Advanced Science and Technology Letters Vol.46 (Cloud and Super Computing 2014), pp.146-153 http://dx.doi.org/10.14257/astl.2014.46.33
Use of Cloud-Synchronized Settings in Intelligent Applications for the Elderly Drew Williams1, Sheikh Iqbal Ahamed1 and William Chu2 1
Marquette University, Milwaukee, WI {drew.williams, sheikh.ahamed}@marquette.edu 2 Tunghai University, Taichung City, Taiwan
[email protected]
Abstract. Both desktop computers and laptop computers possess the ability to make themselves more elderly-friendly via the adjustment of settings within a computer. However, in modern times a user often has more than one computer – perhaps both a desktop computer at work and a mobile phone. This provides us with a problem of settings synchronization: a user with specific settings requirements, such as an elderly user, often has to adjust settings on the machines individually. If the user were to synchronize settings via cloud storage, they could quickly make updates regarding their settings preferences and have the opportunity to use more sensor data from mobile devices and thus obtain a more personalized experience on their various machines. In this paper, we discuss the use of a cloud-stored settings system that brings about the user’s data from all devices and automatically adjusts interfaces for a user’s abilities, keeping connected computers up to date with the proper interface automatically. Keywords: human computer interfaces, elderly people, cloud storage, ubiquitous computing, mobile applications
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Introduction
An active topic in human-computer interaction research is that of developing proper interfaces for the older adult user. Older adult computer users can encounter a variety of problems when using existing applications, [1] due to improper considerations taken during the development of these apps. Said issues can range from being unable to use the application due to improper graphic user interfaces, [2, 3] to being unable to understand how to use the application as a result of lacking tutorials. [3] A variety of different benefits await those elderly users who choose to learn how to use computer applications – ranging from entertainment and education possibilities to medical monitoring applications. [4] As a result, a variety of approaches for making the use of computers easier for elderly users have been developed. One of the solutions suggested is that of intelligent interfaces. Based on either user input or automatic data collection (and perhaps both), an application using an intelligent interface can decide whether a user is feeling frustrated or happy, is having ISSN: 2287-1233 ASTL Copyright © 2014 SERSC
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difficulty using their mouse or not, and adjust an interface accordingly. This does wonders for creating an interface that assists an older user, while allowing him or her to retain their independence. However, these interface designs have been complicated with more users than ever having multiple and mobile devices. If the elderly user chooses to instigate settings for their particular needs within one instance of the application, what happens to the settings when the user moves to another device? Data collected by the user (files and bookmarks) is typically transmitted between multiple applications – but the carefully configured settings are often not. A lack of proper synchronization options also restricts the intelligence of the interface - user data gathered via different devices could assist an intelligent interface in making proper decisions regarding user preferences. To remedy this situation, we propose a system of synchronization via the cloud, which transmits and retrieves profile data sent between desktop and mobile applications. In doing this, we solve three problems: the issue of intelligent interfaces extending across multiple computers, the issue of intelligent interfaces extending to mobile devices, and gathering user data from the sensors of mobile devices to be integrated into the desktop environment, where it may assist in customizing a users’ interface even further. We’ll begin by outlining our basic motivations for such a project, in addition to some related work in human computer interfaces. After this we’ll discuss the nature of the data for intelligent interface customization collected from both desktop and mobile devices, and how it can be consolidated via cloud storage. We’ll illustrate the usefulness of this system via a particular case study. Finally, we’ll conclude with the mention of some future work that we can pursue.
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Motivation
Our primary motivation in developing such a system is to make the use of a given application more attractive to the elderly computer user. Software that runs on mobile devices, like desktop computer software, can offer a number of benefits for the elderly user. Among other users, email and social networking can help elderly users stay in touch with their loved ones, while computer education systems can assist an elderly user in learning a new language. [4] By extending user interface adjustments across computers via cloud synchronization, we give elderly users the ability to continue working with familiar applications even if they are unable to use their home computer. Additional benefits are associated with the use of mobile devices, which user profiles also may extend to. These devices have the potential to travel everywhere with the elderly user – extending their benefit beyond the home office to the world at large. The transition of desktop and web applications to mobile devices can also entice an elderly user in choosing to use mobile devices – having configured and used a given application on a desktop computer, the mobile device version of the application may be more familiar to the elderly user. Especially in this case, the graphical user interface (GUI) of the application can make it more appealing to an elderly user, or destroy interest altogether. Take into consideration the following Copyright © 2014 SERSC
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issues that may crop up when a user attempts to use a familiar application on a mobile device: Improperly-sized/colored visual elements. In the case of something such as the mobile version of a popular web browser, data – such as bookmarks, history, and passwords – is synced from the desktop application to a mobile application. However, if an elderly user took great pains to configure a desktop browser for his or her abilities, i.e. adjusting text size or colors, this data may not be transferred, requiring the configurations to be made all over again. Inaccessible interaction with application in question. Say a user was using maps software for the desktop computer, which allowed them to plot routes using their mouse and keyboard from one destination to another. Current mobile phones are often dependent on touchscreens for interaction with applications – and touch interactions are often only intuitive for users who are experienced with smartphones. As a result, the user in question may not be able to interact as freely as they previously were with the application on the desktop. Overwhelming number of options onscreen for a user to parse. Finally, many options are often added to the interface of mobile devices. A user attempting to parse these many options may find the interface slightly overwhelming – especially if their visual or cognitive abilities are not at the same level as the intended user of the application. By extending the ‘intelligent’ approach to interface design for the elderly and disabled user to the smartphone, we allow users who have previously configured proper interfaces for their abilities on a desktop computer to immediately begin use of corresponding smartphone applications, without requiring the re-acquisition of data already procured for a system. Furthermore, take into consideration that current smartphones offer a variety of extra sensors that may be used to procure additional data for the users’ interface customization settings. This all in all translates to a more positive computing experience for the user.
