Re: Action item - web of things literature summary

Looks good Scott!

No reference to the WoT paper?
  - https://dspace.mit.edu/handle/1721.1/107831

Best,
   Shadi


On 22/11/2017 10:19, Scott Hollier wrote:
> To the RQTF
> 
> Hope TPAC went well!
> 
> I’ve completed the action item from the last meeting and include a 
> summary of the Web of Things literature review below. Much of the work 
> is based on my Internet of Things report but significantly condensed 
> with a greater focus on research and implications.
> 
> I haven’t put in any specific recommendations as yet so that others have 
> a chance to contribute literature before they are progressed.  If 
> someone is able ot find a home for it on a wiki somewhere it’d be great. 
> Content follows.
> 
> Scott.
> 
> Web of Things and access implications
> 
> 
>   1.Introduction
> 
> The significance of the Web of Things can be highlighted by its rapid 
> growth.  With an estimated 8.4 billion devices connected online by the 
> end of 2017 – up 31 per cent in 2016 and growing to an estimated 20.4 
> billion devices by 2020 (Gartner, 2017). this document is designed to 
> consider research and implications in relation to its access for people 
> with disability
> 
> 
>   2.Reasons for Web of Things popularity
> 
> Connectivity
> 
> Increased connectivity options such as fixed, wireless and mobile 
> broadband make it easier for us to engage with Web of Things devices 
> anywhere, anytime. Examples include in our homes, cars and even clothing 
> (G3ICT, 2015).
> 
> Specific environmental information
> 
> Specific information from our environment can include broad information 
> such as the current weather, specific control over the home such as 
> changing a connected light or specific individualised data collected 
> from a smart hairbrush (Bradshaw & Waters, 2017).
> 
> Affordability.
> 
> The low buy-in price of the Web of Things makes it relatively affordable 
> to implement its benefits This includes cheap devices such as the 
> Arduino (Cornel, 2015) and the Raspberry Pi range of devices (Traeg, 
> 2015) which can use sensors and actuators to provide monitoring and 
> adjustment of devices such as adjusting the temperature of a heater. In 
> addition, the ubiquitous presence of smartphones as a consumer-friendly 
> method of interaction provides an affordable method of engagement. The 
> recent uptake of digital assistants also provides affordable mechanisms 
> for Web of Things engagement.
> 
> Ease of interaction
> 
> The conversational nature of digital assistants and associated 
> smarttspeakers has evolved to a point where it is possible to provide 
> commands in a similar way to typical human interaction (Mitchell, 2016; 
> Dores, Reis, & Vasco Lopes, 2014). As a result, it is now much easier to 
> engage with devices which in turn can monitor or change our environment 
> in real-time with relative ease.
> 
> 
>   3.Benefits and Issues
> 
> The broad benefits of the Web of Things for consumers can be placed into 
> six categories (Borne, 2014)(Hollier, et. al., 2017) as follows:
> 
> §Tracking behaviour for real-time marketing: the ability to quickly 
> assess and benefit from, the target market. For example, if our 
> connected devices determined it was raining in our current GPS location, 
> advertisements relating to umbrellas and information on the nearest 
> store could be provided so that we could respond to the situation in 
> real-time.
> 
> §Enhanced situational awareness: the ability to understand and make 
> changes to our real-time environment. For example, features such as 
> updates on traffic based on movement and GPS sensors in cars and 
> smartphones allow us to take a quieter route home from work.
> 
> §Sensor-driven decision analytics: the ability to use big data to record 
> lots of information at once which can then be analysed. For example, 
> information collected from telescopes analysing space phenomenon (Lenz, 
> Meisen, Pomp, & Jeschke, 2016).
> 
> §Process optimisation: For example, the use of sensors to monitor the 
> speech rhythm, pitch and tone of a lecturer to determine the optimal 
> requirement for student engagement (Heng, Yi, & Zhong, 2011).
> 
> §Optimised resource consumption: the ability for an electrical appliance 
> to complete a task based on its ability to determine the optimal point 
> at which the costs are cheapest. For example, a smart washing machine 
> assessing the cost of power and water.
