Redefining the Use of Big Data in Urban Health for Increased Liveability in Smart Cities

“Quarantined within a quarantine”

When the Australian state and lone isle of Tasmania went into coronavirus disease 2019 (COVID-19) quarantine lockdown in March, within a quarantine-imposed Australian continent, thinking it was being very prudent, unforeseen was the lurking virus. Australia across January had been watching the global northern hemisphere scenario occurring and by February was preparing to quarantine itself, echoing its existing and long-term biosecurity exclusion regime. On a much grander scale, following through on a previously trialed national pandemic training exercise, no one had factored in the Ruby Princess variable and its major consequences that would require unprecedented pandemic response. The concentrated impact of cruise ship virus dissemination and escalation has been palpable across the world, but the Ruby Princess will remain a disaster in Australia's history. For Tasmania, several elderly passengers retraveled from Sydney to Tasmania, and a minor cluster has occurred. This chapter contextualizes what has been transpiring in Australia with the pandemic, with particular attention upon Tasmania, including discussion about the new COVIDSafe.App, and then explains the potential application of a Systems Dynamics Modeling exercise of the COVID-19 spread, in collaboration with a custom-built 2D/3D geographic information system (GIS) Dynamic Scenario Planning Model to spatially visualize potential “what-if” scenarios of COVID-19 spread (and other future pandemics) to identify high-risk areas and vulnerable communities in the northern areas of Tasmania that is aiding real-time pattern mapping and preparation work and to further consider and enable the most effective emergency response and recovery scenarios.

Big Data and the United Nations Sustainable Development Goals (UN SDGs) at a Glance

The launch of the United Nations (UN) 17 Sustainable Development Goals (SDGs) in 2015 was a historic event, uniting countries around the world around the shared agenda of sustainable development with a more balanced relationship between human beings and the planet. The SDGs affect or impact almost all aspects of life, as indeed does the technological revolution, empowered by Big Data and their related technologies. It is inevitable that these two significant domains and their integration will play central roles in achieving the 2030 Agenda. This research aims to provide a comprehensive overview of how these domains are currently interacting, by illustrating the impact of Big Data on sustainable development in the context of each of the 17 UN SDGs.

Pandemic stricken cities on lockdown. Where are our planning and design professionals [now, then and into the future]?

Chinese cities have been placed upon lockdown in early 2020 in an attempt to contain the novel coronavirus (COVID-19), as increasingly huge demands are being placed upon Chinese and international health professionals to address this pandemic. Surprisingly, planning and design professionals are absent in the discourses about existing and post-COVID-19 strategies and actions even though previous pandemics historically revealed major impacts on the urban fabric from social and economic perspectives. This paper is a call for action for international architectural and urban organisations to include pandemics and similar in their disaster management strategies. This need is very evident in their need to better design creative and relevant protocols in partnership with health discipine organisations, and so that their applied deployment in pandemic stricken cities can be effected integrated seamlessly within normal city environment planning activities and also in incident situations like containing the current COVID-19 pandemic.

Artificial Intelligence (AI) Provided Early Detection of the Coronavirus (COVID-19) in China and Will Influence Future Urban Health Policy Internationally

Predictive computing tools are increasingly being used and have demonstrated successfulness in providing insights that can lead to better health policy and management. However, as these technologies are still in their infancy stages, slow progress is being made in their adoption for serious consideration at national and international policy levels. However, a recent case evidences that the precision of Artificial Intelligence (AI) driven algorithms are gaining in accuracy. AI modelling driven by companies such as BlueDot and Metabiota anticipated the Coronavirus (COVID-19) in China before it caught the world by surprise in late 2019 by both scouting its impact and its spread. From a survey of past viral outbreaks over the last 20 years, this paper explores how early viral detection will reduce in time as computing technology is enhanced and as more data communication and libraries are ensured between varying data information systems. For this enhanced data sharing activity to take place, it is noted that efficient data protocols have to be enforced to ensure that data is shared across networks and systems while ensuring privacy and preventing oversight, especially in the case of medical data. This will render enhanced AI predictive tools which will influence future urban health policy internationally.

The Potential of RES in the Reduction of Air Pollution: The SWOT Analysis of Smart Energy Management Solutions for Krakow Functional Area (KrOF)

Health impacts and a decrease in the quality of life caused by air pollution is a major problem worldwide. Krakow is one of the most affected cities in the EU by air pollution mostly caused by burning solid fuels in households’ furnaces. It is considered that the most effective remedies would be adequate spatial planning solutions and application of low-emission sources including renewable energy sources (RES). This article draws from the analysis of the use of RES as a means for reducing harmful emissions in Krakow Functional Area (KrOF). The inventories of renewable energy sources and systems were compiled by the authors as a part of the EU project “Smart Edge—Sustainable Metropolitan Areas and the Role of The Edge City”. Using the data from the inventories, a SWOT analysis has been carried out to identify factors that determine the smart management of the RES potential, particularly the decisions of households on the transition towards RES. The results of the analysis have shown that many actions have been taken at the national, regional, and local levels but the greatest influence bear the solutions initiated and implemented at the communal level. The conclusion is that legislative regulations should be combined with locally tailor-made instruments. The proposed method of analysis can be applied in other metropolitan areas as a diagnostic procedure supporting action planning to solve air-quality problems caused by distributed emission sources.

