No abstract

Loss of the ability to speak or hear exerts psychological and social impacts on the affected persons due to the lack of proper communication. Multiple and systematic scholarly interventions that vary according to context have been implemented to overcome disability-related difficulties. Sign language recognition (SLR) systems based on sensory gloves are significant innovations that aim to procure data on the shape or movement of the human hand. Innovative technology for this matter is mainly restricted and dispersed. The available trends and gaps should be explored in this research approach to provide valuable insights into technological environments. Thus, a review is conducted to create a coherent taxonomy to describe the latest research divided into four main categories: development, framework, other hand gesture recognition, and reviews and surveys. Then, we conduct analyses of the glove systems for SLR device characteristics, develop a roadmap for technology evolution, discuss its limitations, and provide valuable insights into technological environments. This will help researchers to understand the current options and gaps in this area, thus contributing to this line of research.

ABSTRACT

Augmented Reality or "AR" has been recognized for its significant importance in different areas of technology, not to mention its significant presence in the education sector. This research aimed to map the relevant literature on AR usage with the aim of rehabilitating people with disabilities. The search was performed on three databases: Science Direct, IEEE Explore and Web of Science from 2013 to 2018. . Based on our inclusion and exclusion criteria, (n=13) articles were selected. Seven of the studies (n=7/13) intellectual disability. Six of the studies (n=6/6) physical disability. The basic idea of this article is to measure the size of the virtual environment utilization in order to rehabilitate the disabled, in addition to the ability of modern technology to restore people with disabilities to normal life and integration into society. This research is expected to display the current literature in this area and to increase the understanding of this research field.

IoT (Internet of Things) has become a separate research field since the development of internet technology and other communication media. IoT optimizes several tools such as sensor media radio frequency identification, wireless sensor networks and other smart objects that allow humans to easily interact with all devices connected to the internet network. The purpose of this research is to build an IoT-based solar cell tracker which can be controlled through mobile Apps and the data can be read anywhere as long as there is an internet network. In this research used LDR sensor, DHT11 sensor, Voltage sensor and MPU6050 sensor to optimize the performance of the proposed solar cell tracker system. The control system is built using an Appinventor that allows the system to be controlled via cellular phone from a distance. All sensors will be connected via Arduino and realtime data can be viewed through the Thinger.Io web page using Raspberry and mini LCD. ESP8266 NODE MCU microcontroller is used for a Wi-Fi connection. The results of this study indicate that the voltage value generated by dynamic solar cell tracker is greater than the static solar cell tracker. Dual axis sun tracker devices that are built using four LDRs produce an average voltage of 19.40 Volt when the sunny weather, 18.05 Volt when the cloudy weather and 13.60 Volt when the rainy weather.