Other packages > Find by keyword >

mmaqshiny  

Explore Air-Quality Mobile-Monitoring Data
View on CRAN: Click here


Download and install mmaqshiny package within the R console
Install from CRAN:
install.packages("mmaqshiny")

Install from Github:
library("remotes")
install_github("cran/mmaqshiny")

Install by package version:
library("remotes")
install_version("mmaqshiny", "1.0.0")



Attach the package and use:
library("mmaqshiny")
Maintained by
Adithi R. Upadhya
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-26
Latest Update: 2020-06-26
Description:
Mobile-monitoring or "sensors on a mobile platform", is an increasingly popular approach to measure high-resolution pollution data at the street level. Coupled with location data, spatial visualisation of air-quality parameters helps detect localized areas of high air-pollution, also called hotspots. In this approach, portable sensors are mounted on a vehicle and driven on predetermined routes to collect high frequency data (1 Hz). 'mmaqshiny' is for analysing, visualising and spatial mapping of high-resolution air-quality data collected by specific devices installed on a moving platform. 1 Hz data of PM2.5 (mass concentrations of particulate matter with size less than 2.5 microns), Black carbon mass concentrations (BC), ultra-fine particle number concentrations, carbon dioxide along with GPS coordinates and relative humidity (RH) data collected by popular portable instruments (TSI DustTrak-8530, Aethlabs microAeth-AE51, TSI CPC3007, LICOR Li-830, Garmin GPSMAP 64s, Omega USB RH probe respectively). It incorporates device specific cleaning and correction algorithms. RH correction is applied to DustTrak PM2.5 following the Chakrabarti et al., (2004) . Provision is given to add linear regression coefficients for correcting the PM2.5 data (if required). BC data will be cleaned for the vibration generated noise, by adopting the statistical procedure as explained in Apte et al., (2011) , followed by a loading correction as suggested by Ban-Weiss et al., (2009) . For the number concentration data, provision is given for dilution correction factor (if a diluter is used with CPC3007; default value is 1). The package joins the raw, cleaned and corrected data from the above said instruments and outputs as a downloadable csv file.
How to cite:
Adithi R. Upadhya (2020). mmaqshiny: Explore Air-Quality Mobile-Monitoring Data. R package version 1.0.0, https://cran.r-project.org/web/packages/mmaqshiny. Accessed 20 Oct. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited mmaqshiny R package
View mmaqshiny citation profile
Other R packages that mmaqshiny depends, imports, suggests or enhances
Complete documentation for mmaqshiny
Functions, R codes and Examples using the mmaqshiny R package
Some associated functions: mmaqshiny-package . mmaqshiny_run . 
Some associated R codes: mmaqshiny-package.R . mmaqshiny_run.R .  Full mmaqshiny package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

conStruct  
Models Spatially Continuous and Discrete Population Genetic Structure
A method for modeling genetic data as a combination of discrete layers, within each of which relate ...
Download / Learn more Package Citations See dependency  
EvalEst  
Dynamic Systems Estimation - Extensions
Provides functions for evaluating (time series) model estimation methods. These facilitate Monte Ca ...
Download / Learn more Package Citations See dependency  
MOTE  
Effect Size and Confidence Interval Calculator
Measure of the Effect ('MOTE') is an effect size calculator, including a wide variety of effect siz ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
ISR  
The Iterated Score Regression-Based Estimation
Algorithm to handle with PCA-based missing data, where ISR is for PCA-based missing data with high c ...
Download / Learn more Package Citations See dependency  
bgeva  
Binary Generalized Extreme Value Additive Models
Routine for fitting regression models for binary rare events with linear and nonlinear covariate eff ...
Download / Learn more Package Citations See dependency  

29,080

R Packages

247,686

Dependencies

76,898

Author Associations

29,081

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA