Artificial Intelligence driven security model for Internet of Medical Things (IoMT)

The Internet of Medical Things (IoMT) has been applied to provide health care facilities for elders and parents. Remote health care is essential for providing scarce resources and facilities to coronavirus patients. Ongoing IoMT communication is susceptible to potential security attacks. In this research, an artificial intelligence-driven security model of the IoMT is also proposed to simulate and analyses the results. Under the proposed plan, only authorized users will be able to access private and sensitive patient information, and unauthorized users will be unable to access a secure healthcare network. The various phases for implementing artificial intelligence (AI) techniques in the IoMT system have been discussed. AI-driven IoMT is implemented using decision trees, logistic regression, support vector machines (SVM), and k-nearest neighbours (KNN) techniques. The KNN learning models are recommended for IoMT applications due to their low consumption time with high accuracy and effective prediction. © 2023 IEEE.

Impact of Facemasks Use on Interpersonal Communication in a Clinical Setup: A Questionnaire Based Study.

Precautionary measures such as physical distancing, wearing a mask, and hand hygiene to suppress virus transmission necessitated a shift in the communication paradigm.The study aimed to check the effects of wearing masks (N95, surgical, and cloth) due to the COVID-19 pandemic on interpersonal communication in audiology-speech-language pathology clinical setup from a clinician perspective. A total of 105 participants, 17 males, and 88 females, in the age range of 19 to 29 years (Mean age = 21.41 years; S.D = 1.6), participated in the study. A questionnaire consisting of 15 close-ended questions grouped into five major categories, Communication Effectiveness (3 questions), Visual Cues (5 questions), Physiological Effect (4 questions), Palliative Effect (1 question), and Environment Effect (2 questions) was framed. Procedure: Participants rated the questions using a binary forced-choice as either Yes or No adapted into a google form. Results showed that most questions in all five categories received an above-average "yes" response. A significant association between questions in communication effectiveness with visual cues and physiological effects was noticed, leading to the conclusion that wearing face masks impacted overall communication by affecting various parameters of speech, majorly, the voice. It was also seen that of all the participants, 60% used N95, 32.4% used cloth, and only 7.6% used surgical face masks. Speech-language pathologists have a significant role in facilitating oral/ verbal communication when such barriers are encountered in clients with communication disorders and fellow professionals with strategies to strengthen oral/ verbal communication.

Machine Learning and Deep Transfer Learning approaches were used to create a Face Mask Identification model for COVID-19

COVID-19 pandemic has led to an international health emergency the WHO considers wearing a face mask an appropriate form of public health protection. This work will describe a face mask identification model that incorporates both deep and traditional machine learning techniques. Parts of the suggested model can be divided into two. Using Resnet50, the initial part of the system is set up for feature extraction. The second component classifies face masks using decision trees, support vector machines (SVMs), and the ensemble approach. The research will focus on three face-masked datasets. The Real-World Masked Face Dataset Includes three datasets: real-world masked faces, simulated faces, and wild faces (LFW). 99.64% of RMFD's SVM classifier is accurate throughout testing.. It achieved a 99.49% accuracy rate in SMFD and a 100% accuracy rate in LFW. © 2022 IEEE.

Self-Powered Vehicle with Enhanced Battery Technology

The covid-19 pandemic has created a situation where public transportation turns out to be not advisable, and people start encouraging their vehicles for safety reasons. If this was the situation, then the number of vehicles on the road would be increased drastically which will lead to a lot of pollution problems and also demand for fuel. To balance the situation, an innovative vehicle with a self-powered facility using piezo transducer and regenerative braking technology with innovative battery pack technology has been created and it turns transportation into a sustainable one. The battery system is designed with new innovative and efficient techniques. All the innovations and designs lead to eco-friendly, sustainable, and more comfortable transport facilities with cheap prices that could be affordable by normal people. The application for the designed self-powered vehicle including Battery Management System (BMS) can be applied in various application of battery vehicles. This innovative technology move on the fact of renewable energy and the environmentally friendly process is a goal aiming to stop the the valuable natural resources which pretend to destroy. Self-powered source of energy plays a major part in the future of the nation. It is cent percent sure that the development of this prototype will indeed contribute to the technology development in electrical and electronics engineering, which make the pride of very own country, India.