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Biometric techniques, such as fingerprint verification, iris or face recognition, retina analysis and hand‐written signature verification, are increasingly becoming basic elements of authentication and identification systems. However, any human physiological or behavioural traits serving as biometric characteristics are personal data protected by privacy protection legislation. To address related issues, this paper examines these classes of biometrics according to data protection principles, purpose, proportionality and security, provided in international legislation. This analysis leads to the desired properties of biometric systems in the form of functional and non‐functional requirements, in order to support developers minimising the risk of being non‐compliant to privacy protection legislation, and to increase user acceptance.

Ubiquitous health-care monitoring systems can provide continuous surveillance to a person using various sensors, including wearables and implantable and fabric-woven sensors. By assessing the state of many physiological characteristics of the patient’s body, continuous monitoring can assist in preparing for the impending emergency. To address this issue, this study aims to propose a health-care system that integrates the treatment of the impending heart, stress and alcohol emergencies. For this purpose, this study uses readings from sensors used for electrocardiography, heart rate, respiration rate, blood alcohol content percentage and blood pressure of a patient’s body.

For heart status, stress level and alcohol detection, the parametric values obtained from these sensors are preprocessed and further divided into four, five and six phases, respectively. A final integrated emergency stage is derived from the stages that were interpreted to examine at a person’s state of emergency. A thorough analysis of the proposed model is carried out using four classification techniques, including decision trees, support vector machines, k nearest neighbors and ensemble classifiers. For all of the aforementioned detections, four metrics are used to evaluate performance: classification accuracy, precision, recall and fmeasure.

Eventually, results are validated against the existing health-care systems. The empirical results received reveal that the proposed model outperforms the existing health-care models in the context of metrics above for different detections taken into consideration.

This study proposes a health-care system capable of performing data processing using wearable sensors. It is of great importance for real-time systems. This study assures the originality of the proposed system.

Many information systems involve data about people. In order reliably to associate data with particular individuals, it is necessary that an effective and efficient identification scheme be established and maintained. There is remarkably little in the information technology literature concerning human identification. Seeks to overcome that deficiency by undertaking a survey of human identity and human identification. Discusses techniques including names, codes, knowledge‐based and token‐based identification, and biometrics. Identifies the key challenge to management as being to devise a scheme which is practicable and economic, and of sufficiently high integrity to address the risks the organization confronts in its dealings with people. Proposes that much greater use be made of schemes which are designed to afford people anonymity, or which enable them to use multiple identities or pseudonyms, while at the same time protecting the organization′s own interest. Describes multi‐purpose and inhabitant registration schemes, and notes the recurrence of proposals to implement and extend them. Identifies public policy issues. Of especial concern is the threat to personal privacy that the general‐purpose use of an inhabitant registrant scheme represents. Speculates that, where such schemes are pursued energetically, the reaction may be strong enough to threaten the social fabric.

User authentication is generally used to protect personal information such as phone numbers, photos and account information stored in a mobile device by limiting the user to a specific person, e.g. the owner of the device. Authentication methods with password, PIN, face recognition and fingerprint identification have been widely used; however, these methods have problems of difficulty in one-handed operation, vulnerability to shoulder hacking and illegal access using fingerprint with either super glue or facial portrait. From viewpoints of usability and safety, strong and uncomplicated method is required.

In this paper, a user authentication method is proposed based on grip gestures using pressure sensors mounted on the lateral and back sides of a mobile phone. Grip gesture is an operation of grasping a mobile phone, which is assumed to be done instead of conventional unlock procedure. Grip gesture can be performed with one hand. Moreover, it is hard to imitate grip gestures, as finger movements and grip force during a grip gesture are hardly seen by the others.

The feature values of grip force are experimentally investigated and the proposed method from viewpoint of error rate is evaluated. From the result, this method achieved 0.02 of equal error rate, which is equivalent to face recognition.

Many researches using pressure sensors to recognize grip pattern have been proposed thus far; however, the conventional works just recognize grip patterns and do not identify users, or need long pressure data to finish confident authentication. This proposed method authenticates users with a short grip gesture.

This paper aims to review the determinants that influence adoption of biometric technologies, with particular emphasis on both devices and hotel processes.

The overall objective was to identify the critical hotel processes and devices. This was achieved by a quantitative survey of 300 hotel customers which focused on the key dimensions of technology behaviour, holiday characteristics, hotel processes, biometric technologies and the “willingness” to adopt.

The findings show that 87.3 per cent of hotel customers may be “willing to use” biometric devices and that there is some correlation between the different processes as well as the different biometric technologies.

Conclusions and recommendations are made as to which specific hotel processes might benefit from biometrics and also how hoteliers might anticipate the rollout of biometric technologies.

This paper provides a first, empirical study into customer adoption of biometrics. It reveals opportunities for hotels to profit from emerging biometric technologies.

It has been six months from the time the first case was registered, and nations are still working on counter steering regulations. The proposed model in the paper encompasses a novel methodology to equip systems with artificial intelligence and computational audition techniques over voice recognition for detecting the symptoms. Regular and irregular speech/voice patterns are recognized using in-built tools and devices on a hand-held device. Phenomenal patterns can be contextually varied among normal and presence of asymptotic symptoms.

