An IoT-Based System for Supporting Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) affects one out of every 54 children, according to statistics. In this paper, we use the Raspberry Pi to build a system that evaluates the efficiency of a Smart monitor for helping children with Autism Spectrum Disorder (ASD) learn and improve their quality of life. Many autistic children are very motivated and interested in Computers and smart monitors. Assistive technology systems like these encourage children with autism to communicate more. Our proposed framework demonstrates that it can support children with ASD by teaching them new skills. It helps them in making choices, respond, and tell parents what they are interested in, identify their needs, think, and maybe even feel. We implement and evaluate the performance of a new system based on Internet of Things (IOT) for supporting learning and improving the quality of life for children with Autism Spectrum Disorder (ASD). Moreover using this System the ASD kids can easily learn any Subjects with ease. Strategies for supporting the large number of students with autism spectrum disorder (ASD) in the area of literacy © 2021 IEEE.

Fusion of image quality assessment and transfer learning for COVID19 detection using CT scan image

One of the main challenges in controlling the spread of COVID19 pandemic is to diagnose infection early. The most reliable method RT - PCR takes several hours to give results. Although the Anti-Body (Serological) test gives the results in a few hours, it is not accurate, and hence it is not reliable. Moreover, they are invasive. Another issue with these methods is that the number of labs performing these tests are very limited. It will be beneficial if the already existing clinical infrastructure is used for diagnosing COVID19 accurately in real time. Recently chest CT images are used by researchers to diagnose the COVID19 with impressive accuracy. The state of the art method for detecting COVID19 using CT chest images involves Deep Learning. Deep Learning is expected to provide accurate and reliable results only when the model is trained on a large data set. Due to non-availability of a large data set the existing models have been trained on a smaller size data set. Therefore it would be better to design a model to give good accuracy with reliability. To achieve accuracy along with reliability we proposed a COVID19 detection model with the combination of deep learning model and the traditional machine learning model. The novelty of the proposed model is the fusion of image quality and deep learning. The proposed method outperformed the state of the art method in terms of accuracy, recall and F1 score (more than 99 % in almost all the metrics) on a benchmark data set. The efficacy of the selected features and also explainability of the method are demonstrated through various tests. © 2021 ACM.

Smart face mask detection using ml

After the breakout of the worldwide pandemic COVID-19.There arises a severe need of protection mechanisms, face mask being the primary one. The main aim of the project is to detect whether the person is wearing mask on live streaming image as well as on the video. The basic concept we used is of transfer learning in neural networks and the final output is to detect the presence or absence of a face mask in a video that is streaming or in an image.Till now there is no sufficient application that helps to check for a person wearing face cover or not which is on high demand in many places like transportation means, densely populated areas like schools,malls,airports etc. to ensure safety. Therefore, this system will be sufficient to detect the face mask on human faces and would drive them to be safe and secure. This system can also be used in public places to make the people aware and for their safety purpose. © 2021, Annals of R.S.C.B. All rights reserved.

Iot based embedded system for continuous healthcare monitoring

Health is consistently a significant worry in each development humanity is progressing regarding innovation. Like the new Covid assault that has destroyed the economy of China to a degree is an model how medical services has happened to significant significance. In such territories where the plague is spread, it is consistently a superior thought to screen these patients utilizing distant wellbeing observing innovation. This system is responsible for collecting pulse, body temperature and heart bit from the patient’s body and send the data into IoT Cloud platform by using WIFI-Module and health condition of patient stored in the cloud. It enables the medical specialist or authorized person to monitor patient’s health, where t he medical specialist or authorized person can continuously monitor the patient’s condition on the cloud server. The proposed outcome of thisresearch is to give suitable and effective health facilities to patients. © 2021 Universitatea de Vest Vasile Goldis din Arad. All rights reserved.