Crowdsensing in Smart Cities: Overview, Platforms, and Environment Sensing Issues

Abstract

Evidence shows that Smart Cities are starting to materialise in our lives through the gradual introduction of the Internet of Things (IoT) paradigm. In this scope, crowdsensing emerges as a powerful solution to address environmental monitoring, allowing to control air pollution levels in crowded urban areas in a distributed, collaborative, inexpensive and accurate manner. However, even though technology is already available, such environmental sensing devices have not yet reached consumers. In this paper, we present an analysis of candidate technologies for crowdsensing architectures, along with the requirements for empowering users with air monitoring capabilities. Specifically, we start by providing an overview of the most relevant IoT architectures and protocols. Then, we present the general design of an off-the-shelf mobile environmental sensor able to cope with air quality monitoring requirements; we explore different hardware options to develop the desired sensing unit using readily available devices, discussing the main technical issues associated with each option, thereby opening new opportunities in terms of environmental monitoring programs.

Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, Chile

“…Despite these limitations, the integration of Wi-Fi microchips and internet of things (IoT) technology in recent years has improved the monitoring potential of low-cost sensors and provides an opportunity to achieve significant progress in the development of smart cities (Alvear et al 2018). In this study, we examined the field performance of a custom-built IoT air quality sensor prototype, which was developed within the framework of the citizen science project LoV-IoT, (http://www.…”

CitySpeed: A Crowdsensing-Based Integrated Platform for General-Purpose Monitoring of Vehicular Speeds in Smart Cities

“…In this context, innovative crowdsensing-based solutions are gaining attention, and may facilitate the manner in which large amounts of data are acquired and processed. As a result, this paradigm provides an effective resource that can accelerate some of the expected transformations promised by the construction of smart cities [5].…”

“…The paradigm is centered on the premise that a number of users can collaboratively and spontaneously provide some kind of data for further processing in applications, in a low-cost and potentially mobile way. For an increasing number of smart-city applications, crowdsensing-based approaches have been used as a reliable and efficient source of data [5].…”

“…The crowdsensing paradigm is based on the idea of "collaboration" [5]. In general, people using a particular service (e.g., a smartphone app) provide data and receive, in exchange, a "benefit"; for example, information about how to avoid roads with heavy traffic, or indications of where to shop cheaper.…”

“…Actually, this principle is self-beneficial, in the sense that people contribute data which may benefit themselves in different ways, and this "reward" is the main motivation for the adoption of such a paradigm by the users. Moreover, the principle of portability is largely exploited in modern crowdsensing-based applications, allowing different platforms to run the same application on multiple devices and to provide real-time data [5,11].…”