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. Any change in these parameters can affect them. Monitoring some of these mandatory water quality factors can help maintain water’s life sustainability. The following dataset contains parameters of three basic water quality factors. Temperature, pH factor and Water Turbidity. Arduino based digital sensors were used to collect these data. Two sets of sensors were used to measure data from different depth of the water label. Data were collected from a fish pond within the premises of Khan Jahan Ali Hall, Khulna University, 22.8054° N, 89.5370° E. It has an approximate area of 1350 square meter and depth of 3 meter. Data were recorded 24 hours continuously for 7 days, from 15 January 2020 to 22 January 2020. 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. Recording rate was 1 set of data per minute in average. The dataset has total 9623 sets of data. Each set has multiple data samples from the corresponding sensors. Data file contents: Data 1:: Sensor data for 30 cm.xlsx: Contains raw sensor data collected from the first set of sensors, data of pH sensor, Temperature sensor and Turbidity sensor. All the sensors were 30 cm below from the water surface. This file has 9623 set 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. 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 sensor data from the second set of sensors, data of Temperature sensor and Turbidity sensor. All the sensors were 60 cm below from the water surface. 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. Each row represents one set of data for that consecutive time of the day. Data samples were taken from a fixed place of the venue hence it represents the exact environmental condition of the place for that time period. Therefore this dataset can be used to determine environmental suitability of the local area for fish farming. Machine learning based projects can use this data for forecasting near future aquatic environmental condition. Such dataset can be also useful for unsupervised machine learning to detect anomalies