## 3 Related Work  
The use of mobile devices, wireless sensor networks, and even the use of IoT-based systems to support urban first responses has been addressed by several researchers. Concerning incident detection, [PERSON] _et al_. [16] proposed an automatic mechanism for traffic accident detection and notification using smartphones. It delivers early alerts to particular emergency centers and thus accelerates the response process. Similarly, [PERSON] _et al_. [17] use cyber-physical elements (called intelligent guards) deployed in the physical infrastructure to deliver early alarms when an extreme event affects a certain urban area. Concerning the support for the first response process, [PERSON] _et al_. [18] propose a RFID-based solution to tag injured people, indicating their health condition before delivering them to a hospital. Several researchers propose the use of mobile ad hoc networks, usually implemented using WiFi, to provide communications support in disaster areas [17, 19, 20]. [PERSON] and [PERSON] [4] go a step further and introduce the concept of human-centric wireless sensor networks. They also show how HWSN-based solutions can be used to increase the information availability in the affected area, and thus allow first responders to make informed decisions. [PERSON] _et al_. [21] describes an IoT-inspired platform, which was designed to support emergency management systems. Although such a proposal is quite general, it allows us to see how the several components participating in the process can interact with one another to capture or disseminate shared information. [PERSON] _et al_. [22] propose a modified \"task-technology fit\" approach to help developers understand how the IoT technology can enhance the urban first response activities. This approach does not indicate how to design IoT solutions to support these operations, but it allows us to carry out the role of IoT technology in urban emergencies. [PERSON] _et al_. [23] propose an opportunistic human activity context recognition based on already deployed sensors, taking advantage of the increasing connectivity provided by these sensors and the IoT capability to support true ambient intelligent applications. In [24] the authors introduce a data management solution for IoT systems that are capable of generating a very large amount of data. The proposal follows a distributed data- and sources-centric approach. [PERSON] _et al_. [25] introduce a different approach to design user-centered IoT systems. The authors argue that a bidirectional processing mechanism between internal knowledge representation (human knowledge) and external knowledge representation (networks of objects), plus an uncertainty-driven arbitration mechanism that acts on this knowledge base, are foundational to the design of truly user-centered IoT systems. These computational principles, underpinned by an enriched understanding of the psychology and neuroscience of human learning, will significantly improve the user's experience in a variety of IoT scenarios. The IoT is becoming a challenging subject for researchers all over the world, as it provides infinite alternatives for developing applications for acquiring, processing and distributing data, information and knowledge. In [26] the authors introduce a new approach to integrate IoT and software-as-a-service (SaaS) model for logistic systems. They propose a framework to design logistic systems based on SaaS cloud computing and IoT technology that uses the cloud. Several initiatives in the European Union and the United States work towards device integration to support early detection of urban emergencies. For instance, Sensors ANYware (SANY) [27] is an initiative oriented to obtain an open standard for integrating already deployed sensor networks with those to be deployed in the future.