Analysis of the factors generating vehicular traffic in the city of Quito and its relation to the application of sensorial and social data with big data as a basis for decision making

2016 ◽  
Author(s):  
Nelson Herrera Herrera ◽  
Hector Sanchez Santamaria ◽  
Miguel Macias Macias ◽  
Estevan Gomez
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Vehicular Traffic ◽  
Social Data ◽  
The City

Deconstructing Smart Cities

Big Data ◽  
2016 ◽  
pp. 1957-1969
Author(s):  
Michael Batty
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Smart City ◽  
New Technologies ◽  
Smart Cities ◽  
Public Realm ◽  
The Public ◽  
Important Challenge ◽  
Urban Problems ◽  
The City

This chapter defines the smart city in terms of the process whereby computers and computation are being embedded into the very fabric of the city itself. In short, the smart city is the automated city where the goal is to improve the efficiency of how the city functions. These new technologies tend to improve the performance of cities in the short term with respect to how cities function over minutes, hours or days rather than over years or decades. After establishing definitions and context, the author then explores questions of big data. One important challenge is to synthesize or integrate different data about the city's functioning and this provides an enormous challenge which presents many obstacles to producing coherent solutions to diverse urban problems. The chapter augments this argument with ideas about how the emergence of widespread computation provides a new interface to the public realm through which citizens might participate in rather fuller and richer ways than hitherto, through interactions in various kinds of decision-making about the future city. The author concludes with some speculations as to how the emerging science of smart cities fits into the wider science of cities.

Deconstructing Smart Cities

2014 ◽  
pp. 1-13 ◽  
Author(s):  
Michael Batty
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Smart City ◽  
New Technologies ◽  
Smart Cities ◽  
Public Realm ◽  
The Public ◽  
Important Challenge ◽  
Urban Problems ◽  
The City

This chapter defines the smart city in terms of the process whereby computers and computation are being embedded into the very fabric of the city itself. In short, the smart city is the automated city where the goal is to improve the efficiency of how the city functions. These new technologies tend to improve the performance of cities in the short term with respect to how cities function over minutes, hours or days rather than over years or decades. After establishing definitions and context, the author then explores questions of big data. One important challenge is to synthesize or integrate different data about the city's functioning and this provides an enormous challenge which presents many obstacles to producing coherent solutions to diverse urban problems. The chapter augments this argument with ideas about how the emergence of widespread computation provides a new interface to the public realm through which citizens might participate in rather fuller and richer ways than hitherto, through interactions in various kinds of decision-making about the future city. The author concludes with some speculations as to how the emerging science of smart cities fits into the wider science of cities.

Big data visualisation, geographic information systems and decision making in healthcare management

2019 ◽  
Vol 57 (8) ◽  
pp. 1937-1959 ◽  
Author(s):  
Anitha Chinnaswamy ◽  
Armando Papa ◽  
Luca Dezi ◽  
Alberto Mattiacci
Keyword(s):  
Decision Making ◽  
Developing Countries ◽  
Big Data ◽  
Geographic Information ◽  
Healthcare Management ◽  
Data Sets ◽  
Content Type ◽  
The World ◽  
The City

Purpose The World Health Organisation estimates that 92 per cent of the world’s population does not have access to clean air. The World Bank in 2013 estimated that only air pollution (AP) was responsible for a $225bn cost in lost productivity. The purpose of this paper is to contribute to the current scholarly debate on the value of Big Data for effective healthcare management. Its focus on cardiovascular disease (CVD) in developing countries, a major cause of disability and premature death and a subject of increasing research in recent years, makes this research particularly valuable. Design/methodology/approach In order to assess the effects of AP on CVD in developing countries, the city of Bangalore was selected as a case study. Bangalore is one of the fastest growing economies in India, representative of the rapidly growing cities in the developing world. Demographic, AP and CVD data sets covering more than 1m historic records were obtained from governmental organisations. The spatial analysis of such data sets allowed visualisation of the correlation between the demographics of the city, the levels of pollution and deaths caused by CVDs, thus informing decision making in several sectors and at different levels. Findings Although there is increasing concern in councils and other responsible governmental agencies, resources required to monitor and address the challenges of pollution are limited due to the high costs involved. This research shows that with developments in the domains of Big Data, Internet of Things and smart cities, opportunities to monitor pollution result in high volumes of data. Existing technologies for data analytics can empower decision makers and even the public with knowledge on pollution. This paper has demonstrated a methodological approach for the collection and visual representation of Big Data sets allowing for an understanding of the spread of CVDs across the city of Bangalore, enabling different stakeholders to query the data sets and reveal specific statistics of key hotspots where action is required. Originality/value This research has been conducted to demonstrate the value of Big Data in generating a strategic knowledge-driven decision-support system to provide focused and targeted interventions for environmental health management. This case study research is based on the use of a geographic information system for the visualisation of a Big Data set collected from Bangalore, a region in India seriously affected by pollution.

