Umair ul Hassan

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Spatial crowd sourcing uses workers for performing tasks that require travel to different locations in the physical world. This paper considers the online spatial task assignment problem. In this problem, spatial tasks arrive in an online manner and an appropriate worker must be assigned to each task. However, outcome of an assignment is stochastic since(More)
The integration of sustainable thinking and performance within day-to-day business activities has become an important business need. Sustainable business requires information on the use, flows and destinies of energy, water, and materials including waste, along with monetary information on environment-related costs, earnings, and savings. Creating this(More)
Human computation systems are characterized by the use of human workers to solve computationally difficult problems. Expertise profiling involves assessment and representation of a worker’s expertise, in order to route human computation tasks to appropriate workers. This paper studies the relationship between the assessment workload on workers and the(More)
Assigning heterogeneous tasks to workers is an important challenge of crowdsourcing platforms. Current approaches to task assignment have primarily focused on content-based approaches, qualifications, or work history. We propose an alternative and complementary approach that focuses on what capabilities workers employ to perform tasks. First, we model(More)
Recent advances in web technologies allow people to help solve complex problems by performing online tasks in return for money, learning, or fun. At present, human contribution is limited to the tasks defined on individual crowdsourcing platforms. Furthermore, there is a lack of tools and technologies that support matching of tasks with appropriate users,(More)
Applications consuming data have to deal with variety of data quality issues such as missing values, duplication, incorrect values, etc. Although automatic approaches can be utilized for data cleaning the results can remain uncertain. Therefore updates suggested by automatic data cleaning algorithms require further human verification. This paper presents an(More)
This paper presents the risks and opportunities of big data and the potential social benefits it can bring. The research is based on an analysis of the societal impacts observed in a set of six case studies across different European sectors. These impacts are divided into economic, social and ethical, legal and political impacts, and affect areas such as(More)
There has been considerable efforts in modelling the semantics of Internet of Things and their specific context. Acquiring and managing metadata related to the physical devices and their surrounding environment becomes challenging due to the dynamic nature of environment. This paper focuses on managing metadata for Internet of Things with the help of(More)
This paper introduces the <i>flag-verify-fix</i> pattern that employs spatial crowdsourcing for city maintenance. The patterns motivates the need for appropriate assignment of dynamically arriving spatial tasks to a pool for workers on the ground. The assignment is aimed at maximizing the coverage of tasks spread over spatial locations; however, the(More)
Spatial crowdsourcing has emerged as a new paradigm for solving problems in the physical world with the help of human workers. A major challenge in spatial crowdsourcing is to assign reliable workers to nearby tasks. The goal of such task assignment process is to maximize the task completion in the face of uncertainty. This process is further complicated(More)