
Martin TomkoUniversity of Melbourne | MSD · Department of Infrastructure Engineering
Martin Tomko
PhD.
Seeking PhD students in: spatial data science/causal analysis, spatial networks, geomorphological ML and viz (Unity)
About
165
Publications
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1,725
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Introduction
I am a spatial information scientist with a particular interest in computational methods supporting the analysis of urban environments (indoor, cities and beyond) for spatial communication.
Publications
Publications (165)
Background
Infectious diseases spread through inherently spatial processes. Road and air traffic data have been used to model these processes at national and global scales. At metropolitan scales, however, mobility patterns are fundamentally different and less directly observable. Estimating the spatial distribution of infection has public health u...
The ubiquity of personal sensing devices has enabled the collection of large, diverse, and fine-grained spatio-temporal datasets. These datasets facilitate numerous applications from traffic monitoring and management to location-based services. Recently, there has been an increasing interest in profiling individuals' movements for personalized serv...
The term between is frequently used to describe spatial arrangements of objects where one described core object is positioned in the space bounded by two or more peripheral objects. As such, the relation between involves spatial configurations of at least three spatial objects. However, most of the existing qualitative spatial reasoning models focu...
In everyday communication, where-questions are answered by place descriptions. To answer where-questions automatically, computers should be able to generate relevant place descriptions that satisfy inquirers’ information needs. Human-generated answers to where-questions constructed based on a few anchor places that characterize the location of inqu...
During the COVID-19 pandemic, evidence has accumulated that movement restrictions enacted to combat virus spread produce disparate consequences along socioeconomic lines. One explanation for this differential impact is the distribution of people into occupations that can be performed from home and may provide greater financial security. However, li...
Traffic analysis is crucial for urban operations and planning, while the availability of dense urban traffic data beyond loop detectors is still scarce. We present a large-scale floating vehicle dataset of per-street segment traffic information, Metropolitan Segment Traffic Speeds from Massive Floating Car Data in 10 Cities (MeTS-10), available for...
A key prerequisite for indoor wayfinding through verbal turn-by-turn route instructions is correctly identifying the origin of the requested route. Here, we show that the origin only needs to be specified down to a granularity that is dependent on the chosen grammar of the instructions when considering the geometric structure of the environment. Th...
Map-matching of trajectory data has widespread applications in vehicle tracking, traffic flow analysis, route planning, and intelligent transportation systems. Map-matching algorithms snap a set of trajectory points observed by a satellite navigation system to the most likely route segments of a map. However, due to the unavoidable errors in the re...
Long-range, low-power, wide-area network modulation technique (LoRa) is already used in a variety of fields, such as agriculture and healthcare, to reliably transmit a small amount of data above ground. Research measuring the reliability and signal strength of LoRa devices underground, however, is rare. The purpose of this study is to test the sign...
The use of information technologies for the public interest, such as COVID-19 tracking apps that aim to reduce the spread of COVID-19 during the pandemic, involve a dilemma between public interest benefits and privacy concerns. Critical in resolving this conflict of interest are citizens’ trust in the government and the risks posed by COVID-19. How...
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 k...
The examination of morality has a long-standing history in philosophy, but recent events, including the dramatic rise of computational technologies has expanded the field into a multidisciplinary study of ethics. With the global connectivity provided by the Internet, cyber ethics is unique due to rapid changes in technology and ever-changing ethica...
Existing question answering systems struggle to answer factoid questions when geospatial information is involved. This is because most systems cannot accurately detect the geospatial semantic elements from the natural language questions, or capture the semantic relationships between those elements. In this paper, we propose a geospatial semantic en...
The trend to equip information systems with question-answering capabilities raises the design problem of deciding which questions a system should be able to answer. Typical solutions build on mining human conversations or logs from similar systems for question patterns. For the case of questions about geographic places, we present a complementary a...
The growing interest in causal inference in recent years has led to new causal inference methodologies and their applications across disciplines and research domains. Yet, studies on spatial causal inference are still rare. Causal inference on spatial processes is faced with additional challenges, such as spatial dependency, spatial heterogeneity,...
During the COVID-19 pandemic, evidence has accumulated that movement restrictions enacted to combat virus spread produce disparate consequences along socioeconomic lines. We investigate the hypothesis that people engaged in financially secure employment are better able to adhere to mobility restrictions, due to occupational factors that link the ca...
Mapping the parking spaces in cities is desirable for reducing cruising time and congestion in the city. But map information regarding parking spaces is often missing or incomplete, due to the variety of their nature: marked or unmarked, on‐street or off‐street, or public, domestic or commercial. Hence, we develop a new method for mapping parking s...
