WLAN Location Sharing through a Privacy Observant Architecture

In the last few years, WLAN has seen immense growth and it will continue this trend due to the fact that it provides convenient connectivity as well as high speed links. Furthermore, the infrastructure already exists in most public places and is cheap to extend. These advantages, together with the fact that WLAN covers a large area and is not restricted to line of sight, have led to developing many WLAN localization techniques and applications based on them. In this paper we present a novel calibration-free localization technique using the existing WLAN infrastructure that enables conference participants to determine their location without the need of a centralized system. The evaluation results illustrate the superiority of our technique compared to existing methods. In addition, we present a privacy observant architecture to share location information. We handle both the location of people and the resources in the infrastructure as services, which can be easily discovered and used. An important design issue for us was to avoid tracking people and giving the users control over who they share their location information with and under which conditions

Temporal and Spatial Expansion of Urban LOD for Solving Illegally Parked Bicycles in Tokyo

The illegal parking of bicycles is a serious urban problem in Tokyo. The purpose of this study was to sustainably build Linked Open Data (LOD) to assist in solving the problem of illegally parked bicycles (IPBs) by raising social awareness, in cooperation with the Office for Youth Affairs and Public Safety of the Tokyo Metropolitan Government (Tokyo Bureau). We first extracted information on the problem factors and designed LOD schema for IPBs. Then we collected pieces of data from the Social Networking Service (SNS) and the websites of municipalities to build the illegally parked bicycle LOD (IPBLOD) with more than 200,000 triples. We then estimated the temporal missing data in the LOD based on the causal relations from the problem factors and estimated spatial missing data based on geospatial features. As a result, the number of IPBs can be inferred with about 70% accuracy, and places where bicycles might be illegally parked are estimated with about 31% accuracy. Then we published the complemented LOD and a Web application to visualize the distribution of IPBs in the city. Finally, we applied IPBLOD to large social activity in order to raise social awareness of the IPB issues and to remove IPBs, in cooperation with the Tokyo Bureau

A risk-based decision policy to aid the prioritization of unsafe sidewalk locations for maintenance and rehabilitation

Air pollution and a general concern for lack of physical activity in North America have motivated governments to encourage non-motorized modes of transportation. A key infrastructure component for these forms of transportation is sidewalks. The City of Saskatoon has identified the need to formalize sidewalk management policies to demonstrate diligence for community protection regarding sidewalk safety. Prioritization of sidewalk maintenance and rehabilitation actions must be objective and minimize risk to the community. Most research on prioritization of pedestrian facilities involved new construction projects. This research proposes a decision model that prioritizes a given list of existing unsafe sidewalk locations needing maintenance or rehabilitation using a direct measure of pedestrian safety, namely, quality-adjusted life years lost per year. A decision model was developed for prioritizing a given list of unsafe sidewalk locations, aiding maintenance and rehabilitation decisions by providing the associated risk to pedestrian safety. The model used data mostly from high quality sources that had already been collected and validated. Probabilities and estimations were used to produce value-added decision policy. The decision analysis framework applied probability and multi-attribute utility theories. This study differed from other research due to the inclusion of age and gender groups. Total average daily population of the city was estimated. This population was distributed to sidewalk locations using probabilities for trip purposes and a location’s ability to attract people relative to the city total. Then trip injury events were predicted. Age and gender distribution and trip injury type estimations were used to determine the impact of those injuries on quality of life.There exist much observable high quality data that can be used as indicators of unknown or unobserved events. A decision policy was developed that prioritizes unsafe sidewalk locations based on the direct safety impact on pedestrians. Results showed that quality-adjusted life years lost per year sufficiently prioritized a given list of unsafe sidewalk locations. It was demonstrated that the use of conditional probabilities (n=594) allowed for the ability to abstract data representing a different source population to another. Average daily population confined and distributed within the city boundary minimized problems of accuracy. Gender-age distribution was important for differentiating the risk at unsafe sidewalk locations. Concepts from this research provide for possible extension to the development of sidewalk service levels and sidewalk priority maps and for risk assessment of other public services