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Hardware Block Diagram C) Software design Front End Design: HTML is a format that tells a computer how to display a web page. The documents themselves
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With the growing interest on wireless network architectures for hospital management services is a renewed demand for efficient and reliable data transfer between the doctor and the patient. Voice and data traffic carried over a variety of access technologies is collected via technology-specific access networks like, Digital Subscriber Line [DSL], P...
Citations
... Some of these systems are designed to measure electrocardiography (ECG) of patients which is later on transmitted to the Cloud database via Internet or other wireless mode of data communication. The recorded data is analyzed and monitored and appropriate actions are undertaken (Dierckx, Pellicori, Cleland, & Clark, 2015;Fanucci et al., 2012;Karthikeyan, Devi, & Valarmathi, 2015). ...
The integration of Cloud and IoT known as CloudIoT offers a novel approach for designing coherent and structured healthcare monitoring systems. With CloudIoT, diverse IoT based healthcare applications interconnect and exchange information with each other for dispensing efficient clinical healthcare solutions. As sensor based communication have seen an exponential growth in recent years, humongous amounts of data gets generated, which becomes difficult to handle with limited processing and storage available in these sensor nodes. To overcome this, Cloud and IoT amalgamation also known as CloudIoT provides an efficient solution for bridging communication between heterogeneous devices and handling ever increasing data demands in healthcare applications. CloudIoT framework permits seamless application deployment