Congestion Aware WSN-IoT-Application Layer Protocols for Healthcare Services

In the healthcare industry, WSN-IoT networks can be used to gather patient data for statistical purposes. IoT-based application-level protocols do not take into account these facts while forwarding the data to the gateway or server, which may degrade the network performance if the data was collected from a patient with ordinary/critical health issues and the route was busy or congested. In this paper, we'll look at the performance of two application layer protocols (i.e. CoAP and MQTT) within the constraints of a scalable network by integrating a congestion-aware scheme with them

A survey of simulation techniques in commerce and defence

Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches

RH-RT: A Data Analytics Framework for Reducing Wait Time at Emergency Departments and Centres for Urgent Care

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordRight Hospital – Right Time (RH-RT) is the conceptualization of the use of descriptive, predictive and prescriptive analytics with real-time data from Accident & Emergency (A&E)/Emergency Departments (ED) and centers for urgent care; its objective is to derive maximum value from wait time data by using data analytics techniques, and making them available to both patients and healthcare organizations. The paper presents an architecture for the implementation of RH-RT that is specific to the authors’ current work on a digital platform (NHSquicker) that makes available live waiting time from multiple centers of urgent care (e.g., A&E/ED, Minor Injury Units) in Devon and Cornwall. The focus of the paper is on the development of a Hybrid Systems Model (HSM) comprising of healthcare business intelligence, forecasting techniques and computer simulation. The contribution of the work is the conceptual RH-RT framework and its implementation architecture that relies on near real-time data from NHSquicker.Torbay Medical Research FundEconomic and Social Research Council (ESRC)Torbay Medical Research FundAcademic Health Science Networ

Big Data Analytics and Its Applications in Supply Chain Management

In today’s competitive marketplace, development of information technology, rising customer expectations, economic globalization, and the other modern competitive priorities have forced organizations to change. Therefore, competition among enterprises is replaced by competition among enterprises and their supply chains. In current competitive environment, supply chain professionals are struggling in handling the huge data in order to reach integrated, efficient, effective, and agile supply chain. Hence, explosive growth in volume and different types of data throughout the supply chain has created the need to develop technologies that can intelligently and rapidly analyze large volume of data. Big data analytics capability (BDA) is one of the best techniques, which can help organizations to overcome their problem. BDA provides a tool for extracting valuable patterns and information in large volume of data. So, the main purpose of this book chapter is to explore the application of BDA in supply chain management (SCM)

The interaction of lean and building information modeling in construction

Lean construction and Building Information Modeling are quite different initiatives, but both are having profound impacts on the construction industry. A rigorous analysis of the myriad specific interactions between them indicates that a synergy exists which, if properly understood in theoretical terms, can be exploited to improve construction processes beyond the degree to which it might be improved by application of either of these paradigms independently. Using a matrix that juxtaposes BIM functionalities with prescriptive lean construction principles, fifty-six interactions have been identified, all but four of which represent constructive interaction. Although evidence for the majority of these has been found, the matrix is not considered complete, but rather a framework for research to explore the degree of validity of the interactions. Construction executives, managers, designers and developers of IT systems for construction can also benefit from the framework as an aid to recognizing the potential synergies when planning their lean and BIM adoption strategies

Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication

A Guide for selecting big data analytics tools in an organisation

Selection of appropriate big data analytics (BDA) tools (software) for business purposes is increasingly challenging, which sometimes lead to incompatibility with existing technologies. This becomes prohibitive in attempts to execute some functions or activities in an environment. The objective of this study was to propose a model, which can be used to guide the selection of BDA in an organization. The interpretivist approach was employed. Qualitative data was collected and analyzed using the hermeneutics approach. The analysis focused on examining and gaining better understanding of the strengths and weaknesses of the most common BDA tools. The technical and non-technical factors that influence the selection of BDA were identified. Based on which a solution is proposed in the form of a model. The model is intended to guide selection of most appropriate BDA tools in an organization. The model is intended to increase BDA usefulness towards improving organization’s competitiveness

Revolutionizing Healthcare through Health Monitoring Applications with Wearable Biomedical Devices

The Internet of Things (IoT) has revolutionized the connectivity and communication of tangible objects, and it serves as a versatile and cost-effective solution in the healthcare sector, particularly in regions with limited healthcare infrastructure. This research explores the application of sensors such as LM35, AD8232, and MAX30100 for the detection of vital health indicators, including body temperature, pulse rate, electrocardiogram (ECG), and oxygen saturation levels, with data transmission through IoT cloud, offering real-time parameter access via an Android application for non-invasive remote patient monitoring. The study aims to expand healthcare services to various settings, such as hospitals, commercial areas, educational institutions, workplaces, and residential neighborhoods. After the COVID-19 pandemic, IoT-enabled continuous monitoring of critical health metrics such as temperature and pulse rate has become increasingly crucial for early illness detection and efficient communication with healthcare providers. Our low-cost wearable device, which includes ECG monitoring, aims to bridge the accessibility gap for people with limited financial resources, with the primary goal of providing efficient healthcare solutions to underserved rural areas while also contributing valuable data to future medical research. Our proposed system is a low-cost, high-efficiency solution that outperforms existing systems in healthcare data collection and patient monitoring. It improves access to vital health data and shows economic benefits, indicating a significant advancement in healthcare technology

Policy needs and options for a common approach towards modelling and simulation of human physiology and diseases with a focus on the virtual physiological human.

Life is the result of an intricate systemic interaction between many processes occurring at radically different spatial and temporal scales. Every day, worldwide biomedical research and clinical practice produce a huge amount of information on such processes. However, this information being highly fragmented, its integration is largely left to the human actors who find this task increasingly and ever more demanding in a context where the information available continues to increase exponentially. Investments in the Virtual Physiological Human (VPH) research are largely motivated by the need for integration in healthcare. As all health information becomes digital, the complexity of health care will continue to evolve, translating into an ever increasing pressure which will result from a growing demand in parallel to limited budgets. Hence, the best way to achieve the dream of personalised, preventive, and participative medicine at sustainable costs will be through the integration of all available data, information and knowledge