Problem Statement

The recent years have seen the prevalence of Autism Spectrum Disorders (ASD) increase at unprecedented rates. So far, the developmental condition is listed among the major cases of mental disorders in various parts of the worlds including the UK, US, and India. Note that the incidence rates in the mentioned regions are 1 in 64, 1 in 68, and 1 in 150 respectively (Kuriakose & Lahiri 2017). Such a realization is quite devastating considering the detrimental impact of the condition on the victim’s social life. The implications are felt by not only the autistic individuals but also their direct guardians (mainly parents). At this point, the reader is urged to consider the established facts regarding autism. The lifelong condition is usually evidenced in children under the age of 3, and it curtails their ability to communicate normally, form social relationships, and engage in normal behavior. While this disorder is barely understood from a causal perspective, most researchers and practitioners argue that it results from defects in the brain regions dealing with memory retention, motor skills, and empathy.

Fortunately, the escalation in the prevalence rates is concurrent with the digital revolution. The modern world is characterized by sophisticated levels of Information and Communications Technology (ICT) advancements that appear instrumental in the alleviation of most of the communication and socialization challenges faced by autistic children. As far as autism is concerned, major strides have been made in the fields of Information Technology and robotics (Teevan, Dumais, & Horvitz 2017). A broad range of computer, smartphone, and artificial intelligence (merged with robotics) software have been developed to help this population cope with their communication and socialization needs (Golestan, Soleiman, & Moradi 2017). The applications have been tailored to meet the special learning capabilities of autistic children. Nevertheless, there is too much fragmentation in the emergent interventions on the same. For this reason, this dissertation project proposes a cloud-based approach so as to allow the patients to access a broad range of learning interventions on a broad project: consider the scope of the World-Wide Web.

By now, it is apparent that different interventions have emerged in attempt to improve the lives of people suffering from autism. Some of the common applications include Pocket PC Picture Exchange Communication System (PECS), Let’s Talk Voice Output Communications Aid (VOCA), dmTEA, and AUTHIC. Note that the first two focus on developing the children’s communication skills (Shminan, Sharif, Adzani, & Lee 2017). dmTEA is a diagnosis tool while AUTHIC improves the patient’s emotional capabilities. It suffices to restate that the mentioned applications are among the various interventions implemented for autistic individuals. Such a trend demonstrates the problematic state of the current progress with respect to the disorder. Logically speaking, it is almost impossible for a single autistic child to benefit from such a fragmented approach. Such a bold sentiment follows the fact that one cannot access all of the applications regardless of the fact that they focus on different aspects of ASD. Perhaps, a cloud-based approach can solve this problem by enhancing the accessibility of the distinct functions – includes digital library, virtual reality (VR), and artificial intelligence (AR) – on a single platform(s).

Literature Review

At the moment, there is a conventional agreement among researchers, academicians, and practitioners regarding the need to invent large-scope solutions for the growing autistic populace. Leroy, Chuang, Huang, and Charlop-Christy (2005) demonstrate their agreement by acknowledging the fact that ASD is the third most prevalent neurological disorder in the United States. Similar sentiments are held by Kuriakose and Lahiri (2017) as they believe that its prevalence expands beyond the U.S. borders. According to them UK and India are also recording high incidence rates. Such perspectives are vital in understanding the global status attained by autism. It is important to know this fact since it supports the idea that the interventions should be geared towards the attainment of broad needs.

It appears wise to assert that the preceding paragraph does not intend to disregard the current progress made in the field. For instance, Kuriakose and Lahiri (2017) propose a VR-based application that utilizes a simulated environment to teach basic communication and socialization skills to the autistic children. This innovation can be said to be an extension of Iyer and Kalbande’s proposed autistic game (2014). Unlike Kuriakose and Lahiri’s invention, the game is played on a personalized graphical user interface (GUI). At this point, one should reflect on this project’s thesis: a cloud-based approach can allow the autistic users to access a broad range of interventions from a single application.

