The mapping of large-scale human movements is important for urban planning, traffic forecasting and epidemic prevention. Work in animals had suggested that their foraging might be explained in terms of a random walk, a mathematical rendition of a series of random steps, or a Levy flight, a random walk punctuated by occasional larger steps. The role of Levy statistics in animal behaviour is much debated — as explained in an accompanying News Feature — but the idea of extending it to human behaviour was boosted by a report in 2006 of Levy flight-like patterns in human movement tracked via dollar bills. A new human study, based on tracking the trajectory of 100,000 cell-phone users for six months, reveals behaviour close to a Levy pattern, but deviating from it as individual trajectories show a high degree of temporal and spatial regularity: work and other commitments mean we are not as free to roam as a foraging animal. But by correcting the data to accommodate individual variation, simple and predictable patterns in human travel begin to emerge. The cover photo (by Cesar Hidalgo) captures human mobility in New York's Grand Central Station. This study used a sample of 100,000 mobile phone users whose trajectory was tracked for six months to study human mobility patterns. Displacements across all users suggest behaviour close to the Levy-flight-like pattern observed previously based on the motion of marked dollar bills, but with a cutoff in the distribution. The origin of the Levy patterns observed in the aggregate data appears to be population heterogeneity and not Levy patterns at the level of the individual. Despite their importance for urban planning1, traffic forecasting2 and the spread of biological3,4,5 and mobile viruses6, our understanding of the basic laws governing human motion remains limited owing to the lack of tools to monitor the time-resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-month period. We find that, in contrast with the random trajectories predicted by the prevailing Levy flight and random walk models7, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time-independent characteristic travel distance and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that, despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent-based modelling.

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Understanding individual human mobility patterns

We introduce a system for sensing complex social systems with data collected from 100 mobile phones over the course of 9 months. We demonstrate the ability to use standard Bluetooth-enabled mobile telephones to measure information access and use in different contexts, recognize social patterns in daily user activity, infer relationships, identify socially significant locations, and model organizational rhythms.

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Reality mining: sensing complex social systems

Mobile devices are becoming increasingly sophisticated and the latest generation of smart cell phones now incorporates many diverse and powerful sensors These sensors include GPS sensors, vision sensors (ie, cameras), audio sensors (ie, microphones), light sensors, temperature sensors, direction sensors (ie, magnetic compasses), and acceleration sensors (ie, accelerometers) The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications In this paper we describe and evaluate a system that uses phone-based accelerometers to perform activity recognition, a task which involves identifying the physical activity a user is performing To implement our system we collected labeled accelerometer data from twenty-nine users as they performed daily activities such as walking, jogging, climbing stairs, sitting, and standing, and then aggregated this time series data into examples that summarize the user activity over 10- second intervals We then used the resulting training data to induce a predictive model for activity recognition This work is significant because the activity recognition model permits us to gain useful knowledge about the habits of millions of users passively---just by having them carry cell phones in their pockets Our work has a wide range of applications, including automatic customization of the mobile device's behavior based upon a user's activity (eg, sending calls directly to voicemail if a user is jogging) and generating a daily/weekly activity profile to determine if a user (perhaps an obese child) is performing a healthy amount of exercise

/pdf/activity-recognition-using-cell-phone-accelerometers-3k6h9fhibm.pdf

Activity recognition using cell phone accelerometers

Mobile phones or smartphones are rapidly becoming the central computer and communication device in people's lives. Application delivery channels such as the Apple AppStore are transforming mobile phones into App Phones, capable of downloading a myriad of applications in an instant. Importantly, today's smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling the emergence of personal, group, and communityscale sensing applications. We believe that sensor-equipped mobile phones will revolutionize many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. In this article we survey existing mobile phone sensing algorithms, applications, and systems. We discuss the emerging sensing paradigms, and formulate an architectural framework for discussing a number of the open issues and challenges emerging in the new area of mobile phone sensing research.