scholarly journals Innovative programming product for work architect-urbanist with Big Data of city

2021 ◽  
Vol 1203 (2) ◽  
pp. 022021
Author(s):  
Oksana Fomenko ◽  
Serhiy Danylov ◽  
Mykhaylo Izbash ◽  
Andrii Izbash
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Dynamic System ◽  
Modern Science ◽  
Strategic Decision ◽  
Information Support ◽  
Strategic Decision Making ◽  
Program Complex ◽  
Decision Making Processes ◽  
The City

Abstract The article substantiates the necessity of creating an innovative programming product "Program complex for modelling the city as a dynamic system". The methodological basics of writing a technical task as the basis for the complex development are described. The aspects of its use as a tool for information support of strategic decision-making processes related to the transition of the city to an intensive type of development are disclosed. The purpose of the program complex: information support for strategic decision-making processes to optimize the principles of the city. The purpose of the program complex is to analyze the processes of city functioning as a complex dynamic system. In this case, it is possible to diagnose the current state of the city as a system in real-time, the state of its subsystems and elements, as well as to predict changes in the dynamic processes of their functioning. The specified program package is based on a combination of two trends in modern science: optimization of the city functioning processes and management of large arrays of city data (Big Data). The Program simulates positive and negative dynamics of the transition of the city, its subsystems and individual elements from a state of stability to crisis and a possible pre-catastrophic state.

What Makes a City Bikeable? A Study of Intercity and Intracity Patterns of Bicycle Ridership using Mobike Big Data Records

2020 ◽  
Vol 46 (1) ◽  
pp. 55-75
Author(s):  
Ying Long ◽  
Jianting Zhao
Keyword(s):  
Big Data ◽  
Average Distance ◽  
Policy Implications ◽  
Rating System ◽  
City Centre ◽  
Average Score ◽  
Policy Makers ◽  
Usage Frequency ◽  
Share Data ◽  
The City

This paper examines how mass ridership data can help describe cities from the bikers' perspective. We explore the possibility of using the data to reveal general bikeability patterns in 202 major Chinese cities. This process is conducted by constructing a bikeability rating system, the Mobike Riding Index (MRI), to measure bikeability in terms of usage frequency and the built environment. We first investigated mass ridership data and relevant supporting data; we then established the MRI framework and calculated MRI scores accordingly. This study finds that people tend to ride shared bikes at speeds close to 10 km/h for an average distance of 2 km roughly three times a day. The MRI results show that at the street level, the weekday and weekend MRI distributions are analogous, with an average score of 49.8 (range 0–100). At the township level, high-scoring townships are those close to the city centre; at the city level, the MRI is unevenly distributed, with high-MRI cities along the southern coastline or in the middle inland area. These patterns have policy implications for urban planners and policy-makers. This is the first and largest-scale study to incorporate mobile bike-share data into bikeability measurements, thus laying the groundwork for further research.

‘Seeing like a city’, or ‘seeing like a state’ in a city? Paris, capital of femonationalism

2021 ◽  
pp. 239965442110025
Author(s):  
Claire Hancock
Keyword(s):  
Decision Making ◽  
Urban Politics ◽  
Policy Making ◽  
Common Factor ◽  
Local Democracy ◽  
Municipal Policy ◽  
City Life ◽  
Women In Decision Making ◽  
The City

This paper questions the ‘seeing like a city’ vs. ‘seeing like a state’ opposition through a detailed discussion of urban politics in the city of Paris, France, a prime example of the ways in which the national remains a driving dimension of city life. This claim is examined by a consideration of the shortcomings of Paris’s recent and timid commitment local democracy, lacking recognition of the diversity of its citizens, and the ways in which the inclusion of more women in decision-making arenas has failed to advance the ‘feminization of politics’. A common factor in these defining features of the Hidalgo administration seems to be the prevalence of ‘femonationalism’ and its influence over municipal policy-making.

Sign in / Sign up

Export Citation Format

Share Document