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Through the last decade, and particularly after the Covid period (2020 - 2022), crowd counting and localization have attracted much attention of AI researchers due to its potential applicability in crowd monitoring and control, public safety, space design, interactive content delivery etc. Once delivery objectives for a system are envisaged and the premises are fixed, we can always construct manifold technology architecture that delivers the set goals. However, in the Indian context a solution of choice needs to be optimized on frugality and ease of adaptability. In this paper we report an economic and replicable application of crowd counting and interactive content delivery in museums through unbiased knowledge systems embedded in robotic museum assistants. We intend to demonstrate a robotic system that can deliver any gallery content to groups of visitors keeping special focus on the exhibits that are popular choices. Crowd counting is used here to enable the content presentation to a group of choice in an interactive way. There are some market-ready solutions available for interactive gallery demonstration by moveable robots but they require not only huge capital investment but are also of limited use within controlled environments. Our proposed design is to multiplex an existing infrastructure of surveillance system as a smart crowd counting and gallery demonstration system along with crowd management with minimum additional hardware infusion. © 2023 IEEE.
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Currently, the implementation of chatbots or virtual assistants presents great benefits for the companies or institutions that use them, since their use allows the user to establish a communication through a program that is integrated to a certain messaging system. Virtual assistants are programmed to communicate with the client and solve their doubts without a person attending them, and their main advantage is that they are always available to interact with users at any time the person requires it. This research aims to evaluate how it affects the use of chatbots in the process of counseling students of the Technical University of Manabi, since with all the technological advances that have been occurring over the years with the implementation of chatbots in the area of education has increased, the application of these virtual assistant systems in schools and universities has increased its popularity of implementation in these times, where virtual education is widely used as a result of the pandemic of covid-19, a situation that has faced the vast majority of countries worldwide. The methodology used for this research is quantitative, bibliographic and experimental. Bibliographic because a research is carried out on works related to the proposed topic. Experimental because it is based on the development of a chatbot in Telegram, which will be executed and subsequently evaluated through a Likert scale survey that aims to determine the QoS of users with respect to the chatbot. The results obtained from the student surveys show a high level of acceptability and satisfaction with the chatbot service, therefore, it is recommended that this service be incorporated at the institutional level, in order to provide information support to users without time constraints. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Cardiovascular diseases (CVDs) are the leading cause of mortality in Europe, with potentially more than 60 million deaths per year, with an age-standardized rate of morbidity-mortality higher in men than women, exceeding deaths from cancer. Heart attacks and strokes account for more than four out of every five CVD fatalities globally. After a patient overcomes an acute cardiovascular event, they are referred for rehabilitation to help them to restore most of their normal cardiac functions. One effective way to provide this activity regimen is via virtual models or telerehabilitation, where the patient can avail themselves of the rehabilitation services from the comfort of their homes at designated timings. Under the funding of the European Union's Horizon 2020 Research and Innovation program, grant no 769807, a virtual rehabilitation assistant has been designed for elderly patients (vCare), with the overall objective of supporting recovery and an active life at home, enhancing patients' quality of life, lowering disease-specific risk factors, and ensuring better adherence to a home rehabilitation program. In the vCare project, the Carol Davila University of Bucharest (UMFCD) was in charge of the heart failure (HF) and ischemic heart disease (IHD) groups of patients. By creating a digital environment at patients' homes, the vCare system's effectiveness, use, and feasibility was evaluated. A total of 30 heart failure patients and 20 ischemic heart disease patients were included in the study. Despite the COVID-19 restrictions and a few technical difficulties, HF and IHD patients who performed cardiac rehabilitation using the vCare system had similar results compared to the ambulatory group, and better results compared to the control group.