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A survey of mobile phone sensing

Providing accurate and opportune information on people's activities and behaviors is one of the most important tasks in pervasive computing. Innumerable applications can be visualized, for instance, in medical, security, entertainment, and tactical scenarios. Despite human activity recognition (HAR) being an active field for more than a decade, there are still key aspects that, if addressed, would constitute a significant turn in the way people interact with mobile devices. This paper surveys the state of the art in HAR based on wearable sensors. A general architecture is first presented along with a description of the main components of any HAR system. We also propose a two-level taxonomy in accordance to the learning approach (either supervised or semi-supervised) and the response time (either offline or online). Then, the principal issues and challenges are discussed, as well as the main solutions to each one of them. Twenty eight systems are qualitatively evaluated in terms of recognition performance, energy consumption, obtrusiveness, and flexibility, among others. Finally, we present some open problems and ideas that, due to their high relevance, should be addressed in future research.

A Survey on Human Activity Recognition using Wearable Sensors

Website owners use web analytics tools to better understand their visitors for a range of purposes. However, there is limited understanding of how owners of non-transactional websites use and benefit from web analytics. Through semi-structured interviews (n=18) with non-transactional web analytics users we explore these uses and benefits. Participants tend to use web analytics to improve site design, by optimizing site structure, content, or technical specifications. However, participants also use web analytics to understand their audiences without a directed purpose, often for curiosity or entertainment. The design of web analytics tools should account for this full range of functionality.

https://dl.acm.org/doi/pdf/10.1145/2598510.2598555

Exploring the benefits and uses of web analytics tools for non-transactional websites

Many have enthusiastically greeted the ability to search and view public records online as a great advance for transparency and accountability. Such ability, however, also creates value tensions with privacy and other important human values. In this paper, we report findings from a survey of 134 residents of the US Pacific Northwest on their awareness of and attitudes towards online access to political campaign records and real estate transaction histories, bringing to light some of the social implications of technological changes that increase ease of access to public records. We show that. while respondents often understood the reason behind making these records public, considerable concern about the current accessibility of these records exists, along with a precautionary indication that such open access may reduce public participation for some individuals.

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Sunlight or sunburn: a survey of attitudes toward online availability of US public records

The focus of this workshop is on the development of interfaces for long-term, voluntary use, spanning dozens, if not thousands, of interactions, and in which maintenance of user adherence to a desired interaction usage pattern is of primary interest. Domains in which these issues are important include: wellness applications, such as long-term exercise or diet promotion; web site "stickiness"; multi-session intelligent tutoring systems; and computer games. This one-day CHI'09 workshop brings together researchers from a wide spectrum of disciplines who share a common interest in finding theoretical frameworks, models, and design methodologies to support longitudinal HCI.

Engagement by design

. As more evaluations of ubiquitous computing (ubicomp) applications are being undertaken, researchers are finding that the evaluations are more difficult than those for typical desktop computing applications. In this paper, we discuss some aspects of ubicomp that make these evaluations challenging. We present some properties unique to ubiquitous computing applications and suggest metrics to evaluate them. Several case studies of ubicomp evaluations are discussed with respect to these properties. 1 Introduction Researchers in ubicomp applications are attempting to produce systems that will fill a user need. To understand if this has been achieved, it is necessary to conduct user-centered evaluations. Because the deployment of this technology will certainly impact how users work and play, user-centered evaluations have become a moving target [1]. In this paper we discuss how evaluating ubicomp applications presents research challenges above those associated with traditional desktop-based and mobile computing applications. In particular, evaluating ubicomp requires understanding and measuring how people perform tasks or engage in activities that may only partially involve computing. We discuss lessons learned about evaluation from several case studies. We also outline some research directions that could facilitate future evaluation of ubicomp applications.

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User-centered Evaluations of Ubicomp Applications

A user may input one or more messages (e.g., visual or audio content) with respect to a projection device that is to project the messages to users within an environment. The user may additionally input related information that dictates a context and manner in which the messages are to be projected. The projection device may monitor the environment to identify users, events or actions within the environment. Upon detecting and identifying a particular user, the projection device may visually project the messages onto a surface within the environment, or may audibly output the messages within the environment, which may convey a particular meaning to that user. Optionally, the projection device may authenticate the user in order to determine that the user is the intended recipient of the messages.

Sunny Consolvo

Papers

Exploring the benefits and uses of web analytics tools for non-transactional websites

Sunlight or sunburn: a survey of attitudes toward online availability of US public records

Engagement by design

User-centered Evaluations of Ubicomp Applications

Projecting content within an environment