Abstract: The ever increasing population along with frequent weather changes is exposing humans to a greater number of problems. This attributes to the increase in the levels of risk. The culture of risk prevention and management is increasingly widespread – also due to the huge media coverage of such phenomena – but cities are complex systems where strict planning is ineffective. Despite the efforts to minimize the risk, disasters occur all the time: in order to have a good disaster response capacity, the need of an adequate awareness of the present and upcoming situation is clear. Current trends in emergency management are going in the direction of structured data collection as a tool to improve reaction time and to allow analyses through geoinformation and geostatistics. Such a problem emerged worldwide in huge events (e.g. the Haiti Earthquake in 2010), but the state of the art lacks solutions focused on communication and designed with the aim of satisfying these requirements. The IoT project tackles this problem. Although we propose a rather general solution, we consider as a reference case study flood emergencies in an urban setting, focusing on the city of Bangalore. We target the scenario of floods as they are fairly frequent in Indian cities, whilst at the same time being difficult to manage. Our project is concerned with exchange and availability of real time information among emergency coordinators: our solution is able to help them in analyzing data retrieved from various sources and identifying problems in order to react in a timely manner. We focus on both integration and visualization: we integrate real time data from different sources (e.g. a mobile app handed out to rescuers) and visualize them in a clear and coherent map developed with web technologies, so that it is possible to immediately answer questions such as “which are the most critical areas?” or “where are the rescue teams?”.
Keywords: Internet of things, LoRaWAN, RFID, Rest API, Flask framework, OpenStreet Maps
| DOI: 10.17148/IJARCCE.2019.81110