Infrastructure Engineering - Research Publications
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ItemTranslating Place-Related Questions to GeoSPARQL Queries(ASSOC COMPUTING MACHINERY, 2022)Many place-related questions can only be answered by complex spatial reasoning, a task poorly supported by factoid question retrieval. Such reasoning using combinations of spatial and non-spatial criteria pertinent to place-related questions is increasingly possible on linked data knowledge bases. Yet, to enable question answering based on linked knowledge bases, natural language questions must first be re-formulated as formal queries. Here, we first present an enhanced version of YAGO2geo, the geospatially-enabled variant of the YAGO2 knowledge base, by linking and adding more than one million places from OpenStreetMap data to YAGO2. We then propose a novel approach to translate the place-related questions into logical representations, theoretically grounded in the core concepts of spatial information. Next, we use a dynamic template-based approach to generate fully executable GeoSPARQL queries from the logical representations. We test our approach using the Geospatial Gold Standard dataset and report substantial improvements over existing methods.
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ItemA Multi-Camera Tracker for Monitoring Pedestrians in Enclosed Environments(IEEE, 2020)Multi-camera pedestrians tracking is a challenging computer vision task. We propose a multi-camera tracker for monitoring pedestrians in an enclosed shopping environment. We assess the performance of the multi-camera tracker in a case study, tracking customers in a food and speciality market hall. Our multi-camera tracker tracks customers' walking between the stalls in the market. The information is useful for market management, visitor safety, and other potential application areas.
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ItemAnalysis of an Ad-hoc Platoon Formation and Dissolution Strategy on a Multi-lane Highway.(University of Auckland, 2019-01-01)Vehicle platooning has become popular in the recent Intelligent Transportation System (ITS) research. The literature typically assumes a planned formation and dissolution of platoons, mostly at source and destination. In contrast, this research considers platoons that can be formed on the fly. We investigate a greedy type of platoon formation with no particular order of destinations of the platoon members. This greedy formation allows a quick formation of the platoon but imposes an overhead of platoon rebuild cost when platoon members leave. The question arises whether this greedy formation and dissolution of platoons can preserve the original fuel benefit of platooning. To investigate this question, this research implements such a strategy and provides a generic guideline for fuel-efficient ad-hoc platooning
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ItemModelling Uncertainty of Single Image Indoor Localisation Using a 3D Model and Deep Learning(ISPRS, 2019-05-29)Many current indoor localisation approaches need an initial location at the beginning of localisation. The existing visual approaches to indoor localisation perform a 3D reconstruction of the indoor spaces beforehand, for determining this initial location, which is challenging for large indoor spaces. In this research, we present a visual approach for indoor localisation that is eliminating the requirement of any image-based reconstruction of indoor spaces by using a 3D model. A deep Bayesian convolutional neural network is fine-tuned with synthetic images generated from a 3D model to estimate the camera pose of real images. The uncertainty of the estimated camera poses is modelled by sampling the outputs of the Bayesian network fine-tuned with synthetic images. The results of the experiments indicate that a localisation accuracy of 2 metres can be achieved using the proposed approach.
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ItemPlace questions and human-generated answers: A data analysis approach(Springer, Cham, 2020-01-01)This paper investigates place-related questions submitted to search systems and their human-generated answers. Place-based search is motivated by the need to identify places matching some criteria, to identify them in space or relative to other places, or to characterize the qualities of such places. Human place-related questions have thus far been insufficiently studied and differ strongly from typical keyword queries. They thus challenge today’s search engines providing only rudimentary geographic information retrieval support. We undertake an analysis of the patterns in place-based questions using a large-scale dataset of questions/answers, MS MARCO V2.1. The results of this study reveal patterns that can inform the design of conversational search systems and in-situ assistance systems, such as autonomous vehicles.
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ItemInitial Analysis of Simple Where-Questions and Human-Generated Answers(LIPIcs, 2019)Geographic questions are among the most frequently asked questions in Web search and question answering systems. While currently responses to the questions are machine-generated by document/snippet retrieval, in the future these responses will need to become more similar to answers provided by humans. Here, we have analyzed human answering behavior as response to simple where questions (i.e., where questions formulated only with one toponym) in terms of type, scale, and prominence of the places referred to. We have used the largest available machine comprehension dataset, MS-MARCO v2.1. This study uses an automatic approach for extraction, encoding and analysis of the questions and answers. Here, the distribution analysis are used to describe the relation between questions and their answers. The results of this study can inform the design of automatic question answering systems for generating useful responses to where questions.
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ItemThe grass is greener on the other side: understanding the effects of green spaces on Twitter user sentiments(ACM Press, 2018)Green spaces are believed to improve the well-being of users in urban areas. While there are urban research exploring the emotional benefits of green spaces, these works are based on user surveys and case studies, which are typically small in scale, intrusive, time-intensive and costly. In contrast to earlier works, we utilize a non-intrusive methodology to understand green space effects at large-scale and in greater detail, via digital traces left by Twitter users. Using this methodology, we perform an empirical study on the effects of green spaces on user sentiments and emotions in Melbourne, Australia and our main findings are: (i) tweets in green spaces evoke more positive and less negative emotions, compared to those in urban areas; (ii) each season affects various emotion types differently; (iii) there are interesting changes in sentiments based on the hour, day and month that a tweet was posted; and (iv) negative sentiments are typically associated with large transport infrastructures such as train interchanges, major road junctions and railway tracks. The novelty of our study is the combination of psychological theory, alongside data collection and analysis techniques on a large-scale Twitter dataset, which overcomes the limitations of traditional methods in urban research.
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ItemActivity-based Mobility Profiling(ACM Press, 2018)Several studies have shown that the spatio-temporal mobility traces of human movements can be used to identify an individual. However, this work presents a novel framework for activity-based mobility profiling of individuals using only the temporal information. The proposed framework is conducive to model individuals' activity patterns in temporal scale, and quantifies the uniqueness measures based on certain temporal features of the activity sequence.
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ItemInternational Workshop on Social Space and Geographic Space(The University of Melbourne, 2007)Social agents are embedded in both social structures and in geographical space. The combination of social and geographic space has often been neglected. With few exceptions, social network theory ignores geographic space, and artificial intelligence studies often assume local societies without sophisticated conceptualisations of social networks. Yet the multiple embeddedness of actors in both physical and social space has important implications for understanding social behaviour. In many related research areas, there is a growing recognition that associations between social structure and geographical nearness may affect social systems and social behaviours. Research on the associations between social and geographic space occurs in disconnected scientific communities, including human geography, social network theory, and geographic agent-based simulation. The International Workshop on Social Space and Geographic Space aims to bring the social and the spatial disciplines together, to discover joint foundations in social and geographical theory, and to integrate approaches for modelling spatial context and social behaviour. Seven papers were selected for presentation at the workshop, out of twelve papers submitted. The chairs would like to acknowledge the support from the ARC Research Network on Spatially Enabled Social Sciences. Special thanks go to Lin-Jie Guan for typesetting these proceedings.
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ItemConsiderations for Efficient Communication of Route Directions( 2006)We can observe that people familiar with an environment give route directions of varying granularity to other locals. Such route directions are typically shorter than the turn based directions of current navigation services, and contain only references of high relevance to the wayfinder. Studying these route directions of varying granularity reveals that they are intended to be memorized, a property that requires a low cognitive workload of the wayfinder during their usage. The short-term memory span of humans imposes a limit on the amount and the structure of information communicated. We argue that route directions of varying granularity provide the means to respect these limits by efficient recoding.