The Potential of Blockchain within Air Rights Development as a Prevention Measure against Urban Sprawl

Dey

Jones

2020

Self Cite

149

105

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.

Section: On Ai-driven Algorithms and Bioinformaticsmentioning

confidence: 99%

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

Dey

Jones

2020

Self Cite

149

105

“…With traditional contracts, the contracting parties face transaction costs linked to the necessity of appointing a third party to verify and enforce the contracts. However, with smart contracts, the self‐executing character of these contracts means that third party verification is not necessary (Allam & Jones, ) and further, smart contracts are programmed to reduce human error and speed up the transaction (Giancaspro, ).…”

Section: Reducing Transaction Costs Of Tps Using Blockchain Smart Conmentioning

confidence: 99%

Reducing transaction costs of tradable permit schemes using Blockchain smart contracts

Shahab

2019

Growth and Change

Self Cite

Tradable permit schemes (TPS) are market‐based policy instruments, which are claimed to be more statically and dynamically efficient in achieving their policy objectives compared to the traditional regulatory instruments. However, some researchers argue that the high level of transaction costs associated with these policy instruments might undermine their efficiency. This paper addresses this issue through exploring the use of Blockchain technology in order to lower transaction costs that arise from TPS transactions. More specifically, it identifies the benefits of using Blockchain smart contracts in implementing TPS that include: increasing the amount of relevant information available to interested actors thus reducing uncertainties; reducing the amount of irrelevant information available to interested actors thus decreasing complexities; correcting information asymmetries among the actors involved thus limiting opportunistic behaviours; lowering the need for the involvement of intermediaries thus decreasing direct monetary costs; and facilitating the linkage between buyers and sellers thus improving trading quality. These potential benefits can increase the efficiency of TPS by decreasing policy‐related transaction costs.

“…However, this may face some resistance from an economic perspective, as ICT corporations would be expected to favor specific networks riding on proprietary technology, thus ensuring market monopoly. Although this is the case, there have numerous calls from various authors [5,7,[103][104][105] to highlight the economic benefits for economic inclusivity through the democratization of smart city technologies and ICT networks, thereby leading to a wider adoption and resulting in higher profit margins by ICT corporations.…”

Section: Discussionmentioning

confidence: 99%

Achieving Neuroplasticity in Artificial Neural Networks through Smart Cities

2019

Smart Cities

Self Cite

Through the Internet of things (IoT), as promoted by smart cities, there is an emergence of big data accentuating the use of artificial intelligence through various components of urban planning, management, and design. One such system is that of artificial neural networks (ANNs), a component of machine learning that boasts similitude with brain neurological networks and its functioning. However, the development of ANN was done in singular fashion, whereby processes are rendered in sequence in a unidimensional perspective, contrasting with the functions of the brain to which ANN boasts similitude, and in particular to the concept of neuroplasticity which encourages unique complex interactions in self-learning fashion, thereby encouraging more inclusive urban processes and render urban coherence. This paper takes inspiration from Christopher Alexander’s Nature of Order and dwells in the concept of complexity theory; it also proposes a theoretical model of how ANN can be rendered with the same plastic properties as brain neurological networks with multidimensional interactivity in the context of smart cities through the use of big data and its emerging complex networks. By doing so, this model caters to the creation of stronger, richer, and more complex patterns that support Alexander’s concept of “wholeness” through the connection of overlapping networks. This paper is aimed toward engineers with interdisciplinary interest looking at creating more complex and intricate ANN models, and toward urban planners and urban theorists working on the emerging contemporary concept of smart cities.