# Devising Mobile Sensing and Actuation Infrastructure with Drones
## 1 Introduction  
Wireless sensor and actuator networks (WSAN) [1] consist of sensors and actuators that are usually supposed to have at least one wireless communication module to communicate with the sink node. The administrator can control the system by collecting the data from sensors, analyzing the data to generate actuation commands and sending them to the actuators. However, it is hardly feasible to combine independent and isolated WSANs into a new additional service network since sensors are tightly coupled with actuators. This tight coupling may result in the following: the actuation should correspond to the sensor data, and the actuator can affect the sensor data after the actuation, so that the actuator and the sensor may have a high spatial correlation. Furthermore, tight coupling is inevitable in traditional WSAN because sensing devices cannot freely create a network of heterogeneous devices due to their limited capabilities of communication and processing. Even if the technical aspect is excluded, many vendors operate both sensors and actuators together since they require appropriate sensing data for their service. On the other hand, a novel network paradigm, called the Internet of Things (IoT), has emerged recently. The paradigm should facilitate the communication of various existing networks with each other to collect data or deploy new services, so that general users are able to access anynetwork with their mobile devices much more easily. According to the Ericsson mobility report [2], the number of non-cellular-based machine-to-machine (M2M) devices will dramatically increase from 6.4 billion-17.4 billion from 2017-2023. Moreover, [3] notes that the IoT will be powered by a trillion sensors in 2020, and the IoT could provide an economic impact of 14 trillion by 2020. Following these statistical reports, WSAN could be one of the core infrastructures to implement the IoT. Additionally, new services in the paradigm demand separation between the sensor network and the actuator network [4; 5; 6; 7], which means that they decide the requirements for the service-related actuator or run it with sensing data obtained from different sensor networks. IoT service providers can increase the profitability of the service by using public sensor data [8; 9], rather than directly constructing sensor networks themselves. To satisfy this idea, using a mobile sink node, it is easy to collect public sensors' data on the IoT service providers part since the public sensor network does not have a sink node, but only broadcasts its sensing data. In the case of a disaster situation, mobile nodes in the disaster area need to be changed from normal mode to emergency mode, in which nodes broadcast their data because cellular communication may be unavailable. Assume a fire has broken out in a building. The sensor and actuator networks may be destroyed in the vicinity of the fire ignition point, and so, some part of them becomes isolated from the external network, such as the Internet, even if they are still alive. Thus, they cannot send any information to firefighters. Based on these observations, we can realize that there needs to be a system that can improvise a networking infrastructure among independent devices, systems, networks and even services in order to dynamically merge sensing and actuation infrastructure into an integrated service network and consequently enhance existing services [10; 11; 12] or forthcoming IoT services. To enable this concept, drones can be employed to implement such a system. The mobility and degree of freedom (DoF) of drones enables an instant deployment of networks into regions that are difficult to reach by humans or ground-based vehicles. Already, some research works [13; 14; 15; 16; 17; 18] have tried to adopt the unmanned aerial vehicle (UAV) as the mobile sink node, but these research works have focused on only implementing the drones in the sensor network and have not considered the advanced operation of the drones, such as dynamic path-planning and constructing a network among the drones.