scholarly journals Development and Analysis of Low-Cost IoT Sensors for Urban Environmental Monitoring

2021 ◽  
Vol 16 (5) ◽  
Author(s):  
Ionut Muntean ◽  
George Dan Mois ◽  
Silviu Corneliu Folea
Keyword(s):  
Low Cost ◽  
Complete Solution ◽  
Sound Intensity ◽  
Negative Effects ◽  
Sound Levels ◽  
Ambient Sound ◽  
Outdoor Spaces ◽  
Cloud Application ◽  
Recorded Data ◽  
Indoor And Outdoor

The accelerated pace of urbanization is having a major impact over the world’s environment. Although urban dwellers have higher living standards and can access better public services as compared to their rural counterparts, they are usually exposed to poor environmental conditions such as air pollution and noise. In order for municipalities and citizens to mitigate the negative effects of pollution, the monitoring of certain parameters, such as air quality and ambient sound levels, both in indoor and outdoor locations, has to be performed. The current paper presents a complete solution that allows the monitoring of ambient parameters such as Volatile Organic Compounds, temperature, relative humidity, pressure, and sound intensity levels both in indoor and outdoor spaces. The presented solution comprises of low-cost, easy to deploy, wireless sensors and a cloud application for their management and for storing and visualizing the recorded data.

scholarly journals An Agent-Based Crop Model Framework for Heterogeneous Soils

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 85
Author(s):  
Jorge Lopez-Jimenez ◽  
Nicanor Quijano ◽  
Alain Vande Wouwer
Keyword(s):  
Growth Models ◽  
Control Strategies ◽  
Low Cost ◽  
Soil Heterogeneity ◽  
Crop Growth ◽  
Negative Effects ◽  
Model Framework ◽  
Agent Based ◽  
Crop Growth Models ◽  
Definition Of

Climate change and the efficient use of freshwater for irrigation pose a challenge for sustainable agriculture. Traditionally, the prediction of agricultural production is carried out through crop-growth models and historical records of the climatic variables. However, one of the main flaws of these models is that they do not consider the variability of the soil throughout the cultivation area. In addition, with the availability of new information sources (i.e., aerial or satellite images) and low-cost meteorological stations, it is convenient that the models incorporate prediction capabilities to enhance the representation of production scenarios. In this work, an agent-based model (ABM) that considers the soil heterogeneity and water exchanges is proposed. Soil heterogeneity is associated to the combination of individual behaviours of uniform portions of land (agents), while water fluxes are related to the topography. Each agent is characterized by an individual dynamic model, which describes the local crop growth. Moreover, this model considers positive and negative effects of water level, i.e., drought and waterlogging, on the biomass production. The development of the global ABM is oriented to the future use of control strategies and optimal irrigation policies. The model is built bottom-up starting with the definition of agents, and the Python environment Mesa is chosen for the implementation. The validation is carried out using three topographic scenarios in Colombia. Results of potential production cases are discussed, and some practical recommendations on the implementation are presented.

scholarly journals SARS-COV-2: SIR Model Limitations and Predictive Constraints

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 676
Author(s):  
Charles Roberto Telles ◽  
Henrique Lopes ◽  
Diogo Franco
Keyword(s):  
Time Series Data ◽  
Data Extraction ◽  
Sir Model ◽  
Series Data ◽  
Atmospheric Conditions ◽  
Main Research ◽  
Outdoor Spaces ◽  
Model Equations ◽  
Physical Features ◽  
Indoor And Outdoor

Background: The main purpose of this research is to describe the mathematical asymmetric patterns of susceptible, infectious, or recovered (SIR) model equation application in the light of coronavirus disease 2019 (COVID-19) skewness patterns worldwide. Methods: The research modeled severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) spreading and dissemination patterns sensitivity by redesigning time series data extraction of daily new cases in terms of deviation consistency concerning variables that sustain COVID-19 transmission. The approach opened a new scenario where seasonality forcing behavior was introduced to understand SARS-COV-2 non-linear dynamics due to heterogeneity and confounding epidemics scenarios. Results: The main research results are the elucidation of three birth- and death-forced seasonality persistence phases that can explain COVID-19 skew patterns worldwide. They are presented in the following order: (1) the environmental variables (Earth seasons and atmospheric conditions); (2) health policies and adult learning education (HPALE) interventions; (3) urban spaces (local indoor and outdoor spaces for transit and social-cultural interactions, public or private, with natural physical features (river, lake, terrain). Conclusions: Three forced seasonality phases (positive to negative skew) phases were pointed out as a theoretical framework to explain uncertainty found in the predictive SIR model equations that might diverge in outcomes expected to express the disease’s behaviour.

