Rational coordination of crowdsourced resources for geo-temporal request satisfaction

Existing mobile devices roaming around the mobility field should be considered as useful resources in geo-temporal request satisfaction. We refer to the capability of an application to access a physical device at particular geographical locations and times as GeoPresence, and we pre- sume that mobile agents participating in GeoPresence-capable applica- tions should be rational, competitive, and willing to deviate from their routes if given the right incentive. In this paper, we define the Hitch- hiking problem, which is that of finding the optimal assignment of re- quests with specific spatio-temporal characteristics to competitive mobile agents subject to spatio-temporal constraints. We design a mechanism that takes into consideration the rationality of the agents for request sat- isfaction, with an objective to maximize the total profit of the system. We analytically prove the mechanism to be convergent with a profit com- parable to that of a 1/2-approximation greedy algorithm, and evaluate its consideration of rationality experimentally.Supported in part by NSF Grants; #1430145, #1414119, #1347522, #1239021, and #1012798

Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges

Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.Comment: Updated version, 4/25/201

Integrating Spatial Data Infrastructures (SDIs) with Volunteered Geographic Information (VGI) creating a Global GIS platform

Spatial Data Infrastructures (SDIs) are a special category of data hubs that involve technological and human resources and follow well defined legal and technical procedures to collect, store, manage and distribute spatial data. INSPIRE is the EU’s authoritative SDI in which each Member State provides access to their spatial data across a wide spectrum of data themes to support policy-making. In contrast, Volunteered Geographic Information (VGI) is one type of user-generated geographic information (GI) where volunteers use the web and mobile devices to create, assemble and disseminate spatial information. There are similarities and differences between SDIs and VGI, as well as advantages and disadvantages to both. Thus, the integration of these two data sources will enhance what is offered to end users to facilitate decision-making. This idea of integration is in its early stages, because several key issues need to be considered and resolved first. Therefore, this chapter discusses the challenges of integrating VGI with INSPIRE and outlines a generic framework for a global integrated GIS platform, similar in concept to Digital Earth and Virtual Geographic Environments (VGEs), as a realistic scenario for advancements in the short term

Scholarometer: A Social Framework for Analyzing Impact across Disciplines

The use of quantitative metrics to gauge the impact of scholarly publications, authors, and disciplines is predicated on the availability of reliable usage and annotation data. Citation and download counts are widely available from digital libraries. However, current annotation systems rely on proprietary labels, refer to journals but not articles or authors, and are manually curated. To address these limitations, we propose a social framework based on crowdsourced annotations of scholars, designed to keep up with the rapidly evolving disciplinary and interdisciplinary landscape. We describe a system called Scholarometer, which provides a service to scholars by computing citation-based impact measures. This creates an incentive for users to provide disciplinary annotations of authors, which in turn can be used to compute disciplinary metrics. We first present the system architecture and several heuristics to deal with noisy bibliographic and annotation data. We report on data sharing and interactive visualization services enabled by Scholarometer. Usage statistics, illustrating the data collected and shared through the framework, suggest that the proposed crowdsourcing approach can be successful. Secondly, we illustrate how the disciplinary bibliometric indicators elicited by Scholarometer allow us to implement for the first time a universal impact measure proposed in the literature. Our evaluation suggests that this metric provides an effective means for comparing scholarly impact across disciplinary boundaries. © 2012 Kaur et al

BLOCKCHAIN-ENABLED INFORMATION AS A SERVICE AND OPTIMAL FULFILMENT CAPACITY BALANCING IN CYBER PLATFORM-DRIVEN CROWDSOURCED MANUFACTURING

As a new emerging manufacturing paradigm, platform-driven crowdsourced manufacturing utilizes the cooperation between the platform, designer, and service providers to configure and fulfill the supply chain. In this value creation and delivery process, the cyber platform enables and manages the interaction between each participant in the supply chain to respond to varieties of customer needs which lets platform-driven crowdsourced manufacturing become a persuasive approach to seeking manufacturing solutions. This thesis examines platform-driven crowdsourced manufacturing based on two unique perspectives: Information as a Service (IaaS) fulfillment and operational excellence of the platform. From the first perspective, this thesis analyzes the use case of the cyber platform in the platform-driven crowdsourced manufacturing system based on its workflow. An IaaS fulfillment system is designed based on the analysis using blockchain and distributed file-sharing technologies. The proposed system is distributed, which fulfills IaaS by providing secured information upload, sharing, and management services. The decentralization feature of the system reduces the cost of trust for using the system. From the perspective of operational excellence, the thesis models the interactions between users and their decision-making process in the system based on ECC game theory, population dynamics, and the Moran process. Based on the models, an optimization strategy is proposed to manage the fulfillment capacity balance by facilitating the participation level of users.M.S

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

A Service-Oriented Approach to Crowdsensing for Accessible Smart Mobility Scenarios

This work presents an architecture to help designing and deploying smart mobility applications. The proposed solution builds on the experience already matured by the authors in different fields: crowdsourcing and sensing done by users to gather data related to urban barriers and facilities, computation of personalized paths for users with special needs, and integration of open data provided by bus companies to identify the actual accessibility features and estimate the real arrival time of vehicles at stops. In terms of functionality, the first "monolithic" prototype fulfilled the goal of composing the aforementioned pieces of information to support citizens with reduced mobility (users with disabilities and/or elderly people) in their urban movements. In this paper, we describe a service-oriented architecture that exploits the microservices orchestration paradigm to enable the creation of new services and to make the management of the various data sources easier and more effective. The proposed platform exposes standardized interfaces to access data, implements common services to manage metadata associated with them, such as trustworthiness and provenance, and provides an orchestration language to create complex services, naturally mapping their internal workflow to code. The manuscript demonstrates the effectiveness of the approach by means of some case studies

Virtually (re)constructed reality: the representation of physical space in commercial location-based games

Location-based games (LBGs) are based on digital representations of our surroundings and the spaces we inhabit. These digital twins of the real world, real world metaverses, are subsequently augmented by imaginary game content. However, the virtual reconstruction of the world inevitably emphasises some aspects of reality and disregards others. In this work we explore and discuss the elements of reality that are included, and omitted, in popular commercial LBGs. We focus on eight popular contemporary LBGs from five different developers and investigate their connections to the real world. Subsequently, we compare the identified real world features of the LBGs to the landscape dimensions of the widely adopted Landscape Character Assessment framework. The findings show that settlement, hydrology, climate and land cover are the most commonly incorporated landscape dimensions, albeit in low fidelity. By contrast, dimensions, such as geology, soils and enclosure were not represented in the observed LBGs. In addition, we discovered several anthropogenic and cultural aspects, such as land ownership and time depth that are implicitly included in some commercial LBGs, notably in the Niantic Wayfarer system providing unique high-fidelity data of cultural and historical locations. Overall, we find only little variance within landscape dimensions between the observed commercial LBGs. Our findings open discussions on choices regarding the virtual representation of the real world in systems, such as LBGs, navigational software and a reality-based metaverse