Search results for: Uvais Qidwai

Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

Abstract:

This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: Uvais Qidwai, Mohamed Shakir

Abstract:

This paper presents an initial study related to the use of robotic toys as teaching and therapeutic aid tools for teachers and care-givers as well as parents of children with various levels of autism spectrum disorder (ASD). Some of the most common features related to the behavior of a child with ASD are his/her social isolation, living in their own world, not being physically active, and not willing to learn new things. While the teachers, parents, and all other related care-givers do their best to improve the condition of these kids, it is usually quite an uphill task. However, one remarkable observation that has been reported by several teachers dealing with ASD children is the fact that the same children do get attracted to toys with lights and sounds. Hence, this project targets the development/modifications of such existing toys into appropriate behavior training tools which the care-givers can use as they would desire. Initially, the remote control is in hand of the trainer, but after some time, the child is entrusted with the control of the robotic toy to test for the level of interest. It has been found during the course of this study that children with quite low learning activity got extremely interested in the robot and even advanced to controlling the robot with the Electromyography (EMG). It has been observed that the children did show some hesitation in the beginning 5 minutes of the very first sessions of such interaction but were very comfortable afterwards which has been considered as a very strong indicator of the potential of this technique in teaching and rehabilitation of children with ASD or similar brain disorders.

Keywords: Autism Spectrum Disorder (ASD), robotic toys, IR control, electromyography, LabVIEW based remote control

Procedia PDF Downloads 420

Authors: Sanober Khanum, Barerah Siddiqui, Asim Qidwai

Abstract:

Objective: To determine the risk factors and frequency of depressive trends in children and adolescents suffering from Beta-Thalassemia. Background: Thalassemia is a chronic disease affecting 10,000 people in 60 countries. Many studies show that prolonged medical conditions cause depression. Due to the invasive procedures and suffering, Beta-Thalassemia cause great psychological distress to both children and their caregivers. The study shows 14-24% prevalence of psychiatric problems in Thalassemic patients. Method: Sample consisted of 195 registered patients of A.M.T.F (Female=95 and Male=100). Based on age range the sample was divided into two groups, Group A = children (4-9 years) and Group B = adolescent (10-16 years). A detailed interview with a self-made screening measure was administered on parents to find out the level of depression in patients. Statistics: Chi-square and t-test was applied in order to analyze the data. Results show high prevalence of depression, depression n= 131(66.83%), no depression n=65(33.16%). Analyses reflect that age influences the level of depression Adolescent (71.05%) and Children (64.16%). The analysis also shows a difference in level of depression between both genders. (t=2.975, p < .05). Conclusion: There is a high possibility of developing depressive trend in children affected with Beta Thalassemia; especially females. Therefore, there is a dire need for psychological screening and appropriate treatment in order to improve physical; as well as mental health.

Keywords: childhood depression, chronic illness, psychopathology, Thalassemia

Procedia PDF Downloads 305