KU-MWQ: A Dataset for Monitoring Water Quality Using Digital Sensors

Water quality depends on many factors. Among them some factors have direct effect in maintaining minimum sustainable environment. The following dataset contains parameters of three basic water quality factors. Temperature, pH factor and Water Turbidity. Two sets of Arduino based digital sensors were used to measure data from two different depths of the water label. Data were collected from a fish pond within the premises of Khan Jahan Ali Hall, Khulna University. Data were recorded 24 hours continuously from 15 January 2020 to 22 January 2020. Recording rate was 1 set of data per minute in average. All the sensors collected data in parallel at the same time. An Arduino Mega microcontroller board acted as the central processing unit and recorded all the sensors’ data altogether. Data file contents: Data 1:: Sensor data for 30 cm.xlsx: Contains raw data from pH sensor, Temperature sensor and Turbidity sensor. This set of sensors was 30 cm underwater. This file has 9623 sets of data each set having 3 data samples from the corresponding sensors. Data arrangement is described below: Column 1: Date and time of data recording in the format of YYYY-MM-DD [hh]:[mm]:[ss]. Time is in 24-hour format. Data are identical for all files. Column 2: Data from Temperature sensor in °C. Temperature values have maximum two decimal places. Column 3: Data from pH sensor. pH values have maximum two decimal places. Column 4: Data from turbidity sensor in “NTU” unit. Data 2:: Sensor data for 60 cm.xlsx: Contains raw data from Temperature sensor and Turbidity sensor. This set of sensors was 60 cm underwater. This file has 9623 sets of data each set having 2 data samples from the corresponding sensors. Data arrangement is described below: Column 1: Date and time of data recording, same as the previous file. Column 2: Data from Temperature sensor in °C. Temperature values have maximum two decimal places. Column 3: Data from turbidity sensor in “NTU” unit. Row-wise data categorisation: Each row represents one set of data for that consecutive time of the day. Considering when the data were taken the rows can be divided into two groups, day time data and night time data. Row 2-116, 811-1445, 2170-2855, 3634-4410, 5156-5885, 6554-7189, 7833-8476, 9078-9624:: Contains day time data from 6:00am to 6:00pm. Row 117-810, 1446-2169, 2856-3633, 4411-5155, 5886-6553, 7190-7832, 8477-9077:: Contains night time data from 6:00pm to 6:00am. These data can also be categorised row-wise based on the wea