Event-Locked Time-Resolved Fourier Spectroscopy

1997 ◽  
Vol 51 (8) ◽  
pp. 1106-1112 ◽  
Author(s):  
H. Weidner ◽  
R. E. Peale
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Michelson Interferometer ◽  
Far Infrared ◽  
Time Base ◽  
The Novel ◽  
Time Resolved ◽  
Mathematical Algorithm ◽  
Scan Time ◽  
Recorded Data

A low-cost method of adding time-resolving capability to commercial Fourier transform spectrometers with a continuously scanning Michelson interferometer has been developed. This method is specifically designed to eliminate noise and artifacts caused by mirror-speed variations in the interferometer. The method exists of two parts: (1) a novel timing scheme for synchronizing the transient events under study and the digitizing of the interferogram and (2) a mathematical algorithm for extracting the spectral information from the recorded data. The novel timing scheme is a modification of the well-known interleaved, or stroboscopic, method. It achieves the same timing accuracy, signal-to-noise ratio, and freedom from artifacts as step-scan time-resolving Fourier spectrometers by locking the sampling of the interferogram to a stable time base rather than to the occurrences of the HeNe fringes. The necessary pathlength-difference information at which samples are taken is obtained from a record of the mirror speed. The resulting interferograms with uneven pathlength-difference spacings are transformed into wavenumber space by least-squares fits of periodic functions. Spectra from the far-infrared to the upper visible at resolutions up to 0.2 cm−1 are used to demonstrate the utility of this method.

scholarly journals Effects of season on ecological processes in extensive earthen tilapia ponds in Southeastern Brazil

2015 ◽  
Vol 75 (4 suppl 1) ◽  
pp. 97-107 ◽  
Author(s):  
E. G. P. Favaro ◽  
L. H. Sipaúba-Tavares ◽  
A. Milstein
Keyword(s):  
Low Cost ◽  
Stocking Density ◽  
Grazing Pressure ◽  
Southeastern Brazil ◽  
Negative Effects ◽  
Ecological Processes ◽  
Pond Ecosystem ◽  
Disposal Option ◽  
Flow Through ◽  
Dry Seasons

Abstract In Southeastern Brazil tilapia culture is conducted in extensive and semi-intensive flow-through earthen ponds, being water availability and flow management different in the rainy and dry seasons. In this region lettuce wastes are a potential cheap input for tilapia culture. This study examined the ecological processes developing during the rainy and dry seasons in three extensive flow-through earthen tilapia ponds fertilized with lettuce wastes. Water quality, plankton and sediment parameters were sampled monthly during a year. Factor analysis was used to identify the ecological processes occurring within the ponds and to construct a conceptual graphic model of the pond ecosystem functioning during the rainy and dry seasons. Processes related to nitrogen cycling presented differences between both seasons while processes related to phosphorus cycling did not. Ecological differences among ponds were due to effects of wind protection by surrounding vegetation, organic loading entering, tilapia density and its grazing pressure on zooplankton. Differences in tilapia growth among ponds were related to stocking density and ecological process affecting tilapia food availability and intraspecific competition. Lettuce wastes addition into the ponds did not produce negative effects, thus this practice may be considered a disposal option and a low-cost input source for tilapia, at least at the amounts applied in this study.

Transitional Spaces: Between Indoor and Outdoor Spaces

2013 ◽  
pp. 14-32 ◽  
Author(s):  
Christian Kray ◽  
Holger Fritze ◽  
Thore Fechner ◽  
Angela Schwering ◽  
Rui Li ◽  
...  
Keyword(s):  
Outdoor Spaces ◽  
Transitional Spaces ◽  
Indoor And Outdoor

scholarly journals Population rate-coding predicts correctly that human sound localization depends on sound intensity

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Antje Ihlefeld ◽  
Nima Alamatsaz ◽  
Robert M Shapley
Keyword(s):  
Sound Localization ◽  
Sound Intensity ◽  
Spatial Location ◽  
Spike Rate ◽  
Behavioral Experiments ◽  
Interaural Time Differences ◽  
Sound Levels ◽  
Rate Coding ◽  
The Brain ◽  
Population Rate

