ABSTRACT
The modern era of advanced communications and electronic structures yields with steady steps the enhanced implementation of smart 'leadership in energy and environmental design' (LEED) buildings with artificial intelligence (AI) structures. These structures need development through various studied steps. In this paper, we propose a holistic design of these buildings ranging from the compatibility of people with these kinds of structures to the impact on their health (in times of pandemics such as Covid-19). Moreover, we propose a viable scheme of an AI environment (inside LEED buildings), which includes virtual empathetic companion and colleague versions. This scheme relies on a proposed algorithmic logic of iterations for the best possible machine learning. Specifically, we first describe the iterative architecture of the proposed AI entity consisting of 5 sectors. Then, we present the proposed machine learning pipeline (MLP) that comprises these 5 sectors. Afterward, we give the 7-stage empathetic essence that should reside inside the MLP. Finally, we exhibit a proposed experiment besides our case study under development. Then, after implementation, the acquired technological experience can lead to a more exquisite version of AI software robots that could be adaptable to several labor and safety protocols. © 2022 IEEE.
ABSTRACT
Currently, hospitals and health care sectors employ low-cost Internet of Things based remote health monitoring systems and labs in order to collect a subject's or patients' real-time data. Such a process can be helpful for the early detection of a healthy newborn life and of critical importance for the survival of these lives. In this article, a preliminary implementation of a system monitoring the fetus heart rate (FHR) has been designed and implemented as a mobile wearable measuring system with remote sensing. The proposed implementation turns out to be an efficient combination of simplicity and cost effectiveness and is accompanied with preliminary accurate measurements of the FHR. The proposed system uses a transceiver module and is capable of efficient data transmission to a remote server station using a IEEE 802.11 b/g/n based wireless network. The patients' data can further be monitored using a smart or satellite phone, or even any well-known internet browser connected to the specific network, thus complying with the health safety distance measures required due to various situations, including that of the COVID-19 pandemic.
ABSTRACT
Background: Currently, there is a vast number of electronic and mobile devices which serve for self-evaluation purposes. Specifically, wearable technology has been vastly developed in the last years in conjunction with the usage of mobile phones’ applications for the convenience of their users. In the context of the aforementioned, a proper segmentation of the bibliography could emerge the significance of monitoring for preventing unwanted situations in pregnant women’s life. Objective: The research study on pregnant women has emerged from the need of identifying through a new type of micro review (utilizing elements from SALSA and PRISMA), the most important works of self-evaluation in times of Covid-19. Especially, vast concerns are reported from pregnant women’s community to have the same quality of monitoring services and at the same time to be properly guarded against Covid-19. The key question is whether the pregnant can accomplish or not the same results through wearable or/and IoT technologies compared to those of frequent hospital visits. Design: The used databases, in conjunction with specific terms and rules, finally produced 18 viable publications for reviewing. Results: The technologies proved to be not only a key factor for the future of monitoring but even considerably affect in some situations the subject under test. Conclusions: This study focused on determining, amongst others, any impact of this technology on the behavior thus to categorize the various technologies into weighted categories. The results showed in some case considerable impact of these devices on the psychological aspect of the subjects. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.