Automated Measurement of Walkability Applying Artificial Intelligence (AI) and Spatial Analysis Techniques

2021 ◽  
Vol 22 ◽  
pp. 101180
Author(s):  
Md Mehedi Hasan ◽  
Valerian Kwigizile ◽  
Jun-Seok Oh
Author(s):  
Luis Alberto Casillas Santillan ◽  
Johor Ismael Jara Gonzalez

This article describes how current video games offer an extreme use of media fusion. Such construction implies a novel form of complexity regarding game control and active response from game to player. All of these elements produce deeper immersion effect in players. In order to perform a detailed supervision over this kind of game, additional controls should be included in game. Some of these controls are the moving and decision schemes. Authors believe that players move around virtual scenarios following some sort of pattern. Every player would have a specific pattern, according to his/her experience and capability to manage the gamepad layout. Current proposal consists in a 3D geometrical model surrounding player's avatar. Data unwittingly provided by the player, have elements to discover and, eventually, learn some gamers' patterns. The availability of these patterns would allow an improved game response and even the possibility of machine learning, as well as other artificial intelligence strategies. Every 3D game may include the model proposed in this paper, due to its noninvasive operation.


2020 ◽  
Vol 44 (2) ◽  
pp. 145-158 ◽  
Author(s):  
Moritz Altenried

This article analyses crowdwork platforms where various forms of digital labour are outsourced to digital workers across the globe. The labour of these workers is, among other things, a crucial component in the production, development and support of artificial intelligence. Crowdwork platforms are an extreme example of new forms of automated measurement, management and control of labour allowing, in turn, for the creation of hyperflexible and highly scalable workforces. Particularly on so-called microtask platforms, work is characterised by decomposition, standardisation, automated management and surveillance, as well as algorithmically organised cooperation between a great number of workers. Analysing these platforms as a paradigmatic example of an emerging digital Taylorism, the article goes on to argue that this allows the platforms to assemble a deeply heterogeneous set of workers while bypassing the need to spatially and subjectively homogenise them. These platforms create a global on-demand workforce, working in their private homes or Internet cafes. As a result, crowdwork taps into labour pools hitherto almost inaccessible to wage labour. The second part of the article investigates this tendency by looking at two sets of workers: women shouldering care responsibilities, who now can work on crowdwork platforms while performing domestic labour, as well as digital workers in the Global South. While there are clear specifics of digital crowdwork, it is also an expression of broader transformations within the world of work, concerning, for example, new forms of algorithmic management just as the return of very old forms of exploitation such as the piece wage.


Author(s):  
Andrew Curtis ◽  
Michael Leitner

n the opening chapters, GIS was broken into four general components, one of which was the spatial analysis of data. This is probably the least utilized of all GIS functions outside of an academic environment. A point that is often missed when discussing GIS is that the technology often exceeds the capabilities of the user. This is especially true if the user has not received any academic training in spatial data and GIS use. In Chapter VI a more sophisticated overview will be presented of the latest spatial analysis techniques along with examples of their implementation. Although the number of “spatially” trained scientists continues to grow, there is still a gap between the number of available skilled GIS modelers and the community programs needing GIS analysis. This chapter is designed to provide a stopgap approach, using more simple spatial statistical approaches that can be applied to gain a reasonable first insight into a birth outcome surface.


2018 ◽  
Vol 39 (6) ◽  
pp. 1347-1377 ◽  
Author(s):  
Abdelaziz Elfadaly ◽  
Wael Attia ◽  
Mohamad Molaei Qelichi ◽  
Beniamino Murgante ◽  
Rosa Lasaponara

Author(s):  
Tony H. Grubesic ◽  
Jake R. Nelson

Spatial analysis refers to a process that relies upon both exploratory and confirmatory techniques to answer important questions and enhance decision making with spatial data. This includes approaches to identify patterns and processes, detect outliers and anomalies, test hypotheses and theories, and generate spatial data and knowledge. Data qualify as “spatial” when their location is known and it has the potential to impact the outcome of an analysis. Most often, this space is tied to the geographic domain and concerns the Earth’s surface or subsurface. However, spatial data also exist within different scales and contexts, including nano- and picoscale processes in cellular electrophysiology and subatomic physics, among many others. When locational information is given about a particular piece of data, researchers in the field of spatial analysis can use that data to calculate statistical and mathematical relationships regarding time and space. If the data do not include locational information, such as a list of bicycle parts, spatial analysis would not be necessary. In fact, unless the data have some sort of locational information, spatial analysis is not possible. This article provides a foundation for exploring some of the most important works in spatial analysis. The General Overviews section provides readers with many of the most common and important techniques used in spatial analysis. Important Reference Resources are then discussed, followed by an overview of popular Journals that publish work pertaining to spatial analysis techniques and their applications. The two most common application areas for spatial analysis techniques, Gis and Remote Sensing, are then discussed, as are their respective software packages. The final section includes a more detailed overview of spatial analysis Techniques and their associated subdomains.


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