## 3 Materials and Methods
### Framework Description  
The graphical representation of the developed modular architecture is presented in Figure 2. The underlying components that drive the process of breaking news detection are described in short. Data propagation for automated, real-time drone coverage of breaking news events is presented as well. The concept was evaluated by collaborating closely with a focus group of active journalists that helped to form the outcome. Figure 2 depicts an overview of the implemented data flow. In the architecture, data collection starts upon their creation while monitoring several news feeds for events (A). An extensive effort was put into multi-source event gathering from (a) websites through data scraping and indexing, (b) written press such as newspapers through digitization and indexing, and (c) social media, television, and traditional radio through transcription, which is currently carried out by a news provider collaborator with the use of custom speech-to-text tools. News extracted by TV and radio is considered especially important. Many events may be firstly broadcast by these traditional media, as they still have faster access to specific news agencies. Each event is described as a single and independent data message, generated by a news feed. Such a data message, e.g., an article or a Twitter tweet, may imply one or multiple events, but in terms of news coverage, this can be considered as a single event requiring journalistic action. This initial process produces events to be propagated to the system after being enriched with additional information that allows categorization and management that will subsequently help to effectively query for events. Figure 1: The envisioned concept architecture of the proposed model [8]. Figure 2: Block diagram of the implemented data flow. Events enter the system utilizing a common bus (B), a communication channel that serves the purpose of conveying information while, at the same time, ensuring data integrity and avoiding data redundancy (buffered process). It can store data in an intermediate state for a specified amount of time that can range from minutes to several days. Events that exit the common channel are stored in a database (C) in a structured way that enables fast indexing and retrieval. Events are retrieved (D) as sets of filtered information for specified time windows/ranges and checked for correlation using a multi-step detection algorithm. The output is a number of real events, along with their statistics, marked as breaking news. For a drone to be able to interconnect with such a system and operate, geographical information is needed. This information is extracted using a separate, multi-stage algorithm (E) that takes into account location-related terms in the actual text of the event, as well as related imagery that can be retrieved from it. The system is integrated as a web application that can also accept UGC that enhances user experience. The framework consists of the modules shown in Figure 3, which outlines the conceptual architectural processes as described above. The innovation of this design lies in the ability of the system to continuously improve its performance, while also being able to handle each different input type independently by inserting new \"pluggable\" entities into the system (e.g., interaction with the devices of mobile journalists). Detailed information is given in the following subsections. Elaborating on the above, the main aim was to set up and configure a modular architecture, allowing each individual modality (radio, TV, newspaper, etc.) to be added and treated consistently, in the form of text and images. Hence, uniform text and image-derived metadata processing steps are introduced and deployed into an integrated framework. It has to be clarified that individual modules, feeding the framework with input data, are not fully optimized as part of this paper. Specifically, the back-end crawling service of a media monitoring collaborator was utilized and tested, representing a real-world scenario.