A crowdsensing method for water resource monitoring in smart communities

Crowdsensing aims to empower a large group of individuals to collect large amounts of data using their mobile devices, with the goal of sharing the collected data. Existing crowdsensing studies do not consider all the activities and methods of the crowdsensing process and the key success factors related to the process. Nor do they investigate the profile and behaviour of potential participants. The aim of this study was to design a crowdsensing method for water resource monitoring in smart communities. This study opted for an exploratory study using the Engaged Scholarship approach, which allows the study of complex real-world problems based on the different perspectives of key stakeholders. The proposed Crowdsensing Method considers the social, technical and programme design components. The study proposes a programme design for the Crowdsensing Methodwhich is crowdsensing ReferenceFrameworkthat includes Crowdsensing Processwith key success factors and guidelines that should be considered in each phase of the process. The method also uses the Theory of Planned Behaviour (TPB) to investigate citizens’intention to participate in crowdsensing for water resource monitoring and explores their attitudes, norms and perceived behavioural control on these intentions. Understanding the profiles of potential participants can assist with designing crowdsensing systems with appropriate incentive mechanisms to achieve adequate user participation and good service quality. A survey was conducted to validate the theoretical TB model in a real-world context. Regression and correlation analyses demonstrated that the attitudes, norms and perceived behavioural control can be used to predict participants’ intention to participate in crowdsensing for water resource monitoring. The survey results assisted with the development of an Incentive Mechanism as part of the Crowdsensing Method. This mechanism incorporates recruitment and incentive policies, as well as guidelines derived from the literature review and extant system analysis. The policies, called the OverSensepolicies, provide guidance for recruitment and rewarding of participants using the popular Stackelberg technique. The policies were evaluated using simulation experiments with a data set provided by the case study, the Nelson Mandela Bay Municipality. The results of the simulation experiments illustrated that the OverSenserecruitmentpolicycan reduce the computing resources required for the recruitment of participants and that the recruitment policy performs better than random or naïve recruitment policies. The proposed Crowdsensing Method was evaluated using an ecosystem of success factors for mobile-based interventions identified in the literature and the Crowdsensing Method adhered to a majority (90%) of the success factors. This study also contributes information systems design theory by proposing several sets of guidelines for crowdsensing projects and the development of crowdsensing systems. This study fulfils an identified need to study the applicability of crowdsensing for water resource monitoring and explores how a crowdsensing method can create a smart community

Convergence of Gamification and Machine Learning: A Systematic Literature Review

Recent developments in human–computer interaction technologies raised the attention towards gamification techniques, that can be defined as using game elements in a non-gaming context. Furthermore, advancement in machine learning (ML) methods and its potential to enhance other technologies, resulted in the inception of a new era where ML and gamification are combined. This new direction thrilled us to conduct a systematic literature review in order to investigate the current literature in the field, to explore the convergence of these two technologies, highlighting their influence on one another, and the reported benefits and challenges. The results of the study reflect the various usage of this confluence, mainly in, learning and educational activities, personalizing gamification to the users, behavioral change efforts, adapting the gamification context and optimizing the gamification tasks. Adding to that, data collection for machine learning by gamification technology and teaching machine learning with the help of gamification were identified. Finally, we point out their benefits and challenges towards streamlining future research endeavors.publishedVersio

Participatory Sensing and Crowdsourcing in Urban Environment

With an increasing number of people who live in cities, urban mobility becomes one of the most important research fields in the so-called smart city environments. Urban mobility can be defined as the ability of people to move around the city, living and interacting with the space. For these reasons, urban accessibility represents a primary factor to keep into account for social inclusion and for the effective exercise of citizenship. In this thesis, we researched how to use crowdsourcing and participative sensing to effectively and efficiently collect data about aPOIs (accessible Point Of Interests) with the aim of obtaining an updated, trusted and completed accessible map of the urban environment. The data gathered in such a way, was integrated with data retrieved from external open dataset and used in computing personalized accessible urban paths. In order to deeply investigate the issues related to this research, we designed and prototyped mPASS, a context-aware and location-based accessible way-finding system

Crowdsourcing as a support to solving complex problems in entrepreneurial settings