> 
> §Instantaneous control and response in complex autonomous systems: For 
> example, a series of sensors monitoring different aspects of a patient 
> in a hospital, adjusting medication and treatment in real-time as 
> sensors assess data sent and received from each other (Chiong, 2017).
> 
> Issues
> 
> The primary issues include:
> 
> ·Privacy: with digital assistants always listening for the activation 
> word, such devices can potentially monitor our environment without 
> permission leading to debates between the benefits of such devices and 
> the trade-off required in terms of privacy implications (Bradshaw & 
> Waters, 2017). Developers in privacy protections are recommended to be  
> proactive and preventative rather than reactive and remedial (Weinberg, 
> Milne, Andonova, & Hajjat, 2015).
> 
> ·Security, generally considered a related issue  to privacy (Bian et 
> al., 2016). With smartphones constantly broadcasting our GPS location to 
> a variety of sources – including the operating system manufacturers, 
> telecommunications providers and others depending on smartphone 
> permissions – there is significant concern about who has access to this 
> data and how it is being used (Lin & Bergmann, 2016). Furthermore, most 
> digital assistant interactions are not restricted to personal use 
> meaning that potentially anyone could interact with them for malicious 
> purposes such as adjusting the temperature of a refrigerator to damage 
> its contents. Furthermore, it is unlikely that most consumers would have 
> the technical knowledge to ensure their environment is secure. 
> (Skarzauskiene & Kalinauskas, 2012; Weber, 2010).
> 
> ·Interoperability: most current solutions are ecosystem-specific meaning 
> that typical Web of Things components are limited as to what device they 
> can connect. This places unnecessary restrictions on manufacturers which 
> affects the ease in which solutions can be implemented, raises costs due 
> to manufacturers having to make multiple versions of the same product 
> for different digital ecosystems, and reduces consumer choice (Zhao & 
> Qi, 2014; Lin & Bergmann, 2016).
> 
> 
>   4.Disability-related implications
> 
> 
>     4.1.Consumer engagement
> 
> There are two main benefits to the web of things for people with 
> disabilities: its use as an assistive technology and the power of 
> connectivity (Hollier et. Al., 2017). While the use of the term 
> ‘assistive technology’  is generally used to describe specific hardware 
> and software that provides access to information and communications 
> technologies for people with disabilities, the fact that such 
> technologies have the capacity to provide assistance based on human 
> limitations suggests that Web of Things is, in principle, a form of AT 
> in itself (Hennig, 2016).
> 
> The literature points to the importance of connectivity through the use 
> of connected sensor and devices in a number of different scenarios that 
> can support people with disabilities.
> 
> [NOTE:  the remainder of this document is an exert from them Hollier, 
> et. Al (2017) report and is used with permission]
> 
> The connectivity of sensors and actuators to provide disability-specific 
> monitoring – this can lead to significant improvements to the health and 
> well-being of people with disabilities. An example of this is 
> highlighted in a project created by AT&T and Premorbid in which a 
> wirelessly connected wheelchair has the ability to increase user 
> independence and freedom – the concept uses Web of Things to easily 
> monitor the wheelchair for comfort, performance, maintenance 
> requirements and location, with adjustments made in real-time (AT&T, 2015).
> 
> A second example is the ability to assist people with disabilities in 
> the achievement of everyday tasks independently such as going shopping. 
> One example focuses on a system used to help a group of vision impaired 
> people to find their way in a store. The store’s RFID system used 
> software to guide the vision impaired people and assist them with 
> scanning products to determine the relevant item (Domingo, 2011). 
> Another retail example is a pilot system developed to assist wheelchair 
> users to interact with shopping items placed beyond their arm’s length – 
> with the help of augmented reality, Web of Things and RFID technologies, 
> this allowed the user to digitally interact with the physical items on 
> the shelf (Rashid et al., 2016).
> 
> However, the primary focus of research in this area relates toe-health, 
> particularly in relation to monitoring the health of the ageing 
> population (G3ICT, 2015)and outpatient medical needs. The focus in this 
> regard is on providing proactive support to people with medical 
> conditions and potentially extending both their quality and length of 
> life (Dores et al., 2014).