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Related Work
A variety of related work exists in the field of development of human-computer interfaces for the elderly: but in creating this system of synchronization, one should also look at the data collected by intelligent interfaces, in addition a basic overview of cloud computing. This said, the work related to this proposed system is divided into three categories: work in the field of elderly human-computer interfaces, work in the field of intelligent interfaces, and work in the field of cloud computing. 3.1
Human-Computer Interfaces for the Elderly
Human-computer interfaces for the elderly typically attempt to solve problems encountered by the elderly user as a result of ability impairments brought about by old age. A number of problems in vision, hearing, motor skills and cognition appear in
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the elderly user, [5] resulting in a number of devices and applications being created to skirt problems caused by such impairments. One approach commonly seen is the development of the ‘elderly-friendly’ computer, like the Telikin, which is touted as a ready-to-go elderly friendly machine. [6] Software created for the older adult computer user is also quite common – Eldy, for example, whittles the interface of a typical desktop computer down into a simplified screen consisting of several large buttons that trigger, among other things, a web browser and simplified chat software. [6] Specific applications have also been reimagined with elderly-friendly interfaces – one particular project from the University of Dundee saw the developers creating an email client and web browser customized to the abilities of the elderly user: with minimal functions, a lack of jargon, and proper visual design for elderly users. [7] However, problems crop up in these approaches due to the fact that the abilities of the elderly user vary greatly. While a number of changes to the eyes, ears, and motor skills (to name a few) come about as a result of old age, [5] the extent of these changes can vary. Developing a multitude of applications with a particular user ability level in mind can affect how said applications are received – some users eschew applications “for the elderly” as a result of feeling as if the applications are over-simplifying things for them. [8] 3.2
Intelligent Human-Computer Interfaces
Adaptable and intelligent user interfaces, with their ability to work for a range of possible users, show some of the most promise in developing software for older users. These systems often boast intelligence based on configurable variables, such as the particular range of motion of a user. Such data is often taken from a survey, although some can be generated after monitoring users’ interactions with software. Dickinson et al. (2007) created an older-customized search and navigation system allowed for three levels of content depending on user ability: a very simplified interface, an interface that included material that had not been simplified, and a third layer of material that was unconstrained by accessibility concerns. [9] Magee and Betke (2010) developed HAIL; a hierarchical web browser that provides the user with a number of levels; each corresponding to increasing complexity of the UI (increasing button size to screen width comparisons). [10] SUPPLE, a popular project from Harvard, creates a model of the users’ preferences as a result of preference statements composed by the user, and rearranges its interface accordingly – the sequel project, SUPPLE++, allows for the modeling to occur on the fly after the user works through a series of performance tasks. [11] A similar system proposed by Leiva (2012) changes the interface of a website based on users’ actions taken in navigation. [12]
3.3
Cloud Computing
Cloud computing is yet a relatively new topic, defined in September of 2011 by the National Institute of Standards and Technology as “a model for enabling ubiquitous,
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convenient, on-demand network access to a shared pool of configurable computing resources.” [13] While a variety of service models and deployment models exist, all cloud computing instances share five particular features: on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service. [13] Current consumer applications utilizing cloud computing technology range from personal storage systems [14] to document creation programs. [15]
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Utilizing Cloud Storage for User Settings
It is the intelligent interface that we hope to augment with the use of cloud storage. To better understand why cloud storage is optimal for the data stored and transmitted in intelligent interfaces, (instead of other methods of data transmission such as Bluetooth), we can discuss the nature of the data being collected. Intelligent interfaces mainly base their decisions on two types of data: automatic data, gathered via watching a user interact with software, and manual data, gathered by (among other things) survey, or recording an instance of a user making a decision regarding settings in-app. Such data is frequently combined to create a user profile, which dictates settings for a particular user based on combinations of the automatic and/or manual data gathered. SUPPLE, for instance, gathers data that is based on user survey (the gathering of preference statements) and uses said data to form opinions on particular user interfaces for the person in question. [11] The user profiles are what we seek to synchronize, and the exact data stored in these profiles should, for the sake of user privacy and security, not include exact recordings of the users’ actions in-application. We look to store timestamps, paths taken in-application, and mentions of user reactions within the application. The exact data stored would depend on the application being evaluated: for an application that simply looks to rearrange a user interface in reaction to a users’ motions in-app, such as in the case of Leiva’s app, [12] paths across the applications interface (stored via linked list or similar data structure) might be recorded. Such data could be stored in simplified formats and uploaded to cloud storage quickly. For applications that make changes based on affective markers, such as gaze tracking or posture detection applications, [16] advanced data recording would need to take place. However, due to the nature of cloud synchronization, bits of this data can be synchronized as it becomes available, instead of the bulk of it being synchronized at once – ensuring, again, quick upload times. Likewise, cloud storage is an optimal choice because of our targeting of mobile applications – we do not know what protocols future mobile devices will support, and thus storing data in the cloud and downloading it via an internet connection is the safest bet for the longevity of the service. It also allows synchronization over WiFi or 3G connections, without the need for Bluetooth to be constantly active on the laptop/desktop or mobile device. Once implemented, cloud synchronization of the user profile would offer the following benefits.
