Innovative technological solutions are required to improve patients' quality of life and deliver suitable treatment. Healthcare workers may be able to watch patients from a distance using the Internet of Things (IoT) by using big data algorithms to analyze instrument outputs. Therefore, it is essential to gather information on use and health problems in order to improve the remedies. To ensure seamless incorporation for use in healthcare institutions, senior communities, or private homes, these technological tools must first and foremost be easy to use and implement. We provide a network cluster-based system known as smart patient room usage in order to achieve this. As a result, nursing staff or caretakers can use it efficiently and swiftly. This work focuses on the exterior unit that makes up a network cluster, a cloud storage mechanism for data processing and storage, as well as a wireless or unique radio frequency send module for data transfer. In this article, a spatio-temporal cluster mapping system is presented and described. This system creates time series data using sense data collected from various clusters. The suggested method is the ideal tool to use in a variety of circumstances to improve medical and healthcare services. The suggested model's ability to anticipate moving behavior with high precision is its most important feature. The time series graphic displays a regular light movement that continued almost the entire night. The last 12 h' lowest and highest moving duration numbers were roughly 40% and 50%, respectively. When there is little movement, the model assumes a normal posture. Particularly, the moving duration ranges from 7% to 14%, with an average of 7.0%.
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http://dx.doi.org/10.3390/s23104614 | DOI Listing |
Rev Bras Epidemiol
January 2025
Universidade de São Paulo, Faculty of Public Health, Postgraduate Degree in Public Health - São Paulo (SP), Brasil.
Objective: To identify clusters of high and low risk for the occurrence of leptospirosis in space and space-time in Acre, between 2001 and 2022, as well as to characterize temporal trends and epidemiological profiles of the disease in the state.
Methods: An ecological study of cases mandatorily reported by health services in Brazil. For the analysis of clusters in space and space-time, the SaTScan software was used, which calculated the relative risks (RR).
BMC Infect Dis
January 2025
EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, nº 135, Porto, 4050 - 600, Portugal.
Background: The incidence of mosquito-borne infections has increased worldwide. Mainland Portugal's characteristics might favour the (re)emergence of mosquito-borne diseases. This study aimed to characterize the spatial distribution of vectors and notification rates of imported cases of mosquito-borne infections in mainland Portugal and demarcate the areas where these geographies overlap.
View Article and Find Full Text PDFSci Rep
January 2025
Laboratory of Veterinary Epidemiology, Graduate Program in Veterinary Medicine, Universidade Federal de Pelotas, University Campus, Building 42, Post Office Box 354, Capão do Leão, RS, CEP 96010-900, Brazil.
Dengue remains a significant public health concern in Brazil, with all federative units registering occurrences of the disease within their territories despite constant measures to control the Aedes aegypti vector. This study aimed to evaluate the profile of notified dengue cases in the Brazilian Legal Amazon from 2001 to 2021, analyzing National System of Notifiable Diseases (SINAN) data on the disease to assess the risks for its occurrence. Subsequently, statistical analyses were conducted to identify incidence and lethality rates.
View Article and Find Full Text PDFEnviron Pollut
January 2025
Department of Zoology, Faculty of Science, University of Peradeniya, Peradeniya 20400, Sri Lanka. Electronic address:
The microbial pollution status of river surface water is important to ensure a river-based quality drinking water supply for the public. The present study aimed to investigate bacterial contamination status in the upper Mahaweli River, the main drinking water supplier to the hill country of Sri Lanka. Both the raw surface water and treated water, taken at 14 drinking water treatment plants (DWTPs) along the river segment of 60 km between Kotmale and Victoria reservoirs, were tested for total bacterial counts (TBC), total coliform counts (TCC) and faecal coliform counts (FCC).
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