> 
> Examples of e-health include the ability to provide real-time monitoring 
> of the health of seniors in aged care facilities based on an intelligent 
> monitoring system. This includes the use of sensors and actuators to 
> monitor temperature, and assess vital signs such as heart rate and 
> movement. While care givers are able to respond immediately to any 
> adverse change in conditions, seniors also have the ability to get 
> attention if they are in distress (Huang, 2013).
> 
> Another example has been applied to tracking patients in 
> e-health/telehealth applications to monitor patients once they are 
> discharged (Chiong, 2017). A point of particular interest is that while 
> the monitoring system is similar to the aged care example, the 
> implementation of the model infers that medical staff are able to 
> provide improved individual support to outpatients based on Web of 
> Things feedback such as distance travelled, temperatures in their 
> location, and food intake. As such, the non-intrusive sensors are able 
> to assess if outpatients are following the prescribed treatment and, in 
> addition, identify key factors that may have an impact on their health 
> based on lifestyle patterns.
> 
> In all these examples, the use of Web of Things data is used in a 
> largely passive way, either without the individual’s specific awareness 
> in the case of e-health or collated to assist in user choice such as the 
> shopping example. However, the broader benefit of Web of Things for 
> people with disabilities comes in the ability to assess data based on 
> their own needs in their own way and, in this regard, it is necessary to 
> review the applicability of the Web of Things user interface as it 
> relates to people with disabilities in the consumer space.
> 
> 
>     4.2.Consumer-based Internet of Things and accessibility
> 
> There are essentially three types of user interface common to 
> consumer-based Web of Things products – a built-in interface, or 
> interaction via a mobile device such as a smartphone or a standalone 
> device such as a digital assistant smart speaker. The ability for people 
> with disabilities to interact with Web of Things, and technology in 
> general, depends largely on two factors – the accessibility of the 
> interface and the use of accessible content to work with on this interface.
> 
> To make an interface accessible, disability-specific AT generally needs 
> to be built into the product.
> 
> With regards to devices that have built-in interfaces such as smart 
> refrigerators, there are currently few that have any such AT features 
> built-in, nor are there mechanisms to add features due to the 
> proprietary nature of the interface. Furthermore, even if devices such 
> as a smart refrigerator were to have an AT such as a screen reader to 
> support people who are blind, it is unlikely that, due to the 
> proprietary operating system of the device, the tool would be familiar. 
> This would therefore mean that it would require the user to learn yet 
> another way to control and interact with the device.
> 
> However, there is an initiative that may provide an access solution – 
> the Global Public Inclusive Infrastructure (GPII) created by Raising the 
> Floor (2017). In a Web of Things context, GPII could provide support in 
> that a compatible device with a built-in interface, such as a smart 
> refrigerator, could potentially change its interface based on the user’s 
> profile. For example, the interface could be set up with high contrast 
> and large print for a low vision user, or the touchscreen buttons could 
> be lowered for a person in a wheelchair. However, the concept of GPII 
> remains elusive at this point in time. As previously discussed, privacy 
> and security concerns are also present – people with disabilities would 
> need to share information about their disability-specific needs with 
> unknown third parties, and this raises concerns. In addition, the 
> large-scale network required to support the sheer volume of devices is 
> not currently available (Hollier, 2013).
> 
> The use of smartphones and other mobile devices as an alternative user 
> interface for Web of Things is therefore currently the most popular, and 
> the most accessible, option available for this purpose (Apple, 2016; 
> Google, 2016; Hollier, 2016). This is due to the two most popular mobile 
> and tablet operating systems, Apple iOS and Google Android, containing a 
> wealth of accessibility features. As such, interaction between a 
> smartphone and Web of Things device can be achieved via an app or a 
> digital assistant in an accessible manner. Furthermore, there are a 
> number of disability-specific benefits in the use of a smartphone to 
> gather information and interact in real-time. For example, the use of 
> parking sensors in a shopping centre can provide useful information to a 
> smartphone app so that a person that needs a disabled parking bay can 
> quickly identify which ones are available and which one is closest to 
> the shop being visited (Lambrinos & Dosis, 2013).