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COVID-19 , Cardiac Rehabilitation , Cardiovascular Diseases , Heart Failure , Myocardial Ischemia , Telerehabilitation , Male , Humans , Adult , Female , Aged , Cardiac Rehabilitation/methods , Quality of Life , Case-Control Studies , RomaniaABSTRACT
If understanding sentiments is already a difficult task in human-human communication, this becomes extremely challenging when a human-computer interaction happens, as for instance in chatbot conversations. In this work, a machine learning neural network-based Speech Emotion Recognition system is presented to perform emotion detection in a chatbot virtual assistant whose task was to perform contact tracing during the COVID-19 pandemic. The system was tested on a novel dataset of audio samples, provided by the company Blu Pantheon, which developed virtual agents capable of autonomously performing contacts tracing for individuals positive to COVID-19. The dataset provided was unlabelled for the emotions associated to the conversations. Therefore, the work was structured using a sort of transfer learning strategy. First, the model is trained using the labelled and publicly available Italian-language dataset EMOVO Corpus. The accuracy achieved in testing phase reached 92%. To the best of their knowledge, thiswork represents the first example in the context of chatbot speech emotion recognition for contact tracing, shedding lights towards the importance of the use of such techniques in virtual assistants and chatbot conversational contexts for psychological human status assessment. The code of this work was publicly released at: https://github.com/fp1acm8/SER. © 2023 The Authors. Cognitive Computation and Systems published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology and Shenzhen University.
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There is a great interest in online learning systems, especially due to COVID-19 pandemic. However, there are a lot of limitations and challenges of online laboratory learning systems. This paper presents an efficient technique that provides an intelligent virtual tutor for online laboratory environment, as in engineering and science sectors. Based on the analysis of the student's mouse activities, the AI virtual Assistant or virtual tutor will automatically estimate the difficulties that the student stuck during conducting the steps of lab's experiment. Hence, the virtual tutor can assist the student, accordingly. The technique is based on multi-threshold that are used to discriminate different levels of difficulties. The values of these thresholds are estimated and optimized via the genetic algorithm. The experimental results show that discrimination between different student behaviors can be achieved accurately and efficiently. © 2022 IEEE.
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The COVID-19 pandemic, a flood of information and news from various sources has raised numerous questions in people's thoughts concerning the disease. COVID-19 is a coronavirus, which encompasses the Severe Acute Respiratory Syndrome (SARS) virus and Middle East Respiratory Symptoms (MERS) virus. Coronavirus is a virus family that comprises virus types that cause the flu and the common cold.Chatbots and voice assistants are becoming increasingly popular ways for people to connect with systems. The days of interacting with services simply through a keyboard are long gone. Artificial Intelligence and Machine Learning developments have contributed to the development of these new types of user interaction. We'll focus on the development of chatbots as a channel for information distribution via an Android application in particular. With over 2.5 billion active users globally and over 3 million devices utilizing this Android application, it is certain to reach a large number of people.A chatbot is proposed in this study to eliminate information pollution, including false information regarding COVID19, and to provide the right responses to people's concerns. In the realm of natural language processing, a chatbot is a popular discussion system (Natural Language Processing). Chatbots are software that allows computers and people to converse. The chatbot is created on the Android platform and uses the RASA [13] open-source framework to answer inquiries regarding COVID-19. It also offers a Rapid API [14] that keeps information on COVID-19 up to date. It delivers correct information by updating the material on a regular basis. © 2022 IEEE.
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Purpose>This paper attempts to provide significant information on the increased growth of literature of chatbots and virtual assistants. Technological changes are dynamic and keep changing at regular intervals. Therefore, it becomes highly crucial to review the performance of chatbots and virtual assistants. This paper aims to review the literature by eminent researchers in the form of authors, keywords and major contributing organizations.Design/methodology/approach>Systematic literature review and bibliometric analysis is used to analyze the growth of literature on chatbots. A sum of articles has been extracted from Scopus database with selected keywords and with certain filters. VOSviewer software is used for analysis of data. A total of 130 documents are extracted from Scopus database from 2017 to 2021 (31st August).Findings>This study provides a significant contribution to an existing literature and provides the understanding of research in the area of chatbots and virtual assistants. The authors with maximum number of citations are Yan, Zaho, Bengio, Weizenbaum, Song, Zhou and Maedche with jointly 180 citations. Research is been contributed by different countries where the United States is the country with highest number of documents published. The United States contributes 17% of the total production in the area of chatbots and virtual assistants. The analysis shows that the area is gaining momentum as contribution in this area is been increasing in last few years.Research limitations/implications>The study shows that several branches of chatbots are also in mainstream like natural language processing, e-learning, behavioural research, conversational agents, virtual assistants, human–computer interaction, natural language and so on. It provides a wider scope to authors and researchers to gain useful insights. The bibliometric study will provide a broader spectrum in this area.Social implications>The developments in technology and also the effect of COVID-19 pandemic is boosting the adoption of technology in different sectors. Deployment of technology will uplift the economy and social infrastructure. Society can avail different services from their comfort area and also in real time. This will help in reducing wastage of resources like people visiting offices for routine jobs which can be easily availed from their workplace. Society may access better services without much human interaction.Originality/value>This paper adds significant contribution to the existing literature by analysing the published papers from Scopus database. The study contains new and significant information as this study covers all industries where chatbots and virtual assistants are being applied whereas in previous literature only specific industry has been taken into consideration.
