相关论文: Detecting home locations from CDR data: introducin…

Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support or even become an integral part of statistical production…

Large-scale location based traces, such as mobile phone data, have been identified as a promising data source to complement or even enrich official statistics. In many cases, a prerequisite step to deploy the massively gathered data is the…

Estimation of people's home locations using location-based services data from smartphones is a common task in human mobility assessment. However, commonly used home detection algorithms (HDAs) are often arbitrary and unexamined. In this…

Home detection, assigning a phone device to its home antenna, is a ubiquitous part of most studies in the literature on mobile phone data. Despite its widespread use, home detection relies on a few assumptions that are difficult to check…

In this contribution we summarize insights on the geographical veracity of using mobile phone data to create (statistical) indicators. We focus on problems that persist with spatial allocation, spatial delineation and spatial aggregation of…

Understanding human mobility is essential for many fields, including transportation planning. Currently, surveys are the primary source for such analysis. However, in the recent past, many researchers have focused on Call Detail Records…

With the growth of using cell phones and the increase in diversity of smart mobile devices, a massive volume of data is generated continuously in the process of using these devices. Among these data, Call Detail Records, CDR, is highly…

Cellphone service-providers continuously collect Call Detail Records (CDR) as a usage log containing spatio-temporal traces of phone users. We proposed a multi-layered hierarchical analytical model for large spatio-temporal datasets and…

The pervasiveness and availability of mobile phone data offer the opportunity of discovering usable knowledge about crowd behaviors in urban environments. Cities can leverage such knowledge in order to provide better services (e.g., public…

The research objectives are exploring characteristics of human mobility patterns, subsequently modelling them mathematically depending on inter-event time and traveled distances parameters using CDRs (Call Detailed Records). The…

State-of-the-art lidar place recognition models exhibit unreliable performance when tested on environments different from their training dataset, which limits their use in complex and evolving environments. To address this issue, we…

Home-work commuting has always attracted significant research attention because of its impact on human mobility. One of the key assumptions in this domain of study is the universal uniformity of commute times. However, a true comparison of…

Accurately detecting home locations from GPS data generated by mobile devices is a foundational step in human mobility research, with significant implications for transportation planning, public health, and emergency response. However,…

The trend towards autonomous driving and the continuous research in the automotive area, like Advanced Driver Assistance Systems (ADAS), requires an accurate localization under all circumstances. An accurate estimation of the vehicle state…

Visual Place Recognition (VPR) enables robots and autonomous vehicles to identify previously visited locations by matching current observations against a database of known places. However, VPR systems face significant challenges when…

Call Detail Records (CDRs) are data recorded by telecommunications companies, consisting of basic informations related to several dimensions of the calls made through the network: the source, destination, date and time of calls. CDRs data…

Despite a large body of literature on trip inference using call detail record (CDR) data, a fundamental understanding of their limitations is lacking. In particular, because of the sparse nature of CDR data, users may travel to a location…

Mobile network operators store an enormous amount of information like log files that describe various events and users' activities. Analysis of these logs might be used in many critical applications such as detecting cyber-attacks, finding…

Since many safety-critical systems, such as surgical robots and autonomous driving cars operate in unstable environments with sensor noise and incomplete data, it is desirable for object detectors to take the localization uncertainty into…

How does a person work out their location using a floorplan? It is probably safe to say that we do not explicitly measure depths to every visible surface and try to match them against different pose estimates in the floorplan. And yet, this…