Improvements in terms of smart device capabilities and of communication technologies allowed crowdsensing solutions to emerge as a powerful strategy to revolutionize environment sensing, becoming one of the key elements of future Smart Cities. In particular, smartphones, smartwatches, and other personal gadgets are now endowed not only with significant computing power and different wireless interfaces but also with an increasing number of sensors able to provide useful information about the user environment, especially when the user is moving around a city. If vehicular mobility is adopted, the sensing capabilities can be further increased by connecting smart devices to vehicles using the OBD-II interface or provided directly by smart vehicles through Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) communications. In the future, with the gradual introduction of autonomous vehicles and unmanned aerial vehicles, many more sensing alternatives are expected.

In parallel to these developments, network infrastructure has experienced significant improvements in recent years in terms of both coverage and performance which, combined with advances in cloud computing, allows transmitting, storing, and processing large amounts of data in an efficient manner. Altogether, the potential for generating and analyzing huge amounts of data is remarkable, being able to provide unprecedented information with high levels of spatial and time resolution about any event of interest occurring in a city.

The purpose of this special issue is to publish high-quality research papers addressing recent advances on mobile sensing, with particular emphasis on novel applications and architectures for crowdsensing and vehicle-based sensing. Original high-quality contributions that are not yet published or not currently under consideration by other journals or peer-reviewed conferences are sought.

Potential topics include, but are not limited to:

• Architectures and frameworks for crowdsensing and vehicular-based sensing
• Communications and networking for crowdsensing and vehicular-based solutions
• Context-aware crowdsensing
• Data retrieval and processing in crowdsensing environments
• Smartphone-based applications for crowdsensing
• Integration of crowdsensing solutions in the Smart City paradigm
• Floating content for information sharing in vehicular environments
• Vehicles as mobile sensors
• Context-aware data sensing and dissemination in vehicular environments
• Emerging sensing solutions using autonomous vehicles and unmanned aerial vehicles
• Cloud-based solutions for handling crowdsensing and vehicular-based sensing data