Review: Mass Screening framework for children with dyslexia using IOT and computing analysis

Abstract

Dyslexia is a medical disorder due to which children have difficulties in learning and reproducing the learnt concepts. In this context children are mostly considered to be not interested or negligent towards their studies. According to dyslexia association of India 10-15 % of children enrolled in schools suffer from some type of Dyslexia. Awareness on Learning difficulties and detection is a complicated. As detection of LD requires diverse features it requires proper guidance and intervention. The issues with explicit learning difficulties in kids have been a reason for worry to parents and educators. Its challenging for the teachers and educationalists to differentiate students with LD and other students. This paper mainly analysis of the paper titled "Diagnosis of Dyslexia using Computing Analysis", Electroencephalogram (EEG) as a tool is used for understanding of brain process and related functions, Number of factors related to Dyslexia and "Power spectral density" is extracted using Gibson test for brain skills. And to identify differences in brain processing using EEG Technology in kids with dyslexia and non-dyslexic. Data sets are generated classifying Dyslexic and non dyslexic and were analysed using the K-means, Fuzzy and ANN classifiers. then the results obtained from these classifiers differentiate between the three different groups (dyslexic, non-dyslexic and disordered). And the next paper "Spatial Blockchain-based Secure Mass Screening Framework for Children with Dyslexia", this paper was mainly focused in detection of symptoms of dyslexia at an age of 8-11 years, so that children can be assisted with various assisting tools and take technologic support so that children can take part in regular schools. This paper is based on Mobile Edge Computing, cloud computing.

Industry 5.0 in Smart Education: Concepts, Applications, Challenges, Opportunities, and Future Directions

“…Hearing impaired students can use automated language translation devices, visually impaired students can use AR, VR and sensor based smart sticks and headsets; smart doors are used for ease of navigation establishing a better learning environment application that helps in monitoring of student behaviour. The automation of administrative tasks using such IoT devices have extensively reduced workload of the teachers enabling them to focus on value added academic activities making the system more agile and lean [85].…”

Edge intelligence enabled Internet of Things

“…In the paper entitled "Review: Mass Screening framework for children with dyslexia using IOT and computing analysis", Mulakaluri1 et al developed an ehealthcare IoT solution that can help to monitor dyslexia for children with learning difficulties [3]. This work compared the IoT devices collected Electroencephalogram (EEG) to analyse brain process and related functions.…”

“…This can also reduce the risks to pose data on the IoT. This issue discusses four key applications of edge intelligence enabled IoT: smart meters [1], indoor navigation using IoT devices [2], smart healthcare [3], and intelligence wearable IoT solutions [4].…”