When a person moves, the set of objects in their visual range changes. Hence, the set of objects perceived from a specific range of locations may be considered as a signature (possibly non-unique) of this region and be used for the localization of this person. In the case of fixed objects, the number of regions with a set of specific visible object...
Mapping urban parking spaces helps drivers to reduce their search and cruising for parking, thus reducing traffic, reducing emissions, and reducing total travel times. Mapped urban parking spaces can also be monitored for real-time occupancy information. But while many cities in Asia, Africa, and Latin America are experiencing a strong increase of...
Conversing about places with a computer poses a range of challenges to current AI.
Detection and correction of errors in map data based on spatial reasoning may be used to improve their quality. However, the majority of current spatial reasoning approaches are based on binary spatial relations and are not able to perform analyses involving more than two objects. This article proposes building accessibility analysis with the terna...
While tracking-data analytics can be a goldmine for institutions and companies, the inherent privacy concerns also form a legal, ethical and social minefield. We present a study that seeks to understand the extent and circumstances under which tracking-data analytics is undertaken with social licence-that is, with broad community acceptance beyond...
Assessing OpenStreetMap (OSM) data quality against authoritative data sources may not always be viable. This is primarily because of the multi-dimensional nature and heterogeneity of the maps, yet the activity is pivotal for targeted data cleansing and quality enhancement undertakings in these data sets. A salient facet of OSM, allowing contributor...
Understanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movement patterns across broad regions. Movement characteristics...
In response to the COVID-19 pandemic, many Governments are instituting mobile tracking technologies to perform rapid contact tracing. However, these technologies are only effective if the public is willing to use them, implying that their perceived public health benefits must outweigh personal concerns over privacy and security. The Australian fede...
In everyday communication, where-questions are answered by place descriptions. To answer where-questions automatically, computers should be able to generate relevant place descriptions that satisfy inquirers' information needs. Human-generated answers to where-questions constructed based on a few anchor places that characterize the location of inqu...
COVID-19 is highly transmissible and containing outbreaks requires a rapid and effective response. Because infection may be spread by people who are pre-symptomatic or asymptomatic, substantial undetected transmission is likely to occur before clinical cases are diagnosed. Thus, when outbreaks occur there is a need to anticipate which populations a...
Existing metonymy resolution approaches rely on features extracted from external resources like dictionaries and hand-crafted lexical resources. In this paper, we propose an end-to-end word-level classification approach based only on BERT, without dependencies on taggers, parsers, curated dictionaries of place names, or other external resources. We...
While tracking-data analytics can be a goldmine for institutions and companies, the inherent privacy concerns also form a legal, ethical and social minefield. We present a study that seeks to understand the extent and circumstances under which tracking-data analytics is undertaken with social licence — that is, with broad community acceptance beyon...
In response to the COVID-19 pandemic, many Governments are instituting mobile tracking technologies to perform rapid contact tracing. However, these technologies are only effective if the public is willing to use them, implying that their perceived public health benefits must outweigh personal concerns over privacy and security. The Australian fede...
All established models in transportation engineering that estimate the numbers of trips between origins and destinations from vehicle counts use some form of a priori knowledge of the traffic. This paper, in contrast, presents a new origin-destination flow estimation model that uses only vehicle counts observed by traffic count sensors; it requires...
This paper investigates the Cyber-Physical behavior of users in a large indoor shopping mall by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the mall operators. Our analysis shows that many users exhibit a high correlation between their cyber activities and their physical context. To find this correlation, we propo...
COVID-19 is highly transmissible and containing outbreaks requires a rapid and effective response. Because infection may be spread by people who are pre-symptomatic or asymptomatic, substantial undetected transmission is likely to occur before clinical cases are diagnosed. Thus, when outbreaks occur there is a need to anticipate which populations a...
Indoor localization, navigation and mapping systems highly rely on the initial sensor pose information to achieve a high accuracy. Most existing indoor mapping and navigation systems cannot initialize the sensor poses automatically and consequently these systems cannot perform relocalization and recover from a pose estimation failure. For most indo...
Understanding syntactic and semantic structure of geographic questions is a necessary step towards true geographic question-answering (GeoQA) machines. The empirical basis for the understanding of the capabilities expected from GeoQA systems are geographic question corpora. Available corpora in English have been mostly drawn from generic Web search...
