## 1 Introduction  
Since the 1950s, emergency services have been operating in North America mostly through a unique three-digit number (e.g., 911) for easy memorization, allowing anyone at anytime to contact a call-taker located in a public safety answering point (PSAP). A PSAP is a facility at which emergency calls are received under the responsibility of a public authority [1]. From this facility, a diversity of first response institutions (FRIs) can be coordinated and dispatched, according to the type of reported emergency. Among the main FRIs, we can find police, medical services, or fire brigades. The first generation of 911 services used the public switched telephone network (PSTN) to receive alert callsin the PSAPs [2]. When cellular communications arrived, these services evolved to enhanced 911 (E-911), with the aim of incorporating and supporting calls made from mobile devices, which have different operation schemes and protocols relative to landlines [3]. The latest technological advances in communications have generated next-generation 911 (NG-911) services, which have enabled the use of Internet protocols for transmitting voice, video, and text messages for emergency communications [4]. These new emergency response services are operating in many countries around the world, including the Integrated Security Service ECU 911 (where ECU is an abbreviation for Ecuador), which began its operations in this country in 2012. All of these emergency services handle a large amount of information with complex geographical and temporal heterogeneities. The information stored in event databases (DBs) at each PSAP has mostly been used for generating numerical reports of events attended by each FRI in a descriptive form. However, it becomes clearer every day that many more benefits can be obtained by exploiting the dynamically stored data in order to provide service managers with efficient tools for analyzing the complex event dynamics and their interactions, rather than limiting ourselves to summary reports [5]. Thus, it seems possible to increase the quality and efficiency of the stored-data analysis by combining statistical, spatial, and temporal information for a better understanding of the attended emergencies, for generating useful reports, and for improving resource management [6; 7; 8]. This analysis will increase the response capacity of the FRIs, optimizing available resources, shortening response times, and helping to plan the response to similar events in the future on the basis of the analysis of historical data [9]. Therefore, this work proposes an analysis system to scrutinize the available information regarding emergencies attended by a PSAP. We used a set of techniques for the simple and effective representation of emergency events using statistical, temporal, and geographical analysis. The implemented model was oriented to obtain a statistical and spatial-temporal characterization of the continuous operation of FRIs. We designed the system and developed a case study by using the information of more than 1 million emergencies attended during 2014 by the E-911 PSAP of Quito, Ecuador. The selected and designed temporal analysis tools included seasonal representations and nonparametric confidence intervals (CIs), which allowed us to dissociate the main temporal components from transients. The spatial analysis tools included a straightforward event location over Google Maps and the detection of heat zones by means of bidimensional geographic Parzen windows with automatic width control in terms of scales and the number of events in a region of interest. Finally, statistical representations are used for jointly analyzing time and space in terms of the \"time-space slices\". This paper is organized as follows. Section 2 describes the emergency representation model and the operation of a PSAP. In Section 3, the behaviors of different FRIs are described, several examples of the emergencies attended during 2014 are analyzed, and the main results are explained and discussed.