrument decreased over its lifespan.


2021 ◽  
Author(s):  
Ridouane El Mezouary ◽  
Abdelmoghit Souissi

Abstract In this article, we propose a new mobility model, for a mobile and geographic cross-layer architecture. This cross-layer architecture allows service differentiation between real-time and best-effort traffic, for a mobile internet of things ( IoT ) network. We present a mathematical model, which works on the parameters of the MAC layer and the network layer. The mathematical model makes it possible to calculate the throughput between a source object and a destination object (gateway), under conditions of stable queues. We use the positional (geographic) information in the mathematical model of the proposed cross-layer architecture, to study the impact of mobility on the performance of the proposed mathematical model. The proposed mobility model defines two time intervals, the first interval for communication (transmission and reception of data without mobility at the same time), and the second time interval for the mobility of objects of the IoT network (without communication at the same time). The results show that the calculated throughput depends on the position of the objects, as well as the probability of transmission. Finally, we study the effect of distance and speed on the performance of the proposed cross-layer architecture.


2020 ◽  
Vol 90 (3) ◽  
pp. 30502
Author(s):  
Alessandro Fantoni ◽  
João Costa ◽  
Paulo Lourenço ◽  
Manuela Vieira

Amorphous silicon PECVD photonic integrated devices are promising candidates for low cost sensing applications. This manuscript reports a simulation analysis about the impact on the overall efficiency caused by the lithography imperfections in the deposition process. The tolerance to the fabrication defects of a photonic sensor based on surface plasmonic resonance is analysed. The simulations are performed with FDTD and BPM algorithms. The device is a plasmonic interferometer composed by an a-Si:H waveguide covered by a thin gold layer. The sensing analysis is performed by equally splitting the input light into two arms, allowing the sensor to be calibrated by its reference arm. Two different 1 × 2 power splitter configurations are presented: a directional coupler and a multimode interference splitter. The waveguide sidewall roughness is considered as the major negative effect caused by deposition imperfections. The simulation results show that plasmonic effects can be excited in the interferometric waveguide structure, allowing a sensing device with enough sensitivity to support the functioning of a bio sensor for high throughput screening. In addition, the good tolerance to the waveguide wall roughness, points out the PECVD deposition technique as reliable method for the overall sensor system to be produced in a low-cost system. The large area deposition of photonics structures, allowed by the PECVD method, can be explored to design a multiplexed system for analysis of multiple biomarkers to further increase the tolerance to fabrication defects.


Author(s):  
J.R. Caradus ◽  
D.A. Clark

The New Zealand dairy industry recognises that to remain competitive it must continue to invest in research and development. Outcomes from research have ensured year-round provision of low-cost feed from pasture while improving productivity. Some of these advances, discussed in this paper, include the use of white clover in pasture, understanding the impacts of grass endophyte, improved dairy cow nutrition, the use of alternative forage species and nitrogen fertiliser to improve productivity, demonstration of the impact of days-in-milk on profitability, and the use of feed budgeting and appropriate pasture management. Keywords: dairy, profitability, research and development


2018 ◽  
Vol 32 (2) ◽  
pp. 103-119
Author(s):  
Colleen M. Boland ◽  
Chris E. Hogan ◽  
Marilyn F. Johnson

SYNOPSIS Mandatory existence disclosure rules require an organization to disclose a policy's existence, but not its content. We examine policy adoption frequencies in the year immediately after the IRS required mandatory existence disclosure by nonprofits of various governance policies. We also examine adoption frequencies in the year of the subsequent change from mandatory existence disclosure to a disclose-and-explain regime that required supplemental disclosures about the content and implementation of conflict of interest policies. Our results suggest that in areas where there is unclear regulatory authority, mandatory existence disclosure is an effective and low cost regulatory device for encouraging the adoption of policies desired by regulators, provided those policies are cost-effective for regulated firms to implement. In addition, we find that disclose-and-explain regulatory regimes provide stronger incentives for policy adoption than do mandatory existence disclosure regimes and also discourage “check the box” behavior. Future research should examine the impact of mandatory existence disclosure rules in the year that the regulation is implemented. Data Availability: Data are available from sources cited in the text.


2020 ◽  
Vol 12 (19) ◽  
pp. 3226
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.


Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.


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