Geographic information retrieval in a mobile environment: evaluating the needs of mobile individuals

This paper describes research that aims to define the information needs of mobile individuals, to implement a mobile information system that can satisfy those needs, and finally to evaluate the performance of that system with end-users. First a review of the emerging discipline of geographic information retrieval (GIR) is presented as background to the more specific issue of mobile information retrieval. Following this, a user needs study is described evaluating the requirements of potential users of a mobile information system; the study finds that there is a strong geographic component to users' information needs. Next, four geographic post-query filters are described which attempt to represent the region of space associated with an individual's query made at some specific spatial location. These filters are spatial proximity (distance in space), temporal proximity (travel time), speed-heading prediction surfaces (likelihood of visiting locations) and visibility (locations that can be seen). Two of these filters — spatial proximity and speed-heading prediction surfaces — are implemented in a mobile information system and subsequently evaluated with users in an outdoor setting. The results of evaluation suggest that retrieved information to which post-query geographic filters have been applied is considered more relevant than unfiltered information, and that users find information sorted by spatial proximity to be more relevant than that sorted by a prediction surface of likely future locations. The paper closes with a discussion of the wider implications of these results for developers of mobile information systems and location-based services

A framework for cloud-based context-aware information services for citizens in smart cities

© 2014 Khan et al.; licensee Springer. Background: In the context of smart cities, public participation and citizen science are key ingredients for informed and intelligent planning decisions and policy-making. However, citizens face a practical challenge in formulating coherent information sets from the large volumes of data available to them. These large data volumes materialise due to the increased utilisation of information and communication technologies in urban settings and local authorities’ reliance on such technologies to govern urban settlements efficiently. To encourage effective public participation in urban governance of smart cities, the public needs to be facilitated with the right contextual information about the characteristics and processes of their urban surroundings in order to contribute to the aspects of urban governance that affect them such as socio-economic activities, quality of life, citizens well-being etc. The cities on the other hand face challenges in terms of crowd sourcing with quality data collection and standardisation, services inter-operability, provisioning of computational and data storage infrastructure. Focus: In this paper, we highlight the issues that give rise to these multi-faceted challenges for citizens and public administrations of smart cities, identify the artefacts and stakeholders involved at both ends of the spectrum (data/service producers and consumers) and propose a conceptual framework to address these challenges. Based upon this conceptual framework, we present a Cloud-based architecture for context-aware citizen services for smart cities and discuss the components of the architecture through a common smart city scenario. A proof of concept implementation of the proposed architecture is also presented and evaluated. The results show the effectiveness of the cloud-based infrastructure for the development of a contextual service for citizens