Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

Data-Driven Operational and Safety Analysis of Emerging Shared Electric Scooter Systems

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters. Perceiving the growth of such a micro-mobility mode, this study aimed to investigate E-Scooter operations and safety by collecting, processing, and mining various unconventional data sources. First, origin-destination (OD) data were collected for E-Scooters to analyze how E-Scooters have been used in urban areas. The key factors that drive users to choose E-Scooters over other options (i.e., shared bikes and taxis) were identified. Concerning user safety tied to the growing usage, we further assessed E-Scooter user guidelines in urban areas in the U.S. Scoring models have been developed for evaluating the adopted guidelines. It was found that the areas with E-Scooter systems have notable disparities in terms of the safety factors considered in the guidelines. Built upon the usage and policy analyses, this study also creatively collected news reports as an alternative data source for E-Scooter safety analysis. Three-year news reports were collected for E-Scooter-involved crashes in the U.S. The identified reports are typical crash events with great media impact. Many detailed variables such as location, time, riders’ information, and crash type were mined. This offers a lens to highlight the macro-level crash issues confronted with E-Scooters. Besides the macro-level safety analysis, we also conducted micro-level analysis of E-Scooter riding risk. An all-in-one mobile sensing system has been developed using the Raspberry Pi platform with multiple sensors including GPS, LiDAR, and motion trackers. Naturalistic riding data such as vibration, speed, and location were collected simultaneously when riding E-Scooters. Such mobile sensing technologies have been shown as an innovative way to help gather valuable data for quantifying riding risk. A demonstration on expanding the mobile sensing technologies was conducted to analyze the impact of wheel size and riding infrastructure on E-Scooter riding experience. The quantitative analysis framework proposed in this study can be further extended for evaluating the quality of road infrastructure, which will be helpful for understanding the readiness of infrastructure for supporting the safe use of micro-mobility systems. To sum up, this study contributes to the literature in several distinct ways. First, it has developed mode choice models for revealing the use of E-Scooters among other existing competitive modes for connecting urban metro systems. Second, it has systematically assessed existing E-Scooter user guidelines in the U.S. Moreover, it demonstrated the use of surrogate data sources (e.g., news reports) to assist safety studies in cases where there is no available crash data. Last but not least, it developed the mobile sensing system and evaluation framework for enabling naturalistic riding data collection and risk assessment, which helps evaluate riding behavior and infrastructure performance for supporting micro-mobility systems

The Digital Literacy Practices of Newly Arrived Syrian Refugees: a Spatio-Visual Linguistic Ethnography

This doctoral research project is a visual linguistic ethnography that provides thick descriptions of newly arrived Syrian refugees’ smartphone-mediated digital literacy practices. The study investigates how three male newcomers to Leeds, Rojan, Aban and Mamoud, utilize mobile technologies and online resources, such as multilingual Facebook groups and smartphone applications, to instigate and support processes of settlement and belonging. To trace and interpret these quotidian mobile practices, prolonged and consistent engagement with my participants and their lifeworlds was required. Thus, data collection concerning this ethnography took place over an in-depth ten-month period at various data collection sites. The multimodal and spatio-visual literacy practices that my key participants engaged with on their mobile devices were inherently diverse and complex to interpret. Here, the analytical lenses of capital and space have informed conceptualizations of how my participants’ digital literacy repertories within distinct mobile contexts relate to and interplay with settlement processes, such as obtaining a UK driving license or finding paid work in the formal and informal economy. The dataset of this research project provides in-depth descriptions of how newly arrived refugees integrate smartphones into their everyday lives. Here, the findings of this study offer crucial insights into the interconnections between mobile technologies and settlement processes within this context of forced migration; the data analyses show how smartphones become key spatial instruments, which have the potential to impact and capitalize on the immediate physical spaces that my participants find themselves in and traverse through during their settlement trajectory, either by creating and joining translocal hybrid spaces, or by penetrating and transforming existing spaces

Seamless Interactions Between Humans and Mobility Systems

As mobility systems, including vehicles and roadside infrastructure, enter a period of rapid and profound change, it is important to enhance interactions between people and mobility systems. Seamless human—mobility system interactions can promote widespread deployment of engaging applications, which are crucial for driving safety and efficiency. The ever-increasing penetration rate of ubiquitous computing devices, such as smartphones and wearable devices, can facilitate realization of this goal. Although researchers and developers have attempted to adapt ubiquitous sensors for mobility applications (e.g., navigation apps), these solutions often suffer from limited usability and can be risk-prone. The root causes of these limitations include the low sensing modality and limited computational power available in ubiquitous computing devices. We address these challenges by developing and demonstrating that novel sensing techniques and machine learning can be applied to extract essential, safety-critical information from drivers natural driving behavior, even actions as subtle as steering maneuvers (e.g., left-/righthand turns and lane changes). We first show how ubiquitous sensors can be used to detect steering maneuvers regardless of disturbances to sensing devices. Next, by focusing on turning maneuvers, we characterize drivers driving patterns using a quantifiable metric. Then, we demonstrate how microscopic analyses of crowdsourced ubiquitous sensory data can be used to infer critical macroscopic contextual information, such as risks present at road intersections. Finally, we use ubiquitous sensors to profile a driver’s behavioral patterns on a large scale; such sensors are found to be essential to the analysis and improvement of drivers driving behavior.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163127/1/chendy_1.pd

