1 Input and format data
2 Data cleaning
- 2.1 Cleaning process
- 2.2 Save a copy of the cleaned data
3 Data summary and Visualisation

1 Input and format data

1.1 Processing Set Up

Specify directories and load libraries Smooth scatter plot example code from https://rstudio-pubs-static.s3.amazonaws.com/151690_ac65a180e03641e2adc3cb2ecf6306c3.html

## Loading required package: data.table

## Warning: package 'data.table' was built under R version 3.1.3

## Loading required package: RColorBrewer

## Warning: package 'RColorBrewer' was built under R version 3.1.2

## Loading required package: RSQLite

## Warning: package 'RSQLite' was built under R version 3.1.2

## Loading required package: DBI

## Warning: package 'DBI' was built under R version 3.1.2

1.2 Input data from the SQlite database

## [1] "channel"     "measurement"

## [1] TRUE

1.3 Assign column names and types and summarise the results

## $timestampStr
## [1] "character"
## 
## $timestampUnix
## [1] "integer"
## 
## $StationID
## [1] "character"
## 
## $PktID
## [1] "integer"
## 
## $Rawrssi
## [1] "integer"
## 
## $NoiseFloor
## [1] "integer"
## 
## $SignalToNoiseRatio
## [1] "integer"
## 
## $Timestamp
## [1] "POSIXct" "POSIXt"

## $timestampStr
## [1] "character"
## 
## $timestampUnix
## [1] "integer"
## 
## $StationID
## [1] "character"
## 
## $SensorID
## [1] "integer"
## 
## $WaterContent
## [1] "numeric"
## 
## $Temperature
## [1] "numeric"
## 
## $Timestamp
## [1] "POSIXct" "POSIXt"

2 Data cleaning

2.1 Cleaning process

adjust RSSI reading for SNR according to datasheet Remove rows with illegal values as follows:
Remove pre-deployment RSSIs (> -50 = MAXRSSI)
StationID is 1 to 5 (sensors from 1 to 8 are in the columns)
Soil moisture is volumetric water content as a percentage
Temperature from MINTEMP = -5 to MAXTEMP = 60 in soil

## [1] "49248 channel rows after data cleaning.  Removed 203 rows with illegal values"

## [1] "218733 measurement rows after data cleaning.  Removed 11250 rows with illegal values"

2.2 Save a copy of the cleaned data

3 Data summary and Visualisation

3.1 General Stats

## [1] 49248     9

## [1] "2018-09-09 08:44:45 WST" "2018-12-05 11:57:55 WST"

3.2 Transmission Summaries

## KernSmooth 2.23 loaded
## Copyright M. P. Wand 1997-2009

UWA Farm Underground LoRa data EDA for Receiver 2 (RPi)

Rachel Cardell-Oliver

7 December 2018

1 Input and format data

1.1 Processing Set Up

1.2 Input data from the SQlite database

1.3 Assign column names and types and summarise the results

2 Data cleaning

2.1 Cleaning process

2.2 Save a copy of the cleaned data

3 Data summary and Visualisation

3.1 General Stats

3.2 Transmission Summaries

3.3 RSSI per station

3.4 Soil moisture timeseries by station and sensor

3.5 Soil moisture measurement ranges