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Due of the current COVID-19 pandemic crises, there is a worldwide need for quick medical findings. Furthermore, due to a lack of medical facilities and medical practitioners' hectic schedules, several examinations must now be performed by the general public. Also because of the high rate of transmissibility of COVID-19, even asymptomatic patients can readily transfer the virus to others, faster detection is critical during the initial phase of COVID-19, which is early identification. The earlier a patient is detected;the better the virus's spread may be stopped and the patient can undergo proper treatment. As the nationwide vaccination process is in its later part, it is obvious that the government will uplift its regulations and the employees will have to return to their workplaces or offices. As a solution to this upcoming urgency the authors would like to propose a solution to identify COVID-19 patients in advance at corporate level. As an IoT based solution a device is supposed to be setup on top of each employee's desk, which in return will be used to monitor the oxygen level, temperature, and heartbeat rate of the employees. © 2022 IEEE.
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Purpose This paper attempts to provide significant information on the increased growth of literature of chatbots and virtual assistants. Technological changes are dynamic and keep changing at regular intervals. Therefore, it becomes highly crucial to review the performance of chatbots and virtual assistants. This paper aims to review the literature by eminent researchers in the form of authors, keywords and major contributing organizations. Design/methodology/approach Systematic literature review and bibliometric analysis is used to analyze the growth of literature on chatbots. A sum of articles has been extracted from Scopus database with selected keywords and with certain filters. VOSviewer software is used for analysis of data. A total of 130 documents are extracted from Scopus database from 2017 to 2021 (31st August). Findings This study provides a significant contribution to an existing literature and provides the understanding of research in the area of chatbots and virtual assistants. The authors with maximum number of citations are Yan, Zaho, Bengio, Weizenbaum, Song, Zhou and Maedche with jointly 180 citations. Research is been contributed by different countries where the United States is the country with highest number of documents published. The United States contributes 17% of the total production in the area of chatbots and virtual assistants. The analysis shows that the area is gaining momentum as contribution in this area is been increasing in last few years. Research limitations/implications The study shows that several branches of chatbots are also in mainstream like natural language processing, e-learning, behavioural research, conversational agents, virtual assistants, human-computer interaction, natural language and so on. It provides a wider scope to authors and researchers to gain useful insights. The bibliometric study will provide a broader spectrum in this area. Social implications The developments in technology and also the effect of COVID-19 pandemic is boosting the adoption of technology in different sectors. Deployment of technology will uplift the economy and social infrastructure. Society can avail different services from their comfort area and also in real time. This will help in reducing wastage of resources like people visiting offices for routine jobs which can be easily availed from their workplace. Society may access better services without much human interaction. Originality/value This paper adds significant contribution to the existing literature by analysing the published papers from Scopus database. The study contains new and significant information as this study covers all industries where chatbots and virtual assistants are being applied whereas in previous literature only specific industry has been taken into consideration.