Human sound localization is an important computation performed by the brain. Models of sound localization commonly assume that sound lateralization from interaural time differences is level invariant. Here we observe that two prevalent theories of sound localization make opposing predictions. The labelled-line model encodes location through tuned representations of spatial location and predicts that perceived direction is level invariant. In contrast, the hemispheric-difference model encodes location through spike-rate and predicts that perceived direction becomes medially biased at low sound levels. Here, behavioral experiments find that softer sounds are perceived closer to midline than louder sounds, favoring rate-coding models of human sound localization. Analogously, visual depth perception, which is based on interocular disparity, depends on the contrast of the target. The similar results in hearing and vision suggest that the brain may use a canonical computation of location: encoding perceived location through population spike rate relative to baseline.

scholarly journals Wind Turbine Noise Reduction from Seismological Data

2021 ◽  
Author(s):  
Janis Heuel ◽  
Wolfgang Friederich
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Computational Cost ◽  
Noise Signal ◽  
Noise Model ◽  
Threshold Function ◽  
High Signal ◽  
Time Data ◽  
Negative Effects ◽  
Before And After

<p>Over the last years, installations of wind turbines (WTs) increased worldwide. Owing to<br>negative effects on humans, WTs are often installed in areas with low population density.<br>Because of low anthropogenic noise, these areas are also well suited for sites of<br>seismological stations. As a consequence, WTs are often installed in the same areas as<br>seismological stations. By comparing the noise in recorded data before and after<br>installation of WTs, seismologists noticed a substantial worsening of station quality leading<br>to conflicts between the operators of WTs and earthquake services.</p><p>In this study, we compare different techniques to reduce or eliminate the disturbing signal<br>from WTs at seismological stations. For this purpose, we selected a seismological station<br>that shows a significant correlation between the power spectral density and the hourly<br>windspeed measurements. Usually, spectral filtering is used to suppress noise in seismic<br>data processing. However, this approach is not effective when noise and signal have<br>overlapping frequency bands which is the case for WT noise. As a first method, we applied<br>the continuous wavelet transform (CWT) on our data to obtain a time-scale representation.<br>From this representation, we estimated a noise threshold function (Langston & Mousavi,<br>2019) either from noise before the theoretical P-arrival (pre-noise) or using a noise signal<br>from the past with similar ground velocity conditions at the surrounding WTs. Therefore, we<br>installed low cost seismometers at the surrounding WTs to find similar signals at each WT.<br>From these similar signals, we obtain a noise model at the seismological station, which is<br>used to estimate the threshold function. As a second method, we used a denoising<br>autoencoder (DAE) that learns mapping functions to distinguish between noise and signal<br>(Zhu et al., 2019).</p><p>In our tests, the threshold function performs well when the event is visible in the raw or<br>spectral filtered data, but it fails when WT noise dominates and the event is hidden. In<br>these cases, the DAE removes the WT noise from the data. However, the DAE must be<br>trained with typical noise samples and high signal-to-noise ratio events to distinguish<br>between signal and interfering noise. Using the threshold function and pre-noise can be<br>applied immediately on real-time data and has a low computational cost. Using a noise<br>model from our prerecorded database at the seismological station does not improve the<br>result and it is more time consuming to find similar ground velocity conditions at the<br>surrounding WTs.</p>

scholarly journals Internet of Trees

2021 ◽  
Vol 10 (2) ◽  
pp. 750-753
Keyword(s):  
Forest Fires ◽  
Low Cost ◽  
Web Server ◽  
Fire Risk ◽  
Fire Detection ◽  
Natural Habitats ◽  
The Public ◽  
Recorded Data ◽  
The Impact ◽  
The Internet Of Things

The frequency of the forest fires that have occurred in the different parts of the world, In recent decades significant population problems and causing the death if the wild animals as the impact of these fires extend beyond the destruction of the natural habitats. The proliferation of the Internet of Things industry, resolutions for initial fire detection should be developed. The valuation of the fire risk of an area and communication of this realities to the population could reduce the amount of fires originated by accident or due to carelessness of the public user. This paper proposes a low-cost network based on NXP Rapid IOT kit and Long Range (Lora) technology to autonomously estimate the level of fire risk in the forest. The system comprises of NXP Rapid IOT kit which humidity, air quality and detection of the tree fall. The data from each node stored and processed in a in a web server or the mobile application that sendsthe recorded data to a web server for graphical conception of collected data.

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