# A Crowdsensing Platform for Monitoring of Vehicular Emissions: A Smart City Perspective
## 7 Conclusions and Future Works  
Pollution of the atmosphere is a problem both for the environment and for the health of living things. In view of this, it can be considered that the monitoring and efficient management of polluted areas in an urban environment are eminent requirements for the development of so-called smart cities, where vehicles represent one of the main polluting sources. The present work had the objective to present methods to estimate the quantity of carbon dioxide emitted by vehicles, referring to the value generated during the moment of combustion in the vehicle's engine. From these values, we could present analyses and estimates that are beneficial when planing and managing modern cities. Figure 4: Toyota Etios route pollutant emission heat map. The use of the two defined methods, namely \"mass air flow\" and \"speed density\", allows access to a larger number of vehicles to perform data collection, since it is common for vehicles to have only one of these two sensors. With the values of the quantities of CO2, we can obtain new results, such as the ones shown in Figure 4, which represent the emission mapping generated during a vehicle route. It shows that it is actually possible to explore the data collected from vehicles to aid in the creation of new solutions and tools. Such items can facilitate the sustainable development of urban centers and thus improve the quality of life for all. The results also showed that the developed solution can also be useful for traffic control systems in cities, since areas with a higher concentration of pollution usually comprise crossings, traffic lights, and congested regions (at specific times). In fact, regions with higher pollution rates may also indicate a higher concentration of cars or even that cars are moving slower (and potentially polluting more). Although crowdsensing for traffic monitoring is not a novelty and popular application tools such as Google Maps and Waze already perform such a service, they do not provide pollution information, and also, their data are not public and auditable. Then, the developed platform could also be used as a bases for an integrated and more comprehensive solution for traffic control and management, when additional information is also monitored from the vehicles. Another potential use of the platform is related to the maintenance of vehicles. The amount of CO2 emitted is directly linked to the combustion efficiency of the engine, i.e., if a vehicle releases very high amounts, it may be an indication that the vehicle has an electrical or mechanical problem, or even be indicative of the quality of the fuel used. It is also important to realize that some difficulties were encountered during the development of the platform, such as the ones met during the evaluation period of the application. Since it is not a controlled environment (as in a simulator), the connection is prone to errors that must be treated. This problem was solved by carrying out a pilot study with two cars, mitigating the errors. Another highlight is in relation to the number of vehicles evaluated, in addition to a single route analyzed. Finally, a number of proposals for future works can be envisioned. Initially, as mentioned before, the use of the platform as a supportive tool for other smart-city applications can be considered as a worthy research and development line. Moreover, the study and development of a strategy for calculating fuel content in flex-fuel vehicles are also expected with the aim of making emission calculations more precise, in the case of vehicles using combined fuels. Finally, the verification of the operation of the tool with other classes and models of cars should also be performed. Authors contributed equally to the development of this work, in different perspectives. All authors participated in the performed reviews of the literature, providing feedback for the brainstorm phases. The development of the modules was mostly conducted by [PERSON], [PERSON] and [PERSON]; [PERSON] and D.G.C.