<p>Istraživanje omogućuje potpunije razumevanje trenutnih potencijala i problema participacije u urbanom planiranju, uz ukazivanje na inovativne alate i kanale, kao i razvojne pravce koji mogu pružiti odgovore na probleme sa kojima se suočavamo. Tokom istraživanja ukazuje se na osnovne prednosti i nedostatke prakse, kao i šanse koje mogu doneti novi pristupi i tehnološki trendovi, poput angažovanja mase internet korisnika (eng. crowdsourcing) i lanca blokova (eng. blockchain).</p> / <p>The research provides a deeper understanding of the current participation<br />potentials and problems in urban planning while pointing to innovative tools<br />and channels, as well as future development directions that can provide<br />answers to the problems we face today. The research highlights the main<br />advantages and disadvantages of current practice, as well as the chances<br />that new approaches and technological trends such as crowdsourcing and<br />blockchain can bring in the participatory planning.</p>

Städer och infrastruktur är i ständig utveckling och arbetet att uppdatera befintlig och äldre data blir ett mödosamt och dyrt arbete. Lantmäteriet undersöker möjligheter att effektivisera samhällsprocessen med hjälp av 3D-data. Det är framförallt en lösning på en mer effektiv detaljplanering och byggprocess som önskas. Vi föreslår en metod där en äldre georeferering hos en 3D-modell utnyttjas för att uppdatera modellen med nytt objekt. Detta betyder att georefereringen ärvs från det äldre objektet. Syftet med studien är att utföra tester och avgöra om lägesosäkerhet som Lantmäteriet ställer som krav vid utförande av detaljmätning ka nuppnås. Kommer det nya objektet att ärva den äldre georefereringen, och vilken avvikelse går det att uppnå i relation mellan nytt objekt och äldre modell? Det nya objektet fotograferas med olika kameror för att simulera en imaginär men realistisk situation, där bilder har samlats in genom crowdsourcing och microtasks. En modell skapades över hus 45 Högskolan Gävle med hjälp av äldre bilder som fotograferats med en UAS. Fotograferingen skedde på 70 m flyghöjd, där även snedbilder har tagits med en lägre flyghöjd runt byggnaden. I programmet Agisoft PhotoScan användes bilderna för att skapa 3D-punktmoln och 3D-bildmodeller. Studien visar att nya objekt kan ärva georeferering från en äldre modell. Ett snitt från båda hörnen visar ett resultat över testmätningar visar en sammanlagd avvikelse i plan på 0,051 m och 0,041 m i höjd. Lantmäteriet ställer krav för detaljmätning med fyra standardnivåer. Där standardnivå 2 har som krav att en lägesosäkerhet på som mest 0,1 m ska kunna garanteras, en nivå som används för kommunaldetaljplanering och vid detaljplanering av tätort. Två olika tekniker används för att utföra mätningar, direkt i 3D-bildsmodell och direkt i 3D-punktmoln, mätningarna utförs även i 2D och i 3D. Det stora problemet med metoden är arbetstiden är väldigt stor, och att Agisoft PhotoScan har begränsningar och direkta problem när det ska användas för att utföra mätningar i en 3D-bildmodell.

Tato práce se zabývá technologiemi velkých dat v kontextu měření parametrů sítě. Popisuje téma velkých dat a jejich využití, představuje základní parametry sítě, jejich měření a metody zhodnocení. Vyhodnocuje RTR NetTest aplikaci, testovací proceduru a měřené parametry. Byla vytvořena skupina nástrojů pro posouzení základních kvantitativních parametrů mobilní sítě na základě dat z databáze RTR. Rozbor denního efektu shrnuje časovou proměnlivost sítě. Chování v prostoru je posouzeno binováním a shlukovou analýzou, současně se srovnáním řízeného testování a crowdsourcingu.

This master thesis is oriented on a problem of creating video and image annotations. This problem is solved by crowdsourcing approach. Crowdsourcing games were designed and implemented to make solution of this problem . It was proven by testing that these games are capable of creating high quality annotations. Launching these games on a larger scale could create large database of annotated videos and images.