When placed into perspective, a huge operating system can be created where both GUI and VR functions can be accessed by the autistic children. For the sake of this argument, the search engine concept described by Zamir, Korn, Fikes, and Lawrence (2010) is quite illustrious: such a system utilizes a user profile to extract relevant information based on the user’s query. With the help of the guardian/practitioner, an autistic child can utilize this system to access various functions including the learning medium (VR or tablet mode), the learning concepts (communication, basic mathematics, or socialization), and level (based on progress). Of course, such a platform must adhere to the improvements suggested by Kodgiwar (2016). According to her, content based image retrieval (CBIR) allows the system to access data based on graphical searches. This function is quite beneficial for children suffering from autism since they are more efficient with visuals than words (Kamaruzaman & Azahari 2014). In their research, Agarwal, Sharma, and Dubey (2016) noted that CBIR can be improved to facilitate sketch image queries. Such an operating system can only be efficient if it is full of visuals and colorful features.

• Apparently, the current ICT interventions geared towards the improvement of autism are functionally fragmented. Can they be integrated to form a broad cloud-based application/software (like the World Wide Web)? If so, how will the proposed solution resolve the current problem?

Primary Research

Sampling and Data Collection. Considering the nature of this investigation, the researcher will utilize information collected from professionals in the fields of Computer Science and Psychology. The survey will be conducted in focus groups: 10 groups of 8. Note that eight participants per group will include male and female specialists from both fields in equal proportions. The researcher prefers 10 focus groups due to the scope of the proposed project: it involves the integration of various ICT infrastructures to serve a general purpose. Each group will have a designated facilitator who will collect the responses garnered from the posed research question.

Analysis. After collection, the information will be collated then assessed to enhance the researcher’s grasp of the potential merits and demerits of the proposed project. It is through this process that the applicability of the proposed solution can be tested before the design and implementation process begins.

Design. As mentioned earlier, the integrated cloud-based application for ASD patients will utilize the structure of a typical search engine. The only difference is that it will be highly graphical due to the content/sketch-based image retrieval algorithms.

Development. By default, such a platform is broad. It will necessitate various procedures including license acquisition, prototype development, and network expansion. Each stage demands huge amounts of financial and human resources. Not to mention the fact that such a project can take up-to a year before completion.

Testing. The software will be tested during the prototype stage. Further development can only continue after the prototype proves functional.

Evaluation. The evaluation process will be based on the number of ASD users in the system.

References

Argawal, S., Sharma, R. and Dubey, R. 2016, Sketch-based image retrieval using watershed transformation. Second International Conference on Computational Intelligence & Communications Technology, 2(1).

Golestan, S., Soleiman, P. and Moradi, H. 2017, Feasibility of using Sphero in rehabilitation of children with autism in social and communication skills. International Conference on Rehabilitation Robotics (ICORR), 1(1).

Iyer, S. and Kalbande, D. 2014, Research on educative games for autistic children. International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA), 1(1)

Kamaruzaman, M.F. and Azahari, M.H.H. 2014, Form design development study on autistic counting skill learning application. International Conference on Computer, Communication, and Control Technology, 1(1).

Kodgiwar, V. 2016, Application of content-based image retrieval for e-commerce. World Conference on Futuristic Trends in Research and Innovation for Social Welfare, 1(1).

Kuriakose, S. and Lahiri, U. 2017, Design of a physiology-sensitive VR-based social communication platform for children with autism. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(8).

Leroy, G., Chuang, S., Huang, J. and Charlop-Christy, M.H. 2005, Digital libraries on handhelds for autistic children. JCDL 5(1).

Shminan, S.A., Adzani, A.R., Sharif, S. and Lee, N.K. 2017, Autipecs: Mobile Based Learning of Picture Exchange Communication Intervention for Caregivers of Autistic Children. New York, USA: IEEE.

Teevan, J., Dumais, S. and Horvitz, E. 2017, Personalizing search via automated analysis of interests and activities. ACM SIGIR Forum, 51(3).

Zamir, O.O., Korn, J.L., Fikes, A.B. and Lawrence, S.R. 2010, United States Patent. Patent No. 7693827B2.