Understanding syntactic and semantic structure of geographic questions is a necessary step towards true geographic question-answering (GeoQA) machines. The empirical basis for the understanding of the capabilities expected from GeoQA systems are geographic question corpora. Available corpora in English have been mostly drawn from generic Web search...
Indoor localization, navigation and mapping systems highly rely on the initial sensor pose information to achieve a high accuracy. Most existing indoor mapping and navigation systems cannot initialize the sensor poses automatically and consequently these systems cannot perform relocalization and recover from a pose estimation failure. For most indo...
Safety on roads is of uttermost importance, especially in the context of autonomous vehicles. A critical need is to detect and communicate disruptive incidents early and effectively. In this paper we propose a system based on an off-the-shelf deep neural network architecture that is able to detect and recognize types of unsigned (non-placarded, suc...
Safety on roads is of uttermost importance, especially in the context of autonomous vehicles. A critical need is to detect and communicate disruptive incidents early and effectively. In this paper we propose a system based on an off-the-shelf deep neural network architecture that is able to detect and recognize types of unsigned (non-placarded, suc...
Frequent, devastating emergencies As a consequence of the rapidly changing climate, devastating emergencies unfold more frequently, their consequences last longer and reach deeper. The Australian bushfire season 2019-2020 led to the largest non-war, domestic defense force deployment and evacuation in Australian history. The recurrent nature of emer...
This paper investigates the Cyber-Physical behavior of a user in a large indoor shopping center by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the center operators. Our analysis shows that many users exhibit high correlation between their cyber activities and physical context. To find this correlation, we propose...
Missing data in Volunteered Geographic Information (VGI) are an unavoidable consequence of the data collection by non-experts, guided by only vague and informal mapping guidelines. While various Missing Value Imputation (MVI) techniques have been proposed as data cleansing strategies, they have primarily targeted numerical data attributes in non-sp...
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...
Place is a central concept in geography and a topic of interest in the social sciences, urban planning, architecture, and most recently in information science. The notion of place has therefore been studied with different foci of interest. Consequently, heterogeneous terminologies, conceptualizations, models, and ontologies have been proposed to ca...
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 docu-ment/snippet retrieval, in the future these responses will need to become more similar to answers provided by humans. Here, we have analyzed human answering behavio...
In the absence of any global positioning infrastructure for indoor environments, research on supporting human indoor localization and navigation trails decades behind research on outdoor localization and navigation. The major barrier to broader progress has been the dependency of indoor positioning on environment-specific infrastructure and resulti...
In a typical data collection process, a surveyed spatial object is annotated upon creation, and is classified based on its attributes. This annotation can also be guided by textual definitions of objects. However, interpretations of such definitions may differ among people, and thus result in subjective and inconsistent classification of objects. T...
In this chapter, we present and discuss an adaptable cyberinfrastructure (e-Infrastructure) for urban research. We illustrate the benefits of a loosely coupled service-oriented architecture-based design pattern for the internal architecture of this e-Infrastructure. This is presented in the context of the Australian Urban Research Infrastructure Ne...
Understanding the association between customer demographics and behaviour is critical for operators of indoor retail spaces. This study explores such an association based on a combined understanding of customer Cyber (online), Physical, and (some aspects of) Social (CPS) behaviour, at the conjunction of corresponding CPS spaces. We combine the resu...
As users of mobile devices make phone calls, browse the web, or use an app, large volumes of data are routinely generated that are a potentially useful source for investigating human behavior in space. However, as such data are usually collected only as a by-product, they often lack stringent experimental design and ground truth, which makes interp...
This paper investigates the Cyber-Physical behavior of a user in a large indoor shopping center by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the center operators. Our analysis shows that many users exhibit high correlation between their cyber activities and physical context. To find this correlation , we propose...
A new ridesharing model called collaborative activity-based ridesharing is proposed to enhance not only overall matching rates but also the matches between preferred ride partners. By coalescing the merits of two recently suggested innovative ridesharing models-the social network-based ridesharing and the activity-based ridesharing-the new model le...
Over the last fifty years, research into street networks has gained prominence with a rapidly growing number of studies across disparate disciplines. These studies investigate a wide range of phenomena using a wealth of data and diverse analytical techniques. Starting within the fields of transport or infrastructure engineering, street networks hav...
Traffic is a highly dynamic environment and ephemeral changes to the on-road conditions
impact it continuously. Research in Autonomous Vehicles (AVs) is currently highly focused
on dynamic changes, due to the high safety requirements [12]. AVs must be able to detect
and respond appropriately to incidents. In a connected traffic data ecosystem [3],...