Temkov Slave, Cavkovski Pance, Lameski Petre, Zdravevski Eftim, Herzog Michael A, Trajkovik Vladimir
Ss Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, North Macedonia.
Magdeburg Faculty of Computer Science, Magdeburg-Stendal University of Applied Sciences, 39011 Magdeburg, Germany.
Data Brief. 2025 May 18;61:111683. doi: 10.1016/j.dib.2025.111683. eCollection 2025 Aug.
This paper introduces an extensive dataset on air pollution monitoring, collected through a crowd sensing IoT platform. The dataset contains real-time measurements of various pollutants, including PM, PM, NO, O, and CO, enriched with meteorological parameters such as temperature, humidity, and atmospheric pressure. Additionally, it includes noise level measurements, offering insights into urban noise pollution. The data, collected across multiple urban locations in Skopje, North Macedonia, spans from early 2018 to December 2024, providing both high spatial and temporal resolution. This dataset is a valuable resource for studying pollution trends, forecasting pollution levels, identifying pollution sources, and assessing the impact of urban planning on air quality. All in all, it supports research aimed at improving air quality and public health through data-driven decision-making and policy development.
本文介绍了一个通过群体感知物联网平台收集的关于空气污染监测的广泛数据集。该数据集包含各种污染物的实时测量数据,包括细颗粒物(PM)、可吸入颗粒物(PM)、二氧化氮(NO)、臭氧(O)和一氧化碳(CO),并丰富了温度、湿度和大气压力等气象参数。此外,它还包括噪声水平测量数据,有助于深入了解城市噪声污染。这些数据是在北马其顿斯科普里的多个城市地点收集的,时间跨度从2018年初到2024年12月,提供了高空间和时间分辨率。该数据集是研究污染趋势、预测污染水平、识别污染源以及评估城市规划对空气质量影响的宝贵资源。总而言之,它支持旨在通过数据驱动的决策和政策制定来改善空气质量和公众健康的研究。