# Integration of a Mobile Node into a Hybrid Wireless Sensor Network for Urban Environments +
## 5 Conclusions  
A modular mobile node has been implemented, capable of using different sensors according to mission needs. The mobile node has been integrated with an existing static network, adding flexibility and range to it and transforming it into a Hybrid Wireless Sensor Network. Integration has avoided the need for multi-hop routing, which can reduce the operating lifetime of the nodes due to increased communication. Two different integration modes have been developed: local mode and networked mode. Data gathered with the mobile node have been presented to the user in real-time, by means of a Human-Machine Interface showing data from a database synchronizing the information gathered by the mobile node, which may include information from other static nodes as well. Finally, the system has been tested in real urban scenarios in a use-case of measurement of gas levels and environmental data. The tests have comprised both working modes: local and networked. In local mode, the database is updated only after all present Transmitter nodes have sent their data. The dynamics of the Mobile node is then driven by that of the slowest node. Results with the local mode have shown a limited amount of data, as expected. In particular, the slow dynamics of the CO\({}_{2}\) sensor has produced a low rate of new data arriving to the external database, and then to the user interface. In networked mode, an update of the database takes place every time that a Transmitter node captures data and sends it to the Receiver node. This strategy allows acquisition of a larger amount of data, as evidenced by the experiments carried out. The architecture is flexible enough to change easily the number and type of sensors. Experiments have been performed with different sets of sensors, showing no compatibility problems. The modular design of the Mobile node allowed an easy reconfiguration. The flexibility of the system makes it easy to be adapted to other use-cases, like search and rescue missions. The proposed system provides a vehicle with a tailored set of sensors, configured for the needs of the mission. The acquired data are accessible to other vehicles or participants of the mission, allowing collaborative efforts towards a Cyber-Physical System integrating sensors, vehicles or humans. Future lines of work advance in this direction. For instance, an improvement can be planning the motion of the Mobile node according to the acquired data, in order to get an improved coverage or amount of data. This line may be particularly interesting in other use cases, like emergency response. In this case, the set of sensors might be defined according to data gathered by the static part of the WSN, thanks to the modular architecture. Another future line of work includes the study of the robustness of the H-WSN, comparing its performance with a static WSN. Additionally, technologies like LoRaWAN can be an alternative to develop this kind of application. An interesting line is the evaluation of the performance of an alternative implementation based on a different technology, and its comparison with the approach proposed in this paper.