In recent years, the evolution of urban environments, jointly with the progress of the Information and Communication sector, have enabled the rapid adoption of new solutions that contribute to the growth in popularity of Smart Cities. Currently, the majority of the world population lives in cities encouraging different stakeholders within these innovative ecosystems to seek new solutions guaranteeing the sustainability and efficiency of such complex environments. In this work, it is discussed how the experimentation with IoT technologies and other data sources form the cities can be utilized to co-create in the OrganiCity project, where key actors like citizens, researchers and other stakeholders shape smart city services and applications in a collaborative fashion. Furthermore, a novel architecture is proposed that enables this organic growth of the future cities, facilitating the experimentation that tailors the adoption of new technologies and services for a better quality of life, as well as agile and dynamic mechanisms for managing cities. In this work, the different components and enablers of the OrganiCity platform are presented and discussed in detail and include, among others, a portal to manage the experiment life cycle, an Urban Data Observatory to explore data assets, and an annotations component to indicate quality of data, with a particular focus on the city-scale opportunistic data collection service operating as an alternative to traditional communications.

The scarcity of parking spaces in cities leads to a high demand for timely information about their availability. In this paper, we propose a crowdsensed parking system, namely ParkCrowd, to aggregate on-street and roadside parking space information reliably, and to disseminate this information to drivers in a timely manner. Our system not only collects and disseminates basic information, such as parking hours and price, but also provides drivers insights of the real-time and future availability of parking spaces based on aggregated crowd knowledge. To improve the reliability of the information being disseminated, we dynamically evaluate the knowledge of crowd workers based on the veracity of their answers to a series of location-dependent point of interest (POI) control questions. We propose a logistic regression based method to evaluate the reliability of the crowd knowledge for real-time parking spaces information. Besides, a joint probabilistic estimator is employed to make inference of parking spaces' future availability based on crowdsensed knowledge. Moreover, to incentivise wider participation of crowd workers, a reliability based incentivisation method is proposed to reward workers according to their reliability and expertise levels. The efficacy of ParkCrowd for aggregation and dissemination of parking space information has been evaluated in both real-world tests and simulations. Our results show that the ParkCrowd system is able to accurately identify the reliability level of the crowdsensed information, estimate the potential availability of parking spaces with high accuracy, and be successful in encouraging participation of the more reliable crowd workers by offering them higher monetary rewards.

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Mobile peer to peer (P2P) networks offer a huge potential for distributed mobile P2P crowd services (MPCS), which enable data and computational tasks to be offloaded and executed directly between mobile devices. Similar to centralised mobile crowd services, such as mobile crowdsensing, incentivisation mechanisms are core to encouraging mobile users to participate in MPCS systems. However, due to the impact of task execution failures and unreliable behaviours of mobile users (particularly task requesters), it is a daunting task to design and implement an incentivisation mechanism to cater for the needs of MPCS systems. In this paper, we propose a fault-tolerant incentivisation mechanism (FTIM) for MPCS systems. With conditional payment strategies, FTIM is proven to accommodate the requirements of two important application scenarios by achieving mechanism properties such as incentive compatibility, economic efficiency, individual rationality, and weak budget balance. Moreover, to tackle the practical challenges in implementing FTIM in the real world, we design a MPCSToken smart contract to facilitate its service auction, task execution and payment settlement process. We implement the MPCSToken contract on Ethereum blockchain. Both real-world experiment and simulation results show that the system is cost effective for deployments and improves the overall mobile users' utility by exploring the opportunities offered by MPCS.