Diese Arbeit soll dafür einen Überblick der verschiedenen Crowdsourcing-Ansätze liefern und die Anforderungen und Probleme des Crowdsourcing untersuchen. Dafür wird zunächst das Zusammenführen unterschiedlicher Datenbestände (data matching) betrachtet. Darauf folgt eine allgemeine Vorstellung des Crowdsourcing, um abschließend die unterschiedlichen Ansätze untersuchen zu können.

Application that combines crowdsourcing and gamification elements should be usable by as many passengers as possible, considering all the different smartphones available on the market and people with disabilities. Thus, most popular platforms for cross-platform mobile application development should be compared in order to choose the appropriate one for this project. Finally, application prototype should be further tested to gather more feedback about design and concept for improvements and future studies.  Such solution is not meant to replace current methods of information gathering, but instead should be one of the available tools.

<p>When humans delegate tasks---whether to human workers or robots---they do so either to trade money for time, or to leverage additional knowledge and capabilities. For complex tasks, however, describing the work to be done requires substantial effort, which reduces the benefit to the requester who delegates tasks. On one hand, human workers---e.g., crowd workers, friends or colleagues on social network, factory workers---have diverse knowledge and level of commitment, making it difficult to achieve joint efforts towards the requester's goal. In contrast, robots and machines have clearly defined capabilities and full commitment, but the requester lacks an efficient way to coordinate them for flexible workflows. </p><p> </p><p> This dissertation presents a series of workflows and systems to enable efficient work transfer to human workers or robots. First, I present BlueSky, a system that can automatically coordinate hundreds of crowd workers to enumerate ideas for a given topic. The latent structure of the idea enumeration task is decomposed into a three-step workflow to guide the crowd workers. Second, I present CoStory, a system that requests alternative designs from friends or colleagues by decomposing the design task into hierarchical chunks. Third, I present AdapTutAR, a system that delegates machine operation tasks to workers through adaptive Augmented Reality tutorials. Finally, I present Vipo, a system that allows requesters to customize tasks for robots and smart machines through spatial-visual programming. This dissertation demonstrates that decomposing latent task structure enables task delegation in an on-demand, scalable, and distributed way.</p>

Ethical, cheap, and scalable, purposeful games leverage player entertainment to incentivise contributors in language resourcing. However, discourse is scarce around the enjoyability of these games, whose playerbases are divided between a tiny minority of reliable contributors and a vast majority of inconsistent contributors. This study aims to deepen the discourse around design possibilities tailored to the unevenly contributing playerbases of such games by building on player-reported data to create three engaging personas and narrative scenarios. Using Pruitt and Grudin’s way of weighing feature suitability in persona-focused design, social incentives and majority voting are indicated as the most and least prominent features, respectively. Indeed, the weight of the primary persona, representing 3.5% of the playerbase, is 72%, more than double the combined weight, 56%, of the remaining 96.5% of the playerbase. Sticking to the original definition of purposeful games is essential for any gaming approach to crowdsourced data collection to remain ethical, cheap, and scalable.