> 
> Another important benefit is affordability. While the affordability of 
> the Web of Things is helpful for everyone, it is of particular benefit 
> to people with disabilities due to the generally high costs associated 
> with disability-specific technology solutions. The Web of things can 
> offer more affordable solutions such as the implementation of home 
> automation.
> 
> However, while smartphones and apps are an effective way to engage with 
> Web of Things, much of their success depends on the need to ensure that 
> the content within the apps is accessible. To achieve this, the apps 
> need to be created in compliance with web standards.
> 
> 
>     4.3.
> 
> 
>     4.4.Current W3C WAI work
> 
> Current W3C Wai work highlights the following issues of importance in 
> addressing potential accessibility issues:
> 
> §Interoperability: for example, a connected television can be controlled 
> by a smartphone with a screen reader.
> 
> §Accessibility support: for example, a connected projector provides 
> access to the presentation data in addition to the video output.
> 
> §Configuration: for example, a profile with preferences, such as large 
> text, could be sent from one device to another.
> 
> §Privacy: for example, a connected refrigerator suggests shopping lists 
> but does not share specific dietary and health needs.
> 
> §Security and safety: for example, a connected pacemaker is safe from 
> manipulation and failure.
> 
> 
> **
> 
> 
>   5.References
> 
> AT&T. (2015). AT&T and Permobil unveil the connected wheelchair proof of 
> concept at CTIA. /AT&T Newsroom/. Retrieved from 
> http://about.att.com/story/att_permobil_unveils_connected_wheelchair.html
> 
> Apple. (2016). iOS accessibility.
> 
> Bian, J., Yoshigoe, K., Hicks, A., Yuan, J., He, Z., Xie, M., Guo, Y., 
> Prosperi, M., Salloum, R., & Modave, F. (2016) Mining Twitter to assess 
> the public perception of the “Internet of Things”. /PLoS ONE 11/(7), 
> e0158450. http://dx.doi.org/10.1371/journal.pone.0158450
> 
> Bradshaw, T., & Waters, R. (2017). The dash to connect the consumer. 
> /Financial Times./ 
> https://www.ft.com/content/67a08388-d3f8-11e6-9341-7393bb2e1b51?mhq5j=e5
> 
> Cornel, C. E. (2015). The role of Internet of Things for a continuous 
> improvement in education. /Hyperion Economic Journal, 3/(2), 24-31.
> 
> Domingo, M. C. (2011). An overview of the Internet of Things for people 
> with disabilities. /Journal of Network and Computer Applications/. 
> /35/(2), 584-596. http://dx.doi.org/10.1016/j.jnca.2011.10.015
> 
> Dores, C., Reis, L., & Vasco Lopes, N., (2014). Internet of things and 
> cloud computing. 9th Iberian Conference on Information Systems and 
> Technologies (CISTI), 18-21 June, 2014. 
> http://ieeexplore.ieee.org/document/6877071/?reload=true
> 
> G3ICT. (2015). /Internet of Things: New Promises for Persons with 
> Disabilities/. Global Initiative for Inclusive Information and 
> Communications Technology.  
> http://g3ict.org/resource_center/publications_and_reports/p/productCategory_books/subCat_2/id_335 
> 
> 
> Gartner. (2017). Gartner says 8.4 billion connected “things” will be in 
> use in 2017, up 31 percent from 2016. Retrieved from 
> http://www.gartner.com/newsroom/id/3598917
> 
> Google. (2016). Android accessibility – Overview. Retrieved from 
> https://support.google.com/accessibility/android/answer/6006564?hl=en
> 
> Heng, Z., Yi, C. D., & Zhong, L. J. (2011). Study of classroom teaching 
> aids system based on wearable computing and centralized sensor network 
> technique. /2011 International Conference on Internet of Things and 4th 
> International Conference on Cyber, Physical and Social Computing/, 
> Dalian, 624-628.
> 
> Hennig, N. (2016). Natural user interfaces and accessibility. /Library 
> Technology Reports, 52/(3), 5-17. 
