Human Mobility - Science topic

Is there any dataset available containing the mobility patterns of people within any city? Can we know which places people have visited in different time intervals with exact location information (i.e geo coordinates latitude and longitude)?

It is ok to have data annonymized to preserve the identity of individuals.

I am reviewing some mobility flow data of the United States. Does anyone have recommendations regarding public access to big datasets such as mobile phone data, smart card data, or daily activities with the explicit origin and destination locations within the US (preferably, the individual-level data and not city or county level)?

My research area is routing protocol for MANET networks, and I'm interested to test my proposition with a human mobility scenario.

I'm using NS2 for the implementation and simulation.

I used previously BonnMotion to generate mobility scenarios, but it doesn't provide any human mobility. I need another mobility generator that creates human mobility scenario.

I need to generate mobility trajectories in a floating car format with (x,y and time) or (lat, lon and time) with any spatio-temporal frequency?

I am looking for both options of map-matched trajectories over a street network or a random simulation in a simple x,y space?

Please suggest

To understand how dynamic process spreads in a population, we need in our study a large scale human mobility dataset. I'm asking, if this project provides such dataset or can you help me to get it?

Thanks

After the carantine (and the 2-3 month confinement), people from all over the world (especially from Europe) will make new decisions about their residential mobility. Taking into account that families have been confined inside very small houses, often in subhuman conditions, in overcrowded cities: Will this pandemic produce the great exodus of people from the city to the villages? Will immigrants return to their countries of origin with more intensity that before?

Mobility is changing. New types of mobility concepts are needed to reduce greenhouse gas emissions and thus mitigate climate change or to prevent the mobility sector from becoming overloaded. Individual mobility as we know it today will not exist in this form in the coming decades! In the literature, numerous concepts such as alternative drive concepts, ridehailing, ridepooling, car sharing, more attractive public transport, better cycling and walking infrastructure are listed for future mobility. What is missing are studies that prove the effectiveness, for example, in terms of reducing greenhouse gas emissions! Which concepts offer the highest potentials considering which parameters (acceptance, infrastructure, financing, etc.)? Which concepts offer the least? Do you know studies on this topic?

We are currently looking to recognize not only steps but detailed gait data (e.g. Shape Context and Linear Time Normalized) based on smartphone accelerometer data. We appreciate hints to existing software solutions (Android, iOS or device independent) as well as related work on the topic. Also, we would like to connect with other groups working on that subject.

We will use this data to support movement training as well as everyday walking activities of older adults (typically aged between 60 and 85).

Is there any dataset available containing the mobility patterns of people within any city? Can we know which places people have visited in different time intervals with exact location information (i.e geo coordinates latitude and longitude)?

It is ok to have data annonymized to preserve the identity of individuals.

The investigation of past human mobility and diet using stable isotope measurements of carbon (apatite and collagen), nitrogen, oxygen and strontium is a standardized practice in archaeology. Inter-sample comparisons derived from different labs are usually performed but is not clear if some differences emerging from the use of measurements obtained in distinct laboratories are negligible or on the contrary are significant.

I am trying to implement graph based slam using LIDAR data. So far I have created a pose graph and used scan matching to obtain odometery data. I have used this data to create pose constraints (edges) between successive nodes. Now I need to add loop closing edges but i dont know how to go about it. I should I detect loop closing edges.

Resistance in the new social movements has an anti-systemic nature. It means revolutionizing power from below. Sanctuary cities are a form of resistance against freedom of movement, recognition of human rights for all, regardless of their migratory status. Moving a step further along this line of thought, how can migrant organizations and movements promote a resistance movement?

More especifically how we could use Big Data to capture and analyze cross-border human mobility in time and space?

I have a bunch of 3D points and connections among these points. I want to plot a 3D network based on them. Any software or open source library can be used to do so?