1Dottorato di Ricerca in Management (XXVIII ciclo), LUISS Guido Carli, Roma, 2017. Relatori: Prof. Francesco Rullani, Prof. Marion Poetz (Copenhagen Business School).openCrowdsourcing is a newly-developed field that has helped a number of organizations to solved complex problems concerning quantities of information and resource accessibility. Many entrepreneurs have utilized crowdsourcing to their benefit, bypassing traditional forms of fundraising in order to increase their probability of success. Paper 1 will look specifically at the ways in which crowdsourcing can perform such a role, supporting the entrepreneur through each phase of the entrepreneurial process. Paper 2 will expand on this idea by exploring the effects that crowdsourcing can have on a company’s performance. Looking specifically at data provided by AngelList, a popular crowdsourcing platform, we’ll attempt to analyze the benefits that the technology has had on businesses by comparing crowdsourcing-based investment paths to those of traditional investors. Specifically, we measured the performance of both traditional and crowdsourcing-base business ventures over a 2-year period, using data extracted from Mattermark. We aim to shed light, here, on the ability of crowdsourcing to produce better performance in the medium-term. Paper 3 will investigate the effects that crowd size and diversity can have on the performance of a crowdsourced venture. AngelList’s data set will be useful in unpacking the relationship between the volume and diversity of a syndicate’s backers to see how these attributes can be beneficial or detrimental to a firm. While a significant amount of research has been undertaken around this topic, we have found that there are many gaps in the available literature. Where researchers have written extensively about the potential for crowdsourcing to support the discovery, exploitation and execution of entrepreneurial opportunities, much of this literature does not take into account the nature of currently-used crowdsourcing platforms. Throughout each of these papers, we’ll attempt to expand into the territory left unexplored by existing research, paying specific attention to the individual attributes phase of the entrepreneurial model.openDottorato di Ricerca in ManagementBALDELLI, FEDERICOBaldelli, Federic

The Gamification of Crowdsourcing Systems: Empirical Investigations and Design

Recent developments in modern information and communication technologies have spawned two rising phenomena, gamification and crowdsourcing, which are increasingly being combined into gamified crowdsourcing systems. While a growing number of organizations employ crowdsourcing as a way to outsource tasks related to the inventing, producing, funding, or distributing of their products and services to the crowd – a large group of people reachable via the internet – crowdsourcing initiatives become enriched with design features from games to motivate the crowd to participate in these efforts. From a practical perspective, this combination seems intuitively appealing, since using gamification in crowdsourcing systems promises to increase motivations, participation and output quality, as well as to replace traditionally used financial incentives. However, people in large groups all have individual interests and motivations, which makes it complex to design gamification approaches for crowds. Further, crowdsourcing systems exist in various forms and are used for various tasks and problems, thus requiring different incentive mechanisms for different crowdsourcing types. The lack of a coherent understanding of the different facets of gamified crowdsourcing systems and the lack of knowledge about the motivational and behavioral effects of applying various types of gamification features in different crowdsourcing systems inhibit us from designing solutions that harness gamification’s full potential. Further, previous research canonically uses competitive gamification, although crowdsourcing systems often strive to produce cooperative outcomes. However, the potentially relevant field of cooperative gamification has to date barely been explored. With a specific focus on these shortcomings, this dissertation presents several studies to advance the understanding of using gamification in crowdsourcing systems

Analysis of Motivational Theories in Crowdsourcing Using Long Tail Theory: A Systematic Literature Review

Motivational theories have been extensively studied in a wide range of fields, such as medical sciences, business, management, physiology, sociology, and particularly in the natural sciences. These theories are regarded as crucial in motivating online workers to engage in crowdsourcing. Nevertheless, there is a dearth of research on an overarching review of these theories. We performed a systematic literature review of peer-reviewed published studies focusing on motivational theories to identify popular theories and risks associated with nascent theories presented over the last decade in crowdsourcing. Based on a review of 91 papers from the domain of the natural sciences, we identified 35 motivational theories. The long tail theory helped us to identify the contribution of major influencing theories in a crowdsourcing environment. The results justify the long tail theory based on the Pareto principle of 80/20, which underlines the 20% of the popular motivation theories, namely self-determination, expectancy-value, game, gamification, behavior change, and incentive theory, as a cause of 80%. Similarly, we discussed the risks associated with 10 theories presented over the long tail, which have a frequency equal to 2. Understanding the significant impact, approximately 80%, of widely recognized motivational theories and their role in risk identification is crucial. This understanding can assist researchers in optimizing their results by effectively integrating these theories

Crowdsourcing as a support to solving complex problems in entrepreneurial settings