Smart City-Ranking of Major Australian Cities to Achieve a Smarter Future

A Smart City is a solution to the problems caused by increasing urbanization. Australia has demonstrated a strong determination for the development of Smart Cities. However, the country has experienced uneven growth in its urban development. The purpose of this study is to compare and identify the smartness of major Australian cities to the level of development in multi-dimensions. Eventually, the research introduces the openings to make cities smarter by identifying the focused priority areas. To ensure comprehensive coverage of all aspects of the smart city’s performance, 90 indicators were selected to represent 26 factors and six components. The results of the assessment endorse the impacts of recent government actions taken in different urban areas towards building smarter cities. The research has pointed out the areas of deficiencies for underperforming major cities in Australia. Following the results, appropriate recommendations for Australian cities are provided to improve the city’s smartness.

On the Coronavirus (COVID-19) Outbreak and the Smart City Network: Universal Data Sharing Standards Coupled with Artificial Intelligence (AI) to Benefit Urban Health Monitoring and Management

As the Coronavirus (COVID-19) expands its impact from China, expanding its catchment into surrounding regions and other countries, increased national and international measures are being taken to contain the outbreak. The placing of entire cities in ‘lockdown’ directly affects urban economies on a multi-lateral level, including from social and economic standpoints. This is being emphasised as the outbreak gains ground in other countries, leading towards a global health emergency, and as global collaboration is sought in numerous quarters. However, while effective protocols in regard to the sharing of health data is emphasised, urban data, on the other hand, specifically relating to urban health and safe city concepts, is still viewed from a nationalist perspective as solely benefiting a nation’s economy and its economic and political influence. This perspective paper, written one month after detection and during the outbreak, surveys the virus outbreak from an urban standpoint and advances how smart city networks should work towards enhancing standardization protocols for increased data sharing in the event of outbreaks or disasters, leading to better global understanding and management of the same.

Mobile Computing for Disaster Emergency Management: Empirical Requirements Analysis for a Cooperative Crowdsourced System for Emergency Management Operation

In large-scale civil emergencies such as floods, earthquakes, and extreme weather conditions, extended geographic areas and a great number of people may be affected by the unfortunate events. The wireless internet and the widespread diffusion of smart-phones and mobile devices make it possible to introduce new systems for emergency management. These systems could improve the efficiency of the interventions by transferring information between affected areas and a central decision support system. Information on the state of the infrastructures, on people displacement, and on every other important and urgent issue can be gathered in the disaster area. The central system can manage all the received information and communicate decisions back to people and also facilitate the exchange of information for different people that are still in the disaster area. This paper presents a requirement analysis for these kinds of systems. The presented analysis allows better tailoring of the features of these systems with the aim to meet the real need of emergency management operators and citizens.

The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy

The use of advanced technologies, especially predictive computing in the health sector, is on the rise in this era, and they have successfully transformed the sector with quality insights, better decision-making, and quality policies. Even though notable benefits have been achieved through the uptake of the technologies, adoption is still slow, as most of them are still new, hence facing some hurdles in their applications especially in national and international policy levels. But the recent case of COVID-19 outbreak has given an opportunity to showcase that these technologies, especially artificial intelligence (AI), have the capacity to produce accurate, real-time, and reliable predictions on issues as serious as pandemic outbreak. A case in point is how companies such as BlueDot and Metabiota managed to correctly predict the spread route of the virus days before such events happened and officially announced by the World Health Organization. In this chapter, an increase in the use of AI-based technologies to detect infectious diseases is underlined and how such uses have led to early detections of infectious diseases. Nevertheless, there is evidence that there is need to enhance data sharing activities, especially by rethinking how to improve the efficiency of data protocols. The chapter further proposes the need for enhanced use of technologies and data sharing to ensure that future outbreaks are detected even earlier, thus accelerating early preventive measures.

Underlining the Role of Data Science and Technology in Supporting Supply Chains, Political Stability and Health Networks During Pandemics

This concluding chapter explores how data science and technology has been key in fighting COVID-19 through early detection and in the devising of tools for containing the spread. Interestingly, two precedence constraints are seen to emerge. First, data-driven modeling is the leading policy at an urban and national level, and second, legislations, which are being passed at record speed, will remain as a legacy postvirus. It is expected that those will accelerate the digital transition of communities for decades to come and lead to a resurgence of the smart cities concept which peaked in 2015. This chapter thus outlines the increasing role of data science in health sciences, the need for more robust digital infrastructures, and the role of technology in supporting livability of communities and world order.