Geographical big data management and analysis in smart cities: the example of air quality

Abstract

With the development of information technologies, the data production style and the collected data volume have increased. With smart city applications, the importance of managing flowing from different data sources such as sensors, IoT, internet, wearable technologies and creating value from these data has increased. Today, traditional data storage and management approaches are insufficient for the management of large volumes and complex data collected, and a new approach has been born with the characteristics of big data such as volume, speed and diversity. Besides SQL-based databases, the NoSQL database provides flexible and scalable solution to manage unstructured data in response to this need. Such sample technologies were evaluated and displayed on the sensor obtained from air monitoring stations in the integration of geographic big data with GIS. Air Quality Index (AQI) was calculated in MongoDB on the NoSQL monitor. The average traffic density was calculated with the data obtained from traffic sensors close to air monitoring stations in GIS environment. According to the results, its relationship with air traffic has been determined.