Climatic, population and daily water consumption dataset of sub tropical humid region of Pakistan

Seven years of water consumption data, along with population data, were manually collected in collaboration with the local municipality office. This data was then combined with climatic data to model the proposed machine learning algorithm. The weather data was recorded for a period of 7 years using precise meteorological instruments installed in Islamabad at coordinates 33.64° N and 72.98° E, with an elevation of 500 meters above sea level. The novel training dataset contains seven variables, providing daily information on population count, water consumption in cubic meters, ambient temperature, dewpoint temperature, percentage humidity, wind speed, and precipitation in inches, spanning seven years. This dataset offers valuable insights into the local population of selected sites and their water consumption, information that was not previously curated. The population data is categorized into two sub-groups: permanent residents and seasonal residents. Permanent residents reside in residential areas throughout the year, while seasonal residents live in the area for 8-10 months each year. The urban site selected for water consumption analysis in this dataset comprises three overhead tanks (OHTs) filled by nine different water pumps installed at distant locations. The data collection was carried out using the following instruments: 1. Campbell CS 215l: Used to record ambient temperature and relative humidity.2. NRG 40H Anemometer: Utilized for recording wind speed.3. Campbell CS 100: Employed for measuring barometric pressure. Overall, this dataset and the information gathered from the instruments will be instrumental in developing and improving the proposed machine learning algorithm for water consumption prediction and analysis.

七年的用水量数据及人口数据，在地方市政办公室的协作下，经人工收集而成。随后，这些数据与气候数据相结合，以构建所提议的机器学习算法。气象数据采用精确的气象仪器在伊斯兰堡（坐标为北纬33.64度，东经72.98度，海拔500米）记录，为期七年。新颖的训练数据集包含七个变量，提供每日的人口计数、立方米用水量、环境温度、露点温度、湿度百分比、风速以及英寸降雨量等信息，时间跨度为七年。该数据集为特定地点的本地人口及其用水量提供了宝贵的见解，此类信息此前未曾被整理。人口数据分为两大类：常住居民和季节性居民。常住居民全年居住在住宅区，而季节性居民每年在该地区居住8-10个月。在本数据集中，用于用水量分析的城市地点选择了三个由九个不同水泵（分别安装在遥远地点）填充的屋顶水箱（OHTs）。数据收集使用以下仪器进行：1. Campbell CS 215l：用于记录环境温度和相对湿度。2. NRG 40H风速仪：用于记录风速。3. Campbell CS 100：用于测量气压。总体而言，此数据集及从仪器收集到的信息将为开发和改进所提议的机器学习算法，以预测和分析用水量提供关键性支持。