In this article, we put forward the paradigm of mobile crowd sensing based on ubiquitous wearable devices carried by human users. The key challenge for mass user involvement in prospective urban crowd sensing applications, such as monitoring of large-scale phenomena (e.g., traffic congestion and air pollution levels), is the appropriate sources of motivation. We thus advocate for the use of wireless power transfer provided in exchange for sensed data to incentivize the owners of wearables to participate in collaborative data collection. Based on this construction, we develop a novel concept of wirelessly powered crowd sensing and offer the corresponding network architecture considerations together with a systematic review of wireless charging techniques to support implementation. Further, we contribute a detailed system-level feasibility study that reports on the achievable performance levels for the envisioned setup. Finally, the underlying energy-data trading mechanisms are discussed, and the work concludes with outlining open research opportunities. crowd sensing in Future smArt cities towArd ubiquitous mobile crowd sensing For the first time in human history, over half of the global population lives in cities, and this astounding number of 3.7 billion people 1 is only expected to double by 2050. As urbanization creates increasingly larger cities, it requires more complex infrastructure to mitigate escalating social problems, including road congestion, air pollution, and public safety. Fueled by advanced monitoring for improved maintenance of critical urban infrastructure, the vision of a smart city materializes rapidly by relying on the integration of the Internet of Things (IoT) with information and communications technology (ICT). As advanced ICT facilitates collection of information from a plethora of data sources across the city, emerging IoT applications promise to revolutionize our daily lives by bringing along faster and more reliable emergency response, controlled outbreaks of serious diseases, as well as lower risk of multi-vehicle accidents, destructive weather events, and terrorist attacks. Pursuing these important goals, big cities were historically forced to deploy large-scale proprietary sensor networks and then rely on the legacy wireless sensor networking (WSN) technologies. However, the conventional WSN solutions have failed to proliferate widely in the real world, primarily due to their high installation and maintenance costs as well as limited coverage and scalability. Overcoming the limitations of commercial WSN deployments, the novel knowledge discovery paradigm of mobile crowd sensing (MCS) has recently emerged to extract information from a multitude of user-paired devices with limited sensing capabilities. Generally, leveraging the power of citizens for massive sensing may assume one of two forms [1] , opportunistic (autonomous data collection without direct involvement of participants) or participatory (with active interaction of humans who decide to contribute data). An evolution of participatory sensing, MCS engages individuals with their companion devices (e.g., mobile phones, smart vehicles, and wearables) into sharing contextual data and extracting relevant information to collectively measure and map large-scale phenomena of common interest [2] . The available information on users and their surrounding environment includes, but is not limited to, location, acceleration, temperature, noise level, traffic conditions, and pollution. By efficiently combining personal and collective data, future MCS applications may offer rich information on urban dynamics by generating knowledge about, for example, safety-related accidents, and thus provide dynamic situational awareness. The emerging vision of urban crowd sensing inherently relies on people who are, in essence, walking sensor networks. Beyond their sensor-rich handheld mobile equipment, increasingly widespread wearable devices are becoming major tools in collaborative data collection. Today's consumer wearables already have a variety of sensing, computing, and communication capabilities, as they feature a host of embedded sensors for determining information on location, positioning, activity, noise, environment, health, human social relationships, and even emotions. Powered by further miniaturization of sensing components [3] , novel classes of wearables promise to transform crowd sensing into a new global utility. However, before urban crowd sensing over wearables can truly take off, many research chal-
Galinina et al. REF conceptualized the idea of incentivizing the owners of wearables to participate in collaborative data collection by providing the energy for their devices using WPT.
Wirelessly Powered Urban Crowd Sensing over Wearables: Trading Energy for Data
IEEE Wireless Communications
IEEE Wireless Communications
Computer Science