> https://journals.ala.org/index.php/ltr/article/view/5969/7598
> 
> Hollier, S. (2013). The accessibility of cloud computing – current and 
> future trends. /Media Access Australia/. 
> https://mediaaccess.org.au/audio-description-on-radio/current-and-future-trends-of-cloud-computing-accessibility
> 
> Hollier, S. (2016). Affordable access. Retrieved from 
> http://www.affordableaccess.com.au
> 
> Hollier, S., et. al (2017), Internet of Things (IoT) 
> Education:Implications for Students with Disabilities. Curtin University.
> 
> Huang, J. (2013). Research on application of Internet of Things in 
> nursing home. /Applied Mechanics and Materials, 303-306, /2153. 
> http://dx.doi.org/10.4028/www.scientific.net/AMM.303-306.2153
> 
> Lenz, L., Meisen, T., Pomp, A., & Jeschke, S. (2016). How will the 
> Internet of Things and big data analytics impact the education of 
> learning-disabled students? A Concept Paper. 3rd MEC International 
> Conference on Big Data and Smart City (ICBDSC) 15-16 March.
> 
> Lin, H., & Bergmann, N. (2016). Web of Things privacy and security 
> challenges for smart Home environments. /Information, 7/(3), 44. 
> http://dx.doi.org/10.3390/info7030044
> 
> LogMeIn. (2013). Xively brings the Internet of Things to the classroom. 
> Press Release. 
> https://globenewswire.com/news-release/2013/08/21/568300/10045697/en/Xively-Brings-the-Internet-of-Things-to-the-Classroom.html
> 
> Mitchell, N. (2016). The 2016 state of the speech technology industry. 
> /Speech Technology, 21/(1), 29-41.
> 
> Raising the Floor. (2017). Global Public Inclusive Infrastructure 
> (GPII). Retrieved from http://gpii.net
> 
> Rashid, Z., Melià-Seguí, J., Pous, R., & Peig, E. (2016). Using 
> augmented reality and Internet of Things to improve accessibility of 
> people with motor disabilities in the context of smart cities. /Future 
> Generation Computer Systems/. http://dx.doi.org/10.1016/j.future.2016.11.030
> 
> Roby, J. (2016). Intelligent new products in home automation. /Air 
> Conditioning, Heating & Refrigeration News, 257/(12), 12-16.
> 
> Skarzauskiene, A., & Kalinauskas, M. (2012). The future potential of 
> Internet of Things. /Socialinės technologijos: mokslo darbai/, /1/(2), 
> 102-113. http://www.mruni.eu/lt/mokslo_darbai/st/archyvas/dwn.php?id=326522
> 
> Traeg, P. (2015). Web of Things projects: Raspberry Pi vs Arduino. 
> Retrieved from 
> https://www.universalmind.com/blog/raspberry-pi-vs-arduino-when-to-use-which/
> 
> Weber, R. H. (2010). Internet of Things – New security and privacy 
> challenges. /Computer Law and Security Review: The International Journal 
> of Technology and Practice, 26/(1), 23-30. 
> http://dx.doi.org/10.1016/j.clsr.2009.11.008
> 
> Weinberg, B. D., Milne, G. R., Andonova, Y. G., & Hajjat, F. M. (2015). 
> Internet of Things: Convenience vs. privacy and secrecy. /Business 
> Horizons, 58/(6), 615-624. http://dx.doi.org/10.1016/j.bushor.2015.06.005
> 
> Zhao, G., & Qi, B. (2014). Application of the WEB OF THINGS technology 
> in the intelligent management of university multimedia classrooms. 
> /Applied Mechanics and Materials, 513-517, /2050-2053. 
> http://dx.doi.org/10.4028/www.scientific.net/AMM.513-517.2050
> 

-- 
Shadi Abou-Zahra - http://www.w3.org/People/shadi/
Accessibility Strategy and Technology Specialist
Web Accessibility Initiative (WAI)
World Wide Web Consortium (W3C)

Received on Wednesday, 22 November 2017 13:48:08 UTC