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4.1
Synchronization Across Devices
If a users’ personalization profile were stored in the cloud, the most important benefit is that the user would be able to apply the profile to all computers that ran a version of the application. This would allow the user to, if travelling, use another computer with the adaptive/intelligent interface software installed and transmit their own profile data to the computer, making it useable for them. In the case of a computer lab at a local library, if the computers were outfitted with the relevant intelligent interface software, elderly users could apply their individualized settings to the machine they wish to use – allowing them to revert the user interface to the comfortable, customized one they grew to like at home. In the case of an application with a mobile counterpart, accessing the cloud-stored profile settings would apply the relevant settings to the mobile counterpart of the application. This would greatly improve the ease of use of the application – a user would not need to worry about re-working the settings in the mobile app to match any accessibility features in the desktop app. . 4.2
Gathering Additional Data with Cloud Storage
Now, as a side effect of utilizing this cloud storage approach, we would be able to store and synchronize data captured from cell phone sensors as well. This gives us the unique opportunity to adjust desktop settings based on users’ accelerometer and GPS data, in addition to user travel trends if necessary. By tracking how a user interacts with a mobile device and which options are chosen most frequently, for example, a desktop application may have a better understanding of which options to display first to a user when they log into the accompanying desktop version of the application at home!
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Case Study: Bright, An Intelligent Healthcare Assistant
As proof of this concept, we offer the example of the theoretical application, ‘Bright.’ Bright allows a user to record eating habits, blood sugar, sleeping trends, exercise and other healthcare-related measurements on a personal desktop computer. As Bright is aimed at the older adult user, it can conform to multiple iterations of interface design to better match the needs to the individual using it – however, the setup process is lengthy, and the interface may change depending on user input over time (i.e. if a users’ eyes grow worse, Bright’s interface may adjust based on user feedback to match this trend). Elaine, an elderly adult, was asked by her doctor to use Bright to track her health trends. Elaine has mild arthritis and poor vision. When setting Bright up for the first time, Elaine works to complete a lengthy user survey, and to her delight Bright adjusts for her eyes (toning down the interface into a bold, monochromatic and simplified one) and adjusts her mouse sensitivity so it is easier for her to move her
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mouse onscreen. However, Elaine is often away from her home on the weekends: Elaine travels between her home and her children’s home then, for family outings. Behind the scenes, Bright utilizes a cloud synchronization platform that allows Elaine to log into another installation of Bright her daughter installed on their home computer, and use the program there. This version of Bright likewise adjusts the interface for Elaine’s eyes and dexterity, making it identical to her home version. However, recently the demand for Bright has expanded to the world of mobile devices, where a version of Bright named BrightM was released. Elaine receives a smartphone for her birthday, and her kids help her set it up. She’s worried when she sees the login page for BrightM, as it retains a multicolored appearance and looks vaguely unfamiliar when compared with her desktop. However, when a user starts BrightM, it synchronizes data with the cloud and brings their adjustments to the mobile device – and within minutes, BrightM becomes more sensitive to Elaine’s slow touchscreen movements, and a monochromatic interface with larger buttons overlays the screen. The improved interface makes Elaine much more prone to using the mobile app. In addition, the increased usage means the application begins to become familiar with the pattern of use that Elaine displays while using the application: additional data about her trends and the patterns she displays in data input, means that menus and the like in-application have more of an idea of what to display first for her. This only continues to improve the experience Elaine encounters with the desktop and mobile applications, and gives her an overall more positive opinion of the technology.
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Conclusion
In conclusion, we have shown that integrating cloud –stored synchronization features into intelligent interfaces for older adults have benefits of increased user comfort with use of the desktop application over multiple computers, improved mobile application usability, and an improved user interface experience as a result of additional data points being added to the users’ profile. Future work that we may want to consider involves the use of cloud computation in determining trends in the user data. By offsetting the work involved in computing trends and improve the intelligence of the existing interfaces, hopefully creating an even more tailored computing experience for the elderly user.
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