# Integration of a Mobile Node into a Hybrid Wireless Sensor Network for Urban Environments +
## 1 Introduction  
Wireless sensor networks (WSNs) allow for the acquisition of information when proximity from the sensors to the phenomenon and persistence over time is required [1; 2]. WSNs have been applied to problems like logistics, traceability, emergency operations or urban environments [3; 4; 5; 6; 7]. In emergency response, WSNs can provide close monitoring with low cost, flexibility and scalability [8; 9], as well as way of integrating robot into rescue teams [10], as a step towards Cyber-Physical Systems (CPS) for first response [11; 12; 13]. In urban environments, WSNs can help monitoring power systems, solid waste or water facilities [14]. But traffic has attracted most of attention, since it is generally considered as one of the main problems affecting the health of city population [15]. The number of vehicles has grown notably in recent decades; as has pollution [16]. Pollution data are usually measured using an infrastructure of fixed sites. Such an infrastructure is limited, expensive and static. As a result, pollution and air quality data are limited [17; 18]. WSNs, on the contrary, are flexible and dynamic, and can be easily adapted to rural or urban environments. These features have made WSNs a valuablealternative for the way Intelligent Transportation Systems (ITSs) are implemented nowadays. ITSs are a way of improving transportation efficiency and safety [19], but also to save energy and to reduce emissions of vehicles [20] through a better management of available resources. But one of the obstacles to the implementation of new transport strategies is the limited amount of information on urban traffic WSNs provide a mean to improve the amount and quality of the data available for planning and management in ITSs [21; 22]. The effectiveness of WSNs depends strongly on the network coverage and connectivity provided by the sensor deployment [23; 24]. Even if sensor nodes are usually easy to install, once they have been placed they only way to improve the information they acquire is to add new nodes, or to re-deploy the existing ones. Thus, the strategy to select the locations of the nodes becomes a key feature for the performance of WSNs [25; 26; 27]. A complementary strategy is to provide mobility to the sensor nodes, for example by including a method for replacing the sensor nodes if they present a malfunction [28]. Another option is to mount the sensor nodes onboard vehicles or mobile robots [29; 30]. This approach is valid not only for urban applications, but also for other use-cases, like disaster robotics [6]. Mobility of the sensor nodes can be found in mobile ad hoc networks (MANETs), defined as a set of wireless mobile nodes characterized as self-adaptive and infrastructure-less [9]. In vehicular ad hoc networks (VANETs), or in general, in vehicular sensor networks (VSNs), moving vehicles and infrastructure become nodes of a dynamic network [20]. In general, a WSN including both static and mobile sensor nodes can be considered a Hybrid Wireless Sensor Networks (H-WSNs). Several authors have proposed VSNs for real-time data acquisition and monitoring [8; 31; 32; 33; 34; 35], including solutions like cloud computing [36], fog-based event monitoring [37] or high resolution maps in urban environments [38]. The existence of mobile nodes in VSNs (or, in general, in H-WSNs) can make difficult to ensure coverage. The development of a H-WSN must pay special attention to this feature [39]. A classical approach to design a WSN considers a flat architecture. However, this kind of network does not allow for applications with mobile nodes [40], since a constant reconfiguration of the network is then required [29]. A hierarchical architecture can improve performance in these cases [41; 42; 43], decreasing delays, while improving the reliability of data transmission and connectivity of the network [40]. However, special attention must be paid to the organization of the network [44; 45].