The lives of patients and healthy beings are seriously affected with various precautionary measures and social distancing. The spread of virus infection is mitigated with necessary actions by governments and nations. Resulting in increased death ratio, the novel coronavirus is certainly a serious pandemic which spreads with unhygienic practices and contact with air-borne droplets of infected patients. With minimal measures to detect the symptoms from the early onset and the rise of asymptotic outcomes, coronavirus becomes even difficult for detection and diagnosis.

A number of significant parameters are considered for the analysis, and they are dry cough, wet cough, sneezing, speech under a blocked nose or cold, sleeplessness, pain in chests, eating behaviours and other potential cases of the disease. Risk- and symptom-based measurements are imposed to deliver a symptom subsiding diagnosis plan. Monitoring and tracking down the symptoms inflicted areas, social distancing and its outcomes, treatments, planning and delivery of healthy food intake, immunity improvement measures are other areas of potential guidelines to mitigate the disease.

This paper also lists the challenges in actual scenarios for a solution to work satisfactorily. Emphasizing on the early detection of symptoms, this work highlights the importance of such a mechanism in the absence of medication or vaccine and demand for large-scale screening. A mobile and ubiquitous application is definitely a useful measure of alerting the officials to take necessary actions by eliminating the expensive modes of tests and medical investigations.

Introduction: Coronavirus-19 (COVID-19) global outbreak poses a danger to millions of people’s health and the uncertainty and financial prudence around the world. Without a doubt, the sickness will place a tremendous strain on healthcare systems, which existing or traditional-based treatments cannot adequately handle. Only intelligence derived from diverse data sources can provide the foundation for rigorous clinical and social responses that optimise the use of constrained healthcare resources, create tailored patient treatment plans, educate policy-makers, and accelerate clinical trials

Purpose: This chapter aims to incorporate innovative practices of artificial intelligence (AI) into local, national, and global healthcare systems that can save lives of people and as well helps in human capital management ways that may be deployed rapidly and effectively with minimal errors.

Methodology: AI technologies and tools play a crucial part in COVID-19 crisis response by assisting with the virus discovery, early detection, and the development of effective medications and therapies. In this chapter, significant issues related to COVID-19 and how they may be addressed by applying HRM practices with recent advances in AI. Also, through a literature review of the recent studies implemented in a similar context, an AI solution is proposed by formulating a conceptual model.

Findings: This chapter offers that the latest AI techniques can assist policy-makers in implementing modern human capital management practices to fight against COVID-19. The goal is to remotely monitor patients utilising gadgets that are embedded with state-of-the-art medical technology. To limit hospital visits, or at least cut them down to a minimum, on the one hand, the health clinic also wants to deliver reliable health information to the doctors before or during virtual consultations.

A detailed analysis on the characteristics of laminar flow over a bell‐shaped stenosis for a physiological pulsatile flow is presented in this study. In order to have a good understanding of the physiological pulsatile flow, a comparison of the numerical solutions to three types of pulsatile flows, including a physiological flow, an equivalent pulsatile flow and a pure sinusoidal flow, are made in this work. The comparison shows that the flow behavior cannot be properly estimated if the equivalent or simple pulsatile inlet flow is used in the study of flow fields through stenosed arteries instead of actual physiological one. Then the physiological pulsatile flow is further studied by considering the effect of constriction ratio of stenosis, Womersley number and Reynolds number on the flow behavior through stenosed arteries. The analysis shows that the variation of these flow parameters puts significant impacts on the pulsatile flow field for the physiological flow.

This paper presents a critical review of studies which map the urban environment using continuous physiological data collection. A conceptual model is consequently presented for mitigating urban stress at the city and the user level.

The study reviews relevant publications, examining the tools used for data collection and the methods used for data analysis and data fusion. The relationship between urban features and physiological responses is also examined.

The review showed that the continuous monitoring of physiological data in the urban environment can be used for location-aware stress detection and urban emotion mapping. The combination of physiological and contextual data helps researchers understand how the urban environment affects the human body. The review indicated a relationship between some urban features (green, land use, traffic, isovist parameters) and physiological responses, though more research is needed to solidify the existence of the identified links. The review also identified many theoretical, methodological and practical issues which hinder further research in this area.

While there is large potential in this field, there has been no review of studies which map continuously physiological data in the urban environment. This study covers this gap and introduces a novel conceptual model for mitigating urban stress.

Understanding how health status and physiological factors affect performance is a daunting task. This chapter will discuss physiological, behavioral, and psychological factors that influence or determine the capacity to fight, and will consider metrics that can be used to measure their status. The premise of this discussion is that there is a set of physiological and psychological factors that intimately affect performance and that the relative contribution of these variables is individually unique. These factors can be identified and assessed, and are amenable to modification. A fuller understanding of these variables can lead the effort to maintain and improve performance in the adverse and challenging environments of military operations.