Crowdsourcing is a newly-developed field that has helped a number of organizations to solved complex problems concerning quantities of information and resource accessibility. Many entrepreneurs have utilized crowdsourcing to their benefit, bypassing traditional forms of fundraising in order to increase their probability of success. Paper 1 will look specifically at the ways in which crowdsourcing can perform such a role, supporting the entrepreneur through each phase of the entrepreneurial process. Paper 2 will expand on this idea by exploring the effects that crowdsourcing can have on a company’s performance. Looking specifically at data provided by AngelList, a popular crowdsourcing platform, we’ll attempt to analyze the benefits that the technology has had on businesses by comparing crowdsourcing-based investment paths to those of traditional investors. Specifically, we measured the performance of both traditional and crowdsourcing-base business ventures over a 2-year period, using data extracted from Mattermark. We aim to shed light, here, on the ability of crowdsourcing to produce better performance in the medium-term. Paper 3 will investigate the effects that crowd size and diversity can have on the performance of a crowdsourced venture. AngelList’s data set will be useful in unpacking the relationship between the volume and diversity of a syndicate’s backers to see how these attributes can be beneficial or detrimental to a firm. While a significant amount of research has been undertaken around this topic, we have found that there are many gaps in the available literature. Where researchers have written extensively about the potential for crowdsourcing to support the discovery, exploitation and execution of entrepreneurial opportunities, much of this literature does not take into account the nature of currently-used crowdsourcing platforms. Throughout each of these papers, we’ll attempt to expand into the territory left unexplored by existing research, paying specific attention to the individual attributes phase of the entrepreneurial model.Crowdsourcing is a newly-developed field that has helped a number of organizations to solved complex problems concerning quantities of information and resource accessibility. Many entrepreneurs have utilized crowdsourcing to their benefit, bypassing traditional forms of fundraising in order to increase their probability of success. Paper 1 will look specifically at the ways in which crowdsourcing can perform such a role, supporting the entrepreneur through each phase of the entrepreneurial process. Paper 2 will expand on this idea by exploring the effects that crowdsourcing can have on a company’s performance. Looking specifically at data provided by AngelList, a popular crowdsourcing platform, we’ll attempt to analyze the benefits that the technology has had on businesses by comparing crowdsourcing-based investment paths to those of traditional investors. Specifically, we measured the performance of both traditional and crowdsourcing-base business ventures over a 2-year period, using data extracted from Mattermark. We aim to shed light, here, on the ability of crowdsourcing to produce better performance in the medium-term. Paper 3 will investigate the effects that crowd size and diversity can have on the performance of a crowdsourced venture. AngelList’s data set will be useful in unpacking the relationship between the volume and diversity of a syndicate’s backers to see how these attributes can be beneficial or detrimental to a firm. While a significant amount of research has been undertaken around this topic, we have found that there are many gaps in the available literature. Where researchers have written extensively about the potential for crowdsourcing to support the discovery, exploitation and execution of entrepreneurial opportunities, much of this literature does not take into account the nature of currently-used crowdsourcing platforms. Throughout each of these papers, we’ll attempt to expand into the territory left unexplored by existing research, paying specific attention to the individual attributes phase of the entrepreneurial model.LUISS PhD Thesi

State-of-the Art Study in Citizen Observatories : Technological Trends, Development Challenges and Research Avenues

Citizen science has rapidly spread in the last decades around the world as a genuine interactive and inclusive opportunity for engaging citizens in the continuous collection of data relevant for science, governance, businesses, communal living and individual concerns. The present–day abundance of ICT technologies has caused the proliferation of two data collection methods in this field: participatory (user-centric) and opportunistic (device-centric). As a result, citizen observatories have become big data systems, with large scale volumes of data that come and go to millions of users.; about any social or environmental phenomenon (e.g. transit, air or weather) and comes in different formats (e.g. XML, Plain Text, CSV) and through different platforms (e.g. websites, mobile apps, sensor networks). This study reviewed the last 10 years of citizen science literature through a systematic literature review. This study identified 108 citizen observatories, which were deeply studied and clustered to identify global and European trends in environmental applications, practices, engagement techniques and technology uses. Challenges and recommendations from the literature in the field were classified to understand the common present and future path for the discipline. Furthermore, a survey and interviews were applied to stakeholders in Finland to gain broader understanding of the field country–wise. This study, provides the first comprehensive insight of the broad scale of contemporary ICT enabled citizen observatories in social and environmental dimensions