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

Crowdsourcing for Research: Perspectives From a Delphi Panel

Crowdsourcing, an open call for the public to collaborate and participate in problem solving, has been increasingly employed as a method in health-related research studies. Various reviews of the literature across different disciplines found crowdsourcing being used for data collection, processing, and analysis as well as tasks such as problem solving, data processing, surveillance/monitoring, and surveying. Studies on crowdsourcing tend to focus on its use of software, technology and online platforms, or its application for the purposes previously noted. There is need for further exploration to understand how best to use crowdsourcing for research, as there is limited guidance for researchers who are undertaking crowdsourcing for the purposes of scientific study. Numerous authors have identified gaps in research related to crowdsourcing, including a lack of decision aids to assist researchers using crowdsourcing, and best-practice guidelines. This exploratory study looks at crowdsourcing as a research method by understanding how and why it is being used, through application of a modified Delphi technique. It begins to articulate how crowdsourcing is applied in practice by researchers, and its alignment with existing research methods. The result is a conceptual framework for crowdsourcing, developed within traditional and existing research approaches as a first step toward its use in research

Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks

The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN

Digital Humanities: Community Participation in the Balinese Language Digital Dictionary

In recent years, the capability of Balinese people to write and speak their mother tongue has declined significantly among the younger generations because of the growing influence and adoption of the national language, Bahasa Indonesia.  It has spread rapidly among Balinese youth because it is considerably more straightforward than the Balinese language and is free of caste regulations.  In this paper, we present the details of our digital humanities preservation research dealing with the Balinese language.  We utilize community-based crowdsourcing to participate in expanding and enriching the BASABali Wiki digital dictionary in the form of an online competition. Ninety-six participants in 24 groups participated in our study, and their contribution populated 2686 new unique sentences to the BASABali Wiki digital dictionary. We also discuss the procedures employed to evaluate the digital dictionary: to receive feedback on the digital dictionary system and our approach to acquiring the knowledge of the community

Morphological Approach in Creative Requirements Elicitation from Crowdsourcing

Creativity is a subject that gained increasing interest in requirements engineering field. Creative-based requirements elicitation helps in generating requirements in original and innovative ways. Lately, crowdsourcing has been emerged in requirements elicitation after realizing the benefits of crowd. Crowdsourcing allows a wide diversity of stakeholders able to express their perceptions about product. However, to analyze the large amount of ideas from crowd would be a great challenge. This work focuses on how ideas gathered from the crowd and then analyzed using morphological approach in deriving requirements for the software product. Furthermore, the involvement of crowd in the approach helps in eliciting creative ideas for producing an innovative software product

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

Understanding information diversity in the era of repurposable crowdsourced data

Organizations successfully leverage information technology for the acquisition of knowledge for decision-making through information crowdsourcing, which is gathering information from a group of people about a phenomenon of interest to the crowdsourcer. Information crowdsourcing has been used to drive business insight and scientific research, providing crowdsourcers access to information outside their traditional reach. Crowdsourcers seek high-quality data for their information crowdsourcing projects and require contributors who can provide data that meet predetermined requirements. Crowdsourcers recruit contributors with high levels of relevant knowledge or train contributors to ensure the quality of data they collect. However, when crowdsourced data needs to fit more than a single usage scenario because the requirements of the project changed or the data needs to be repurposed for tasks other than the one(s) for which it was initially collected, the ability of contributors to provide diverse data that can meet multiple requirements is also desirable. In this thesis, I investigate how the domain knowledge a contributor possesses affects the diversity and quality of data they report. Using an experiment in which 84 students randomly assigned to three knowledge conditions reported information about artificial stimuli, I found that explicitly trained contributors provided less diverse data than either implicitly trained or untrained contributors. In addition, I looked at the longitudinal effect of knowledge on the diversity of data reported by contributors. Using review data from Amazon.com and organism sighting data from NLNature.com (a citizen science data crowdsourcing platform), I studied the impact of knowledge on the diversity and quality of crowdsourced data. The results show that experience reduced the diversity and usefulness of contributed data. The study provides insights for crowdsourcers in industry and academia on how to manage and utilize their crowds effectively to collect high-quality reusable data

Using crowdsourced geospatial data to aid in nuclear proliferation monitoring

In 2014, a Defense Science Board Task Force was convened in order to assess and explore new technologies that would aid in nuclear proliferation monitoring. One of their recommendations was for the director of National Intelligence to explore ways that crowdsourced geospatial imagery technologies could aid existing governmental efforts. Our research builds directly on this recommendation and provides feedback on some of the most successful examples of crowdsourced geospatial data (CGD). As of 2016, Special Operations Command (SOCOM) has assumed the new role of becoming the primary U.S. agency responsible for counter-proliferation. Historically, this institution has always been reliant upon other organizations for the execution of its myriad of mission sets. SOCOM's unique ability to build relationships makes it particularly suited to the task of harnessing CGD technologies and employing them in the capacity that our research recommends. Furthermore, CGD is a low cost, high impact tool that is already being employed by commercial companies and non-profit groups around the world. By employing CGD, a wider whole-of-government effort can be created that provides a long term, cohesive engagement plan for facilitating a multi-faceted nuclear proliferation monitoring process.http://archive.org/details/usingcrowdsource1094551570Major, United States ArmyMajor, United States ArmyApproved for public release; distribution is unlimited