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Location-based Data Analysis of Visitor Structure for Recreational Area Management
This work presents a location-based data analysis framework for profiling visitors structures. In terms of recreational area management, understanding visitors’ structure and popularity is important. Traditionally, visitors monitoring with automatic counting devices has drawbacks of inaccurate visitors counting. In this work, compared to automatic counting devices, we use Wi-Fi tracking as the main method to count visitors, which provides a fairly precise picture of visitor structures. Moreover, we deliver rich analytic functions in this framework and we present the functionality with visitor data collected from Guanyinshan Visitor Center. This framework not only standardizes visitor counting process but also facilitates a profound analysis of visitor structures.
Key Words:
Guanyinshan Visitor Center, Wi-Fi trackin
Statistical modelling and analysis of big data on pedestrian movement
This work follows a long line of studies and empirical investigations in Space Syntax research, that, in general, try to conceptualise, describe and quantify the relation between physical space and human agency. How many people share public space is known to affect many socio-economic processes in cities, such as segregation, vitality and local commercial markets. Observing and measuring pedestrian movement through surveys, as well as statistically analysing it have been at the core of diverse investigations not least in the field of Space Syntax, not only a means to validate and measure the dependence of pedestrian movement on spatial configuration, but also as a means to forecast and predict pedestrian flows. However, these studies do not necessarily provide us with comparable, let alone generalisable findings that can lead to generalisable propositions. They remain in most cases specific investigations of particular cities, neighbourhoods or types of areas (e.g. city centres). Another issue, as will be elaborated in this paper, is that the typical statistical methods used, such as multivariate regression models, are not always the optimal or even suitable for modelling pedestrian movement, typically measured in pedestrian counts.\ua0This paper aims therefore, to directly address three methodological challenges: first, construction of comparable GIS-models; second, gathering large scale pedestrian data; third, applying advanced statistical modelling suitable for pedestrian data.The ultimate goal is to estimate the impact of spatial form on urban life in a way that is methodologically sound and can provide robust results that can be generalisable, and allows us to speak of the relation between spatial form and pedestrian movement in a way that is not specific to a certain area, or types of areas or streets, or even to a specific city. \ua0The results show, first, high and consistent correlations between spatial form and pedestrian movement in a study of unprecedented size that comprises three cities, including a large range of neighbourhoods of varying morphological types, from villa areas to urban cores, and offer convincing proof that the tested morphological variables have a strong impact on the spatial distribution of pedestrian flows in cities. Second, the study shows that the model with all explanatory variables has the highest explanatory power and the best model fit where Angular integration and Accessible FSI are the explanatory variables with the largest effect on pedestrian movement, but others are significantly contributing to the predictive power of the model. Third, the study contributes to the advancement of the statistical modelling that is suitable for the specificities of the data used, proposing the use of a negative Binomial model instead of regression models, most common in the field
WIFI SCANNER FOR OBTAINING PEDESTRIAN DATA
Recently, many technologies to estimate pedestrian data to know about pedestrian travel behavior. Wifi is one of the most useful technologies that can be used in counting pedestrian data. This paper described using of WiFi scanner which carried out seven times circulated the bus. The method used WiFi and GPS are to counting MAC address as raw data from pedestrian smartphone or WiFi devices nearfrom the bus as long as the bus going around the route, generate and processing to be pedestrian data. There are five processes to make pedestrian data from raw data. The purpose of this study is to calculate, obtain and estimate the number of pedestrian data divide circulation number and road segmentation.
Human Crowds Estimation based on Mobile Sensing
University of Tokyo(東京大学
Indoor Localization for Fire Safety : A brief overview of fundamentals, needs and requirements and applications
An indoor localization system for positioning evacuating people can be anticipated to increase the chances of a safe evacuation and effective rescue intervention in case of a tunnel fire. Such a system may utilize prevalent wireless technologies, e.g., Bluetooth, RFID and Wi-Fi, which today are used to survey incoming and outgoing traffic to a certain space or location, to estimate group sizes and to measure the duration of visits during normal operation of buildings. Examples also exist of where the same wireless technologies are used for safety purposes, for example to assess real-time location, tracking and monitoring of vehicles, personnel and equipment in mining environments. However, they are relatively few, and typically rely on a high degree of control over the people that are to be tracked, and their association with (connection to) the localization system used for the tracking. In this report, the results of a brief overview of the literature within the field of indoor localization in general, and the application of indoor localization systems within the field of particularly fire safety, is summarized. This information forms the underlying basis for the planning and execution of a future field study, in which an indoor Wi-Fi localization system will be tested and evaluated in terms of if, and if so how, it can be used to position evacuating people in tunnels. Whereas such a system allows digital footprints to be collected within a wireless network infrastructure (also already existing ones), questions remains to be answered regarding aspects such as precision and accuracy, and furthermore, how these aspects are affected by other independent variables. In the end of this report, examples of research questions deemed necessary to answer in order to enable a sound evaluation of the system is presented. These need to be addressed in the future planning of the above-mentioned field study
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