Sistemas de Transporte ESTACIÓN METROPOLITANO

Approaches

Even though Wireless Sensor Network monitoring approaches yield better spatial coverage and data resolution when compared to traditional fixed monitoring stations, it might also present limitation when required to produce a fine-grained pollution data on a per street (micro-scale) basis. For example, works in [15] and [16] as- sume that WSNs are used for monitoring of limited areas, whereas works in [14] and [17] use WSN to monitor specific locations in urban areas, such as for example the heavy-traffic location or remote places. Thus, in order to cover an entire urban area and enable the pollution micro-scale monitoring, fixed sensors should be installed inside every street, which still requires considerable investment in the infrastructure. Additionally, some of the WSN-based monitoring approaches assume the data pro-

cessed in a centralised manner is available to the public after certain period of time, which could bring a limitation in obtaining a near real-time information about the monitored pollution. For example, work in [14] assumes that the control centre re- freshes the pollution data every hour, whereas work in [15] provides an information about the pollution levels on a daily basis.

One of the major benefits of using VSN for the pollution monitoring is its cost- effectiveness as it allows using the existing vehicles for sensing purposes. Deploying a large number of such vehicles in an urban area with diverse mobility patterns could provide a detailed insight of the air quality in vast urban areas [20], and enable monitoring of some locations that otherwise could not be monitored with the fixed sensors. In case the vehicles are cars or buses, it is assumed that their on-board units are powered by the vehicles’ batteries [28], so there are no major limitations in terms of processing capabilities, battery and storage. However, some of their downsides include additional exhaustion of polluting gases in the air, their mobility can be constrained by a road configuration or in a case of buses, they can have the predefined routes. Alternatively, using the public bicycles as a mean of transportation is a growing trend in the populated urban areas, which can also be used for urban pollution monitoring. Unlike cars or buses, bicycles would have con- strained resources such as processing capability, battery, storage. However, bicycles are environment-friendly as they do not pollute the environment with exhaust gases like that is the case with cars and buses, and are more flexible in terms of mobil- ity as they can move not only on the roads, but also at the locations available to pedestrians.

Some of the works based on Vehicular Sensor Network such as [3], [18], [21], [24], [26] and [27] use cellular networks for the transmission of the pollution data to the central server. However, using cellular network for pollution data transmission could induce high operational costs that are required for the cellular connectivity (SIM cards and data plans). Works presented in [5], [20], [22] and [23] assume the vehicles collect and carry the pollution data to the access points (e.g. Wi-Fi, Static Sensor Nodes) where it is transferred to the central server. In these works, the

vehicles do not analyse the collected data to identify alarming levels of the pollution while they are on the move, and instead they have a role of carriers of the pollution data which is later processed in a centralised manner. However, in order to identify hazardous pollution levels in near real-time, it is desirable to have an access to the pollution data and to perform its analysis on the fly. According to [21], the access to such pollution data is still limited. Hence, there is a clear need to investigate a concept of decentralised pollution monitoring in which the vehicles with on-board units would be able to analyse the collected pollution data and to detect dangerous pollution levels in near real-time. The work in [22] assumes that buses equipped with sensors are moving in a controlled mobility fashion with a predefined fixed routes. In order to achieve monitoring of large urban areas, the controlled mobility of the vehicles would limit the spatial resolution of the collected pollution data. Thus, to obtain a higher spatial resolution of the pollution data, it is desirable that VSN monitoring solution is based on vehicles with more flexible movement like, for example public bicycles.

In contrast to the works presented in [3], [18], [20]-[24] where vehicles with on- board units or mobile phones with sensors collect sensor measurements, the work in [25] assumes that vehicle such as bicycle performs pre-processing of the sen- sor measurements. Even though the work in [25] assumes pre-processing of sensor measurements, it does not use these measurements to analyse the evolution of the pollution level over time. Instead, the collected measurements are spatially aggre- gated (calculating mean and median) for each traversed road segment. In order to achieve decentralised monitoring using bicycles with on-board units, it is necessary to have accurate pollution data which can be analysed to reveal variations of the pollution levels in near real-time. The sensor measurements could be additionally refined using some advanced techniques, such as for example filters, which is not present in work [25]. Filters have a task to produce estimates of the monitored pol- lution concentration that tend to be more accurate than the sensor measurements taken by devices of different accuracy levels. Also, additional advantage of using filters is that they can be used for predicting the state of the observed phenomenon

(e.g. pollution level) in case there is a lack of sensor measurements. These predicted values of the observed phenomenon can be further analysed to gain additional knowl- edge about that phenomenon (e.g. trend analysis of the pollution level). Finally, the work presented in [25] assumes using cumbersome hardware equipment which is composed of the back-pack that stores netbook computer, batteries and the rest of the proposed equipment, which could make driver’s ride difficult.