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Using intelligent virtual assistants for controlling employee population in workspaces is a research area that remains unexplored. This paper presents a novel application of virtual humans to enforce Covid-19 safety measures in a corporate workplace. For this purpose, we develop a virtual assistant platform, Chloe, equipped with automatic temperature sensing, facial recognition, and dedicated chatbots to act as an initial filter for ensuring public health. Whilst providing an engaging user interaction experience, Chloe minimizes human to human contact, thus reducing the spread of infectious diseases. Chloe restricts the employee population within the office to government-approved safety norms. We experimented with Chloe as a virtual safety assistant in a company, where she interacted and screened the employees for Covid-19 symptoms. Participants filled an online survey to quantify Chloe’s performance in terms of interactivity, system latency, engagement, and accuracy, for which we received positive feedback. We performed statistical analysis on the survey results that reveal positive results and show effectiveness of Chloe in such applications. We detail system architecture, results and limitations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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In the modern era computers are becoming faster, smarter and better. Their usage is rising in the fields such as medicine, business administration, education etc. So there is a need for simplifying the operability and usability of a computer. Digital virtual assistants are known for easing the interaction with computers. Since most of the digital virtual assistants use voice as mode of communication deaf and dumb persons are finding it difficult to use virtual assistants on their devices. This research work attempts to propose a voice and gesture based virtual assistant that can be used by disabled as well as non disabled persons to perform common tasks on their computers. The main aim of this research paper is to develop natural human-machine interaction. Input to the virtual assistant is the user's choice. Users can choose to communicate using voice and gestures or operate a mouse pointer using gestures. In thee proposed system, gestures are recognized even in low light conditions. So, the proposed system is very much helpful in all day conditions. It can be of great help in times like Covid-19 pandemic to be contact free as well as for people with disabilities. © 2022 IEEE.
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Since the discovery of corona virus (nCOV-19), and its subsequent progression into a global pandemic, an enormous hurdle faced by hospitals and their healthcare staff has been to streamline, and look after the huge flow of cases. It has become increasingly difficult to consult a Covid specialist when the first wave occurred in rural and areas not connected as well to modern amenities. Thus, it has become obvious that an interactive Chatbot with efficient execution can help patients living in such areas by educating on the appropriate preventive measures, news on virus strains, reducing the psychological damage caused by the fear of the virus and mental effects of solitary isolation. This study displays and discusses the schematics of an artificial intelligence (AI) chatbot for the purpose of evaluation, diagnosis and recommending immediate preventive as well as safety measures for patients who have been exposed to nCOV-19, and doubles as a virtual assistant to aid in measuring the severity of the infection via symptom analysis and connects with the authorised medical facilities when it progresses to a serious stage. © 2022 IEEE.
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In the twenty-first century, Internet of Things (IoT) has boomed to be impossible to not to relate to. From computers, mobile phones, smart watches or your virtual assistants, everything is connected to the complex web of IoT. With the technological development in this century, healthcare sector has also had its fair share of innovations including innovation related to healthcare, diagnostics, sensors, or even data analytic along with development in Machine Learning and Artificial Intelligence. IoT in healthcare is expected to help improve the quality of life for the people due to the flexibility that it provides. We looked at the significant amount of work done in this sector, and found a trend that COVID-19 has only spurred the development of this field. We explored both the benefits and challenges that IoT in Healthcare might possess and have addressed challenges such as data security, cloud integration problems. Additionally, we looked at the issue of data security in depth and along with the current method of LSCSH being used, we have recommended that Zero-trust architecture being used as well as it caters to the needs of the evolving data management space. From 2013, IoT in healthcare has dominated the space as new devices are released and there has been a boom of devices that are being developed and being researched on. Most of the devices are affordable and some can even be accessed with a small subscription fee. Our results show us that IoT has started to pick up its popularity since 2015 as companies succeeded to win the trust of the market. Even though most of the development for these technologies look to come in the future, the progress made in the recent years look promising. © 2021 IEEE.
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Purpose: The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations. Design/methodology/approach: The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic. Findings: The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper. Research limitations/implications: Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis. Practical implications: First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data. Originality/value: As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic. © 2022, Emerald Publishing Limited.
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Since the last months of 2019 with the arrival of COVID-19, jobs changed due to confinement;for this reason remote work increased;In a survey carried out among workers from the Universidad de Ciencias y Humanidades, the desire to improve the organization of their work schedule is mentioned, for this reason it was decided to create a virtual assistant, taking into account that virtual assistants and smart devices are increasingly more involved in daily life, devices that can be controlled with the voice, to perform specific activities, in some field of application, the virtual assistant created will help in the organization and recall of events, during remote work, based on these requirements, was born YANA, a virtual assistant developed in Python, which through voice instructions, guides you to organize your work schedule in addition to reminding you of upcoming events, thus managing to provide support in the organization of the agenda, leaving aside the concern of forgetting something Important event;Together with the development of YANA, it was possible to create a user interface, which allows us to control YANA and interact with it, since it is also capable of answering various questions that are asked, as well as the ability to follow a conversation;In the evaluation system developed to evaluate YANA's interaction with users, an average of 7 out of 10 was obtained from a series of questions posed to users. © 2021 IEEE.
