Estimating Footfall From Passive Wi-Fi Signals: Case Study with Smart Street Sensor Project

Measuring the distribution and dynamics of the population at granular level both spatially and temporally is crucial for understanding the structure and function of the built environment. In this era of big data, there have been numerous attempts to undertake this using the preponderance of unstructured, passive and incidental digital data which are generated from day-to-day human activities. In attempts to collect, analyse and link these widely available datasets at a massive scale, it is easy to put the privacy of the study subjects at risk. This research looks at one such data source - Wi-Fi probe requests generated by mobile devices - in detail, and processes it into granular, long-term information on number of people on the retail high streets of the United Kingdom (UK). Though this is not the first study to use this data source, the thesis specifically targets and tackles the uncertainties introduced in recent years by the implementation of features designed to protect the privacy of the users of Wi-Fi enabled mobile devices. This research starts with the design and implementation of multiple experiments to examine Wi-Fi probe requests in detail, then later describes the development of a data collection methodology to collect multiple sets of probe requests at locations across London. The thesis also details the uses of these datasets, along with the massive dataset generated by the ‘Smart Street Sensor’ project, to devise novel data cleaning and processing methodologies which result in the generation of a high quality dataset which describes the volume of people on UK retail high streets with a granularity of 5 minute intervals since August 2015 across 1000 locations (approx.) in 115 towns. This thesis also describes the compilation of a bespoke ‘Medium data toolkit’ for processing Wi-Fi probe requests (or indeed any other data with a similar size and complexity). Finally, the thesis demonstrates the value and possible applications of such footfall information through a series of case studies. By successfully avoiding the use of any personally identifiable information, the research undertaken for this thesis also demonstrates that it is feasible to prioritise the privacy of users while still deriving detailed and meaningful insights from the data generated by the users

Movements in Cities: Footfall and its Spatio-Temporal Distribution

The contributors to this book, all from the Consumer Data Research Centre, provide a first consolidated statement of the enormous potential of consumer data research in the academic, commercial and government sectors - and a timely ..

Self-Organizing Networks in Complex Infrastructure Projects

While significant importance is given to establishing formal organizational and contractual hierarchies, existing project management techniques neglect the management of self-organizing networks in large-infrastructure projects. We offer a case-specific illustration of self-organization using network theory as an investigative lens. The findings have shown that these networks exhibit a high degree of sparseness, short path lengths, and clustering in dense “functional” communities around highly connected actors, thus demonstrating the small-world topology observed in diverse real-world self-organized networks. The study underlines the need for these non-contractual functions and roles to be identified and sponsored, allowing the self-organizing network the space and capacity to evolve

Geo-Design in Planning for Bicycling: An Evidence-Based Approach for Collaborative Bicycling Planning

In recent times, cities have increasingly promoted bicycling as a mode of transport as part of their strategy to develop a more sustainable transportation system. Australia is one of the countries that seeks to promote bicycling in a significant manner. There are two primary barriers faced in this effort. The first is the organizational complexity of planning and of implementing cycling-related projects, which can span across different agencies in government at various levels, from federal to local. Second is the lack of a clear framework for effectively planning a bicycling network using multiple data and tools available to these agencies within a limited budget. This study investigates the use of a geo-design-based, collaborative, and data-driven framework for planning bicycling networks, which brings various stakeholders, such as transport planners, urban designers, and academics, into the planning practice, thus overcoming the mentioned barriers. Geo-design is an environmental design framework for complex problems involving the collaboration of different teams and stakeholders, supported by digital computing and communication technologies. To the best of our knowledge, there is no study in the literature applying the geo-design approach for bicycling planning. Therefore, this study aims to develop and test a geo-design framework for planning bicycling networks to examine possible design scenarios and facilitate decision-making processes. In this regard, this study developed a geo-design framework for planning for bicycling using various bicycling-related datasets and digital tools, such as the Agent-Based Model. Then, it applied the framework to design a real-world bicycle network through a geo-design workshop while examining the usefulness and effectiveness of the developed procedures and tools. Policymakers attended the geo-design workshop from the local government authority of the case study area, Penrith, and post-graduate level urban planning students from UNSW. Due to COVID-19-related restrictions, the workshop was held in a hybrid format, with half of the participants joining online. The results of this study revealed that by facilitating collaboration and applying data-driven approaches, the proposed geo-design bicycling framework could improve the process of planning for bicycling infrastructure. This study also enabled the research team to understand the strengths and limitations of the developed framework and associated tools, which will help to optimize them for other planning practices in the future

Geo-Design in Planning for Bicycling: An Evidence-Based Approach for Collaborative Bicycling Planning

In recent times, cities have increasingly promoted bicycling as a mode of transport as part of their strategy to develop a more sustainable transportation system. Australia is one of the countries that seeks to promote bicycling in a significant manner. There are two primary barriers faced in this effort. The first is the organizational complexity of planning and of implementing cycling-related projects, which can span across different agencies in government at various levels, from federal to local. Second is the lack of a clear framework for effectively planning a bicycling network using multiple data and tools available to these agencies within a limited budget. This study investigates the use of a geo-design-based, collaborative, and data-driven framework for planning bicycling networks, which brings various stakeholders, such as transport planners, urban designers, and academics, into the planning practice, thus overcoming the mentioned barriers. Geo-design is an environmental design framework for complex problems involving the collaboration of different teams and stakeholders, supported by digital computing and communication technologies. To the best of our knowledge, there is no study in the literature applying the geo-design approach for bicycling planning. Therefore, this study aims to develop and test a geo-design framework for planning bicycling networks to examine possible design scenarios and facilitate decision-making processes. In this regard, this study developed a geo-design framework for planning for bicycling using various bicycling-related datasets and digital tools, such as the Agent-Based Model. Then, it applied the framework to design a real-world bicycle network through a geo-design workshop while examining the usefulness and effectiveness of the developed procedures and tools. Policymakers attended the geo-design workshop from the local government authority of the case study area, Penrith, and post-graduate level urban planning students from UNSW. Due to COVID-19-related restrictions, the workshop was held in a hybrid format, with half of the participants joining online. The results of this study revealed that by facilitating collaboration and applying data-driven approaches, the proposed geo-design bicycling framework could improve the process of planning for bicycling infrastructure. This study also enabled the research team to understand the strengths and limitations of the developed framework and associated tools, which will help to optimize them for other planning practices in the future

Usefulness of an Urban Growth Model in Creating Scenarios for City Resilience Planning: An End-User Perspective

Urban growth models are increasingly being used to generate scenarios within city and regional planning support systems (PSS). However, their usefulness in land use planning applications, particularly in city resilience planning, is not fully understood. Thus, we developed a cellular automata model using Metronamica PSS for the Greater Sydney region and assessed its usefulness as perceived by planning and policy practitioners. The study was implemented through a collaborative geodesign workshop where participants (n = 19) were guided to an understanding of the modelling process and to create and validate alternative policy scenarios for 2050 that reflected Business-As-Usual, Bushfire resilience, Flood resilience, and Combined resilience. We conducted two surveys and a SWOT analysis to assess the usefulness of the PSS and its outputs. We found that the PSS created credible scenarios using collaborative inputs from the participants. The PSS had perceived value for informing participants about land use changes in the resilience planning contexts with high flexibility and granularity. The plausibility of the scenario outputs, a usefulness parameter, was readily accepted, but the model’s transparency (another parameter) was seen as potentially inhibiting application in real-world planning. Future research should involve a broader audience, including the local community, in analysing the usefulness of PSS