Design and Effect of Continuous Wearable Tactile Displays

Our sense of touch is one of our core senses and while not as information rich as sight and hearing, it tethers us to reality. Our skin is the largest sensory organ in our body and we rely on it so much that we don\u27t think about it most of the time. Tactile displays - with the exception of actuators for notifications on smartphones and smartwatches - are currently understudied and underused. Currently tactile cues are mostly used in smartphones and smartwatches to notify the user of an incoming call or text message. Specifically continuous displays - displays that do not just send one notification but stay active for an extended period of time and continuously communicate information - are rarely studied. This thesis aims at exploring the utilization of our vibration perception to create continuous tactile displays. Transmitting a continuous stream of tactile information to a user in a wearable format can help elevate tactile displays from being mostly used for notifications to becoming more like additional senses enabling us to perceive our environment in new ways. This work provides a serious step forward in design, effect and use of continuous tactile displays and their use in human-computer interaction. The main contributions include: Exploration of Continuous Wearable Tactile Interfaces This thesis explores continuous tactile displays in different contexts and with different types of tactile information systems. The use-cases were explored in various domains for tactile displays - Sports, Gaming and Business applications. The different types of continuous tactile displays feature one- or multidimensional tactile patterns, temporal patterns and discrete tactile patterns. Automatic Generation of Personalized Vibration Patterns In this thesis a novel approach of designing vibrotactile patterns without expert knowledge by leveraging evolutionary algorithms to create personalized vibration patterns - is described. This thesis presents the design of an evolutionary algorithm with a human centered design generating abstract vibration patterns. The evolutionary algorithm was tested in a user study which offered evidence that interactive generation of abstract vibration patterns is possible and generates diverse sets of vibration patterns that can be recognized with high accuracy. Passive Haptic Learning for Vibration Patterns Previous studies in passive haptic learning have shown surprisingly strong results for learning Morse Code. If these findings could be confirmed and generalized, it would mean that learning a new tactile alphabet could be made easier and learned in passing. Therefore this claim was investigated in this thesis and needed to be corrected and contextualized. A user study was conducted to study the effects of the interaction design and distraction tasks on the capability to learn stimulus-stimulus-associations with Passive Haptic Learning. This thesis presents evidence that Passive Haptic Learning of vibration patterns induces only a marginal learning effect and is not a feasible and efficient way to learn vibration patterns that include more than two vibrations. Influence of Reference Frames for Spatial Tactile Stimuli Designing wearable tactile stimuli that contain spatial information can be a challenge due to the natural body movement of the wearer. An important consideration therefore is what reference frame to use for spatial cues. This thesis investigated allocentric versus egocentric reference frames on the wrist and compared them for induced cognitive load, reaction time and accuracy in a user study. This thesis presents evidence that using an allocentric reference frame drastically lowers cognitive load and slightly lowers reaction time while keeping the same accuracy as an egocentric reference frame, making a strong case for the utilization of allocentric reference frames in tactile bracelets with several tactile actuators

The erosion of nongambling spheres by smartphone gambling: a qualitative study on workplace and domestic disordered gambling

The potential dangers of internet-based gambling as compared with more traditional land-based gambling have been increasingly investigated over the past decade. The general consensus appears to be that although internet gambling might not be a more dangerous medium for gambling per se, the 24/7 availability it generates for problem gamblers, however, is. Because smartphones have become the most used way of gambling online, internet gambling must, therefore, be further subcategorized according to the device by which it is accessed. This study examines the issue by exploring the views of smartphone gamblers undergoing treatment for gambling disorder in focus group settings (N=35). Utilizing thematic analysis, the paper shows that smartphone gambling has colonized spaces previously regarded as nongambling spheres. The workplace, especially in male-dominated contexts, emerged as an accommodator and stimulator of gambling behavior, raising issues of productivity rather than criminality. Domestic gambling was mostly characterized by an invasion of bathroom and bedtime spheres of intimacy. The study examines the implications of prevention and treatment, focusing on the minimization of exposure to gambling stimuli, the erosion of intimacy that recovering gamblers must endure, and the necessity of embracing a broader definition of gambling-related harm

Leveraging emerging technologies to enable environmental monitoring and accountability in conflict zones

The growth of access to the internet, wide availability of smart phones and increased public access to remote sensing data from hundreds of satellite systems have spurred a revolution in tracking the linkages between armed conflict and environmental damage. Over the last decade, a growing community of open-source investigative experts, environmentalists, academics and civil society groups have applied these methods to document war crimes, human rights violations and environmental degradation. These developments have created new opportunities for building accountability and transparency. The wealth of data on conflict-linked environmental damage has already been successfully leveraged to address acute and long-term environmental health risks and inform humanitarian response and post-conflict environmental assessments in Iraq, Syria and Ukraine. There are, however, larger questions on how to best make use of these data streams and information layers, and how to navigate the opportunities and limitations of these developments. This article will outline the new developments in this field and provide recommendations to ensure that data is used responsibly and effectively to strengthen accountability for environmental damages as a result of armed conflict

Social media and GIScience: Collection, analysis, and visualization of user-generated spatial data

Over the last decade, social media platforms have eclipsed the height of popular culture and communication technology, which, in combination with widespread access to GIS-enabled hardware (i.e. mobile phones), has resulted in the continuous creation of massive amounts of user-generated spatial data. This thesis explores how social media data have been utilized in GIS research and provides a commentary on the impacts of this next iteration of technological change with respect to GIScience. First, the roots of GIS technology are traced to set the stage for the examination of social media as a technological catalyst for change in GIScience. Next, a scoping review is conducted to gather and synthesize a summary of methods used to collect, analyze, and visualize this data. Finally, a case study exploring the spatio-temporality of crowdfunding behaviours in Canada during the COVID-19 pandemic is presented to demonstrate the utility of social media data in spatial research