The correct estimation of ambulance travel time is an extremely important issue from the perspective of healthcare and the security of citizens. In some events, the threat to the health or life of an injured person increases with each minute of waiting for an ambulance. The authors of this article analyzed how ambulances travel throughout the entire Lesser Poland voivodeship in southern Poland. Based on the analysis of 300 million GPS records that were collected over several years from 300 ambulances, real ambulance speed characteristics were compiled for the most important cities in the region. The obtained results regarding ambulance speed characteristics were used to understand the correlation between ambulance speed, the density of the road network, and the built-up areas of a given city. Furthermore, the impact on the speed of ambulances of traffic, time of day, day of the week, or the season was also examined. The influence of the use of ambulances’ lights/sirens on travel time was also examined. The culmination of the research was the presentation of the theoretical foundations of coverage maps and a method of implementing them based on the determined speed characteristics. The presented studies show that the speed at which ambulances move is a very local phenomenon. Also, a relatively constant average speed of ambulances throughout the whole week was found. Moreover, a difference in speed between signaled and non-signaled ambulance trips was observed. The speed characteristics that were obtained were used as input data for the development of dynamic coverage maps, which are an invaluable tool for supporting the decisions of ambulance dispatchers.

Crowdsourcing is one of the spatial data sources, but due to its unstructured form, the quality of noisy crowd judgments is a challenge. In this study, we address the problem of detecting and removing crowdsourced data bias as a prerequisite for better-quality open-data output. This study aims to find the most robust data quality assurance system (QAs). To achieve this goal, we design logic-based QAs variants and test them on the air quality crowdsourcing database. By extending the paradigm of urban air pollution monitoring from particulate matter concentration levels to air-quality-related health symptom load, the study also builds a new perspective for citizen science (CS) air quality monitoring. The method includes the geospatial web (GeoWeb) platform as well as a QAs based on conditional statements. A four-month crowdsourcing campaign resulted in 1823 outdoor reports, with a rejection rate of up to 28%, depending on the applied. The focus of this study was not on digital sensors’ validation but on eliminating logically inconsistent surveys and technologically incorrect objects. As the QAs effectiveness may depend on the location and society structure, that opens up new cross-border opportunities for replication of the research in other geographical conditions.

The article is composed of two sections. In the first section, the authors describe the application of minimum line dimensions which are dependent on line shape, width and the operational scale of the map. The proposed solutions are based on the Euclidean metric space, for which the minimum dimensions of Saliszczew’s elementary triangle (Elementary triangle – is the term pertaining to model, standard triangle of least dimensions securing recognizability of a line. Its dimensions depend on scale of the map and width of the line representing it. The use of a triangle in the simplification process is as follows: triangles with sides (sections) on an arbitrary line and bases (completing the sides) are compared with lengths of the shorter side and the base of the elementary triangle.) were adapted. The second part of the article describes an application of minimum line dimensions for verifying and assessing generalized data. The authors also propose a method for determining drawing line resolution to evaluate the accuracy of algorithm simplification. Taking advantage of the proposed method, well-known simplification algorithms were compared on the basis of qualitative and quantitative evaluation. Moreover, corresponding with the methods of simplified data accuracy assessment the authors have extended these solutions with the rejected data. This procedure has allowed the identification of map areas where graphic conflicts occurred.

Contemporary monitoring systems are a source of data streams. Processing of this data is an interesting issue from both a performance and data storage perspective. It is worth paying attention to the concept of stream database management systems, which are a hybrid that allows for efficient analysis of the data stream and provide a set of implemented statistical methods. This article presents the issues raised by embankment monitoring systems, a sensor network which generates a large stream of measured signals that should be analyzed in real-time. Warning or crash scenarios are also generated which are compared to the incoming data. A model of this data is presented and a construction of stream data analysis is proposed.