Impact of Covid-19 on the Usage of Ai with Respect to Chat Bots in Hotels

Nobody might at any point imagine that this world would come at a halt in 2020, when the Covid 19 previously hit nobody accepted it could get such gigantic changes which would change the world as far as we might be concerned. It welcomed on many changes like work-from-home, social separating, changes in how cleanliness is kept up with and with it hits to various enterprises as well as an opportunity to arrive at new levels regarding innovation, particularly in lodgings. With the requirement for contactless assistance during the pandemic, the upsides of an AI attendant turned out to be significantly additionally articulated. The study descriptive in nature and adopted snowball sampling for collecting the data. The study the impact of covid -19 on the usage of artificial Intelligence, regression analysis was applied and found that among AI and RS AI (Chat-bots, Motion Detectors, Voice Recognition System) and RS (Online Reservation AI TOOLS INFLUENCING GUEST IN HOTELS 69 Portal), RS is relatively more important than the AI in explaining the guest intensity to stay. Study also explained that customer age is not significantly (0.103) impacted the guest intensity to stay in hotel. Copyright © 2023 Authors. All rights reserved.

Design and Evaluation of Noncontact Elevator Control Mode and User Interface

In response to the global coronavirus disease 2019 (COVID-19) pandemic, the use of short-term confined spaces has attracted widespread attention, and elevators have become a major pathway for pathogens. This study uses video recognition technology to develop a contactless elevator operating system, which can be operated by hand gestures of the user. This design can solve current elevator usage problems by integrating human and spatial aspects into the control mode and user interface. By observing and analyzing operational interfaces and behaviors in current hospital elevators, specifications for the new interface were developed. A video motion recognition sensory system was applied to formulate the design and planning principles of the noncontact elevator. Gesture images were combined with simulations to create experimental tasks, in which users were timed and interviewed to evaluate the acceptability and efficiency of the designed interface. The results of this study show that the planning and design of noncontact elevator control modes and user interfaces are advantageous, intuitive, and easy to learn. The control interface of the elevator was displayed in an electronic panel using colors, shapes, and sizes to show operational information, enabling a quick search and high learnability. © MYU K.K.

Detecting and Visualizing Stops in Dance Training by Neural Network Based on Velocity and Acceleration.

Various genres of dance, such as Yosakoi Soran, have contributed to the health of many people and contributed to their sense of belonging to a community. However, due to the effects of COVID-19, various face-to-face activities have been restricted and group dance practice has become difficult. Hence, there is a need to facilitate remote dance practice. In this paper, we propose a system for detecting and visualizing the very important dance motions known as stops. We measure dance movements by motion capture and calculate the features of each movement based on velocity and acceleration. Using a neural network to learn motion features, the system detects stops and visualizes them using a human-like 3D model. In an experiment using dance data, the proposed method obtained highly accurate stop detection results and demonstrated its effectiveness as an information and communication technology support for remote group dance practice.

Mime 3D: A Patient Monitoring System

The Covid-19 Pandemic has affected the entire world. Most notably, the healthcare industry has been under constant pressure to treat patients. Spikes in the number of patients have put the workforce under tremendous pressure. Doctors and nurses are finding it difficult to observe multiple patients at the same time. In addition to that, medical practitioners are reluctant to deal with the diagnosis and treatments, as it requires frequent physical intervention. The aim of this project is to reduce this strain on medical practitioners by developing a system that aims to constantly track the activity of the patients and replicate the same using a 3D Human Model. For this multiple Inertial Motion Sensors (IMU's) are used that will collect the motion data of the joints of the patient, with help of which our 3D Model will replicate the actions. The system will use Internet of Things and Cloud Computing to collect and transfer data to the web application. All the activity of the patient can be monitored using fully authenticated web applications by doctors and even by the family members. Thus with the help of the technology patients can be monitored without any physical intervention and the risk of getting affected by viruses or diseases for the doctors is also minimized. © 2022 IEEE.

ASSESSMENT OF MOBILE APPS FOR ADULTS WITH KNEE/HIP OSTEOARTHRITIS

Purpose: Greater access to smartphones and mobile app technology, coupled with the COVID-19 pandemic, has fueled a growing interest in mobile health apps. Patients with knee and/or hip osteoarthritis (OA) may benefit from mobile apps when seeking additional guidance and advice. Clinicians may leverage these apps for symptom monitoring, activity tracking, and exercise program delivery. Integrating mobile apps into patient care may empower self-management and enhance communication, therapeutic alliance, and treatment adherence. Mobile apps could also facilitate access to healthcare services and reduce costs. However, little is known about the quality of these apps. We aimed to synthesize and evaluate current available mobile apps for adults with knee/hip OA. Methods: We searched Apple App Store, Android Google Play, and Amazon App Store for mobile health apps targeting management of knee/hip OA. Inclusion criteria for appraisal: available in English;containing search terms of “knee”, “knee OA”, “hip”, “hip OA”, “osteoarthritis”, “arthritis”, “physical therapy”, “rehabilitation”, and/or “rehab” in the app description;targeting knee and/or hip OA;and free to download. Exclusion criteria for appraisal: apps specific for rheumatoid arthritis;unavailable for download;could not be opened due to incompatibility;requiring subscription, passwords, institutional accounts, download fees, or additional accessories (e.g. motion sensor) for usage. The search was terminated for each search term when the last 10 apps on a platform did not meet the inclusion criteria, consistent with the methodology used in prior research. Paired reviewers rated apps using the adapted Mobile App Rating Scale (MARS) (score range 0-132, higher is better) that appraises apps by technical aspects, engagement, functionality, aesthetics, information, quality, and relevant information to the subject matter. Disagreements were resolved by discussion between 2 reviewers. Apps that scored ≥3/5 on overall app quality or totaled ≥80/132 were included in the final descriptive summary. Results: Among 797 identified apps, 41 met inclusion/exclusion criteria for MARS appraisal. As shown in Figure 1, 17 apps met the pre-determined score thresholds for final summary. Their key characteristics are summarized in Table 1. The median MARS score was 86 (interquartile range = 23 and ranged from 63 to 115). App features varied. Common app features were exercise recommendations, education, goal setting, and improving well-being. Many apps allowed for social media sharing and included measures to protect privacy. 11 apps demonstrated low to moderate credibility. Jointfully Osteoarthritis (Apple), My Arthritis (Apple), and Jointfully Osteoarthritis (Android) were the top three rated apps. They also were the only apps receiving an overall 5/5 quality rating. Conclusions: While many no-cost apps targeting knee/hip OA management exist, only three were rated highly. Features varied widely in our sample. Future research is needed to identify optimal app designs and functions for self-management strategies tailored to patients with knee/hip OA. Evaluating whether incorporating mobile apps in patient care improves outcome, treatment adherence, and patient satisfaction will help guide clinical practice recommendations. [Formula presented] [Formula presented]