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In late 31 December 2019, a cluster of unexplained pneumonia cases was reported in Wuhan, China [1]. A few days later, the causative agent of this mysterious pneumonia was identified as the new COVID-19 virus. Currently, it has been spreading for more than one and a half years and has lost a huge number of lives all over the world. Most people faced this disaster because of their ignorance, carelessness and lack of updates. By the way most people are in lack of knowledge regarding COVID-19 pandemic, symptoms and what should do to survive from that. Those issues are great problems nowadays. 'CoviDefender' is set to offer a solution to this worldwide COVID-19 pandemic problem. This is a new technological solution from a mobile application. 'CoviDefender' is a Smart Assistant for Defending against COVID-19 Pandemic. This can be described as a solution to the ignorance and carelessness of the people who have been the main cause of the spread of this epidemic. © 2021 IEEE.
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Chatbots or virtual assistants are being used by industries all over the world, they can reduce human intervention and improve efficiency. These days smart-Assistants such as Amazon Alexa and Google Assistant help users get quick access to most generic queries within seconds, but when it comes to students and their everyday queries, these assistants fall short in answering the queries they have related to their academic schedules i.e., timetable queries, online classes links, syllabus queries, test dates, etc. The motive behind building this chatbot is to help students get quick and accurate responses to their schedule and syllabus-related queries, this is especially beneficial for students who are taking online classes due to the COVID-19 pandemic and cannot talk to their peers face to face. This chatbot was developed with the Rasa, it is a framework for developing contextual AI assistants and chatbots. Rasa enables the use of components in the NLU pipeline to customize the intent classification, entity extraction, and response selection. This paper goes through the pipeline customizations that were necessary to process the schedule-specific queries from students. It also goes over the stories and custom actions used to generate responses once the intent and entities are extracted. Telegram was used to deploy the chatbot onto the real world to enable students to talk to this chatbot from the comfort of their smartphones. © 2021 IEEE.
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In this paper we propose an intelligent chatbot that helps tackle the critical COVID-19 situation in India, which is a detrimental issue affecting the population of the country. Patients wait in long queues outside hospitals to obtain critical resources such as beds but return back in vain due to unavailability. The Covisstance Chatbot that we propose helps users locate available beds and ventilators in all hospitals at the user's location, without the need for them to travel. The proposed virtual assistant is implemented integrating several serverless services from Microsoft Power Virtual Agent, Power Automate flows to define actions, Microsoft Lists as a test database and Microsoft's Language Understanding Artificial Intelligence service (LUIS) that performs language and semantic analysis of user's queries. Experimental results show that the proposed chatbot successfully responds to all users' queries related to hospital information about beds and oxygen cylinders availability. © 2021 Association for Computing Machinery.
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This paper presents the design and development of an efficient and intelligent chatbot. The proposed idea is to create a health companion which can be used for a daily well-being. An agile approach was used for its development and deployed on a platform such that all types of users can communicate with it. This virtual assistant makes our life easier and saves time via automated user query replies. Responding to user queries regarding home remedies as well as the recent pandemic COVID-19, the bot is well-equipped and reliable. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Community-dwelling older adults have raised the scientific community's interest during the COVID-19 era as their chronic conditions might be aggravated by the consequences of confinement. Digital devices in this field to monitor cognitive impairment are an emerging reality of an innovative nature. However, some groups may not have benefited from these developments as much as, for example, younger people. The aim of this manuscript is to carry out a review on the development of digital devices, and specifically virtual assistants, for the detection of cognitive impairment in older adults. After a screening process, eight studies were found under the given criteria, and this number was even smaller for those using virtual assistants. Given the opportunities offered by virtual assistants through techniques such as natural language processing, it seems imperative to take advantage of this opportunity for groups such as older adults.