# Feasibility Analysis of a LoRa-Based WSN Using Public Transport
## 1 Introduction  
The Internet of Things (IoT) refers to the network of different devices, designed to provide smart services and applications without the need of human intervention. It is one of the key technologies of the near future [1]. Essentially, IoT is a \"system\" where the network itself and all the connected devices have \"less of everything\": less memory, less processing power, less available bandwidth, less available energy etc. [2]. Notwithstanding, the set of sensors and devices connected to the IoT is continuously increasing. It has been estimated that 50 billion devices will be connected by 2020 [3]. IoT offers a wide range of possible applications. Actually, the basis of IoT is the pervasive, continuous, and efficient real data collection. Data can be acquired, transmitted, stored, and aggregated for different purposes [4; 5; 6]. The future will be a world where the objects will become \"smart\" and integrated into a large information network exploiting the global connectivity. Services will also be available to interact with these \"smart objects\", query and change their state and any information associated with them, taking into account security and privacy issues as well. The set of \"smart objects\" (both sensors and equipment) by which IoT is made of, constitutes a wide Distributed Measurement System (DMS) [7]. Among the infinite range of possibilities thatIoT is able to offer, one of the most important is related to implement smart cities, with pollution and environmental monitoring, and transportation control [8]. In particular, the real-time, efficient, and distributed monitoring of environmental pollution and meteorological parameters (such as temperature, atmospheric pressure, and humidity), also known as Environmental IoT (EIoT) [9], is one of the goals that most cities are trying to achieve for various purposes. Although standard observation stations have been used for decades, they present some limitations for measurements with a higher spatial resolution. Indeed, they pretend to monitor large areas but the collected data ends up being the average of numerous contributions, not allowing to precisely identifying critical zones (e.g., small and defined areas more subject to pollution problems) and not giving the possibility to improve the performances of the local meteorological and weather forecasting models. Of course, ad-hoc instrumented vehicles would be too expensive. However, it has been already proved that standard vehicles can be used as meteorological integrated sensors; they can be either properly equipped with a specific monitoring station [10; 11; 12] or they can even use the set of sensors currently installed on them [13]. A valid means to realize a capillary and distributed monitoring system is represented by the city's public transport fleet. In fact, according to the European Metropolitan Transport Authorities (EMTA) Barometer 2015, \(11^{\circ}\) Edition, public transportation covers, on average, an area of 1432 km\({}^{2}\) of urbanized surface [14], corresponding to the area that can be monitored. A report of, Italian National Institute of Statistics (ISTAT, Istituto Nazionale di Statistica) from Italy from 2015 shows that the public transport system has more than 200 vehicles distributed over the municipal territory of the biggest Italian cities (e.g., Milan, Turin) [15]. Continuously moving within the entire city area, vehicles are able to provide a near real-time map of air quality and environmental parameters as well as detailed statistics defining hourly and daily trends. Some experimental Wireless Sensor Networks (WSNs) for similar purposes were already proposed. For example, [16; 17] presents WSNs based on Zigbee. However, they are not based on Low Power Wide Area Network (LPWAN) technologies [2]. LoRa is only one of many LPWAN technologies.