# A Multi-Technology Communication Platform for Urban Mobile Sensing
## 1 Introduction  
Technological progress over the recent decades, favored by developments in information and communication technology (ICT), has revolutionized the way people live their everyday lives. As a result, paradigms such as Internet of Things (IoT) have emerged. IoT is a paradigm where any everyday object can be equipped with both processing and communication capabilities in order to collect and exchange information between _things_, or the Internet [1]. By enabling interaction with such wide and diverse devices, this paradigm finds applications in many different domains. One domain of particular interest is the urban context, since the paradigm tries to address the problems caused by the rapid increase in population density. To confront this adversity, the availability of public resources as well as the quality of services offered to the citizens should increase, while the operational costs of public administration should tend to decrease, encouraging the fast deployment of the smart city concept [2; 3]. The smart city concept is the combination of the IoT paradigm in an urban context with the exploitation of ICT solutions [2]. Several core areas are covered by this paradigm. The smart environment [4; 5] is one of them: it tries to address concerns regarding environmental protection, lackof energy efficiency, poor usage of the natural resources, environmental pollution, and sustainable resource management, among others. A typical smart city scenario has to deal with an extensive number of sensors and data generators (some of which are placed in high mobile devices), deployed to collect and generate all types of information, which will increase the numbers of communicating machines, modifying the current scenario of human-centric communications. The consequence is an avalanche of mobile and wireless traffic information. The high heterogeneity and volatility of the network carries connectivity issues, such as long and variable delays, sparse and intermittent connectivity, high error rate, high latency, highly asymmetric data rate, or even a non-existent end-to-end connectivity [6]. Along with the necessity to have a low-cost infrastructure, and to overcome the issues associated with the network disruption, the concept of the delay-tolerant network [7] is usually adopted in these scenarios. Moreover, in a smart city environment, a large number of devices are battery-powered and located in remote areas where wired connectivity is hard to guarantee. However, these devices need to be connected to cloud applications that offer a broad vision of city management. Low-Power Wide-Area Network (LPWAN) technology can be a good option to meet these requirements [8]. The long-range (LoRa) network is also a relevant form of LPWAN technology due to its unique modulation [9], which makes it a very versatile form of technology that can be easily adapted to different types of environments and applications [10]. Besides, it is seen as an attractive solution for IoT and machine-to-machine (M2M) platforms since it operates in unlicensed bands. In this context, this work implemented and evaluated, through a real environment, a multi-technology opportunistic platform for environmental data gathering with respect to smart cities, considering both static and moving sensing elements, and both long- and short-range communication. The main contributions of this work can be summarized as follows:  
* The evaluation of a novel medium access control (MAC) protocol for LoRa networks with multiple gateways;
* The evaluation of two urban-centric forwarding decision strategies for an opportunistic delay-tolerant network supporting a mobile sensing network;
* The joint evaluation of long- and short-range communications granting the possibility of collecting heterogeneous information in a smart city;
* Conclusions about the feasibility of each platform's component, along with the overall platform performance. The remainder of this paper is organized as follows. Section 2 discusses the relevant related work.