Most engineering curricula in the United States include some form of major design project experiences for students, such as capstone courses or design-build-fly projects. Such courses are examples of project-based learning (PBL). Part of PBL is to prepare students—and future engineers—to deal with and prevent common project failures such as missing requirements, overspending, and schedule delays. <i>But how well are students performing once they join the workforce?</i> Unfortunately, despite our best efforts to prepare future engineers as best we can, the frequency of failures of complex projects shows no signs of decreasing. In 2020 only 53% of projects were on time, 59% within budget, and 69% met their goal, as reported by the Project Management Institute. If we want to improve success rates in industry projects, letting students get the most out of their PBL experience and be better prepared to deal with project failures before they join the workforce may be a viable starting point. <br><br>The overarching goal of this dissertation is to identify and suggest improvements to areas that PBL lacks when it comes to preparing students for failure, to investigate student behaviors that lead to project failures, and to improve these behaviors by providing helpful feedback to students. <br><br>To investigate the actions and behaviors that lead to events that cause failures in student projects, I introduced “crowd signals”, which are data collected directly from the students that are part of a project team. In total, I developed 49 survey questions that collect these crowd signals. To complete the first part of the dissertation, I conducted a first experiment with 28 student teams and their instructors in two aerospace engineering PBL courses at Purdue University. The student teams were working on aircraft designs or low-gravity experiments.<br><br><i>Does PBL provide sufficient opportunities for students to fail safely, and learn from the experience? How can we improve?</i> To identify areas that PBL may lack, I compared industry failure cause occurrence rates with similar rates from student teams in PBL courses, and then provided recommendations to PBL instructors. Failure causes refer to events that frequently preceded budget, schedule, or requirements failures in industry, and are identified from the literature. Through this analysis, I found that PBL does not prepare students sufficiently for situations where the failure cause missing a design aspect occurs. The failure cause is fundamentally linked to proper systems engineering: it represents a scenario where, for example, students failed to consider an important requirement during system development, or did not detect a design flaw, or component incompatibility. I provided four recommendations to instructors who want to give their students more opportunities to learn from this failure cause, so they are better prepared to tackle it as engineers. <br><br><i>Is crowdsourced information from project team members a good indicator of future failure occurrences in student projects?</i> I developed models that predict the occurrence of future budget, schedule, or requirements failures, using crowd signals and other information as inputs, and interpreted those models to get an insight on which student actions are likely to lead to project failures. The final models correctly predict, on average, 73.11±6.92% of budget outcomes, 75.27%±9.21% of schedule outcomes, and 76.71±6.90% of technical requirements outcomes. The previous status of the project is the only input variable that appeared to be important in all three final predictive models for all three metrics. Overall, crowdsourced information is a useful source of knowledge to assess likelihood of future failures in student projects. <br><br><i>Does targeted feedback that addresses the failure causes help reduce failures in student projects?</i> To improve student behaviors that lead to project failures, I used correlations between failure measures and the crowd signals as a guide to generate 35 feedback statements. To evaluate whether the feedback statements help reduce project failures in the student teams, I conducted a second experiment at Purdue University with 14 student teams and their instructors. The student teams were enrolled in aircraft design, satellite design, or propulsion DBT courses. The student teams were split in two treatment groups: teams that received targeted feedback (i.e., feedback that aimed to address the failure causes that the specific team is most prone to) and teams that received non-targeted feedback (i.e., feedback that is positive, but does not necessarily address the failure causes the specific team is most prone to). Through my analysis, I found that my targeted feedback does not reduce the failure occurrences in terms of any metrics, compared to the non-targeted feedback. However, qualitative evaluations from the students indicated that student teams who received targeted feedback made more changes to their behaviors and thought the feedback was more helpful, compared to the student teams who received non-targeted feedback.<br><br>

Crowdsourcing has become a popular choice for tackling problems that neither computers nor humans alone can solve with adequate speed, cost, and quality. However, instructing crowds to execute tasks in the manner expected by the requesters is challenging. It depends on not only requesters’ task design abilities but also workers’ understanding of the tasks. Task design bridges the communication gap between workers and requesters, which consists of instructions, payment, time limit on task, and the interface for workers to work on. It remains an underdeveloped but important topic that needs further exploration for improving crowdsourcing experience. My research studies task delivery from requesters to crowd workers. The goal is to improve the communication between the two and, in turn, increase accuracy of results and decrease variability due to differing interpretations and perspectives. Specifically, this dissertation presents a series of studies to show that high-quality results can be obtained from human workers through improved task design, by 1) designing incentives to recruit workers with the appropriate skills for given tasks, 2) designing unambiguous instructions to clearly express task requirements, 3) choosing the correct strategy to communicate the requisite task knowledge with workers, and 4) enhancing requesters’ ability to rapidly prototype Augmented Reality (AR) instructions. This dissertation demonstrates that crowdsourcing quality is improved when the tasks are communicated using mediums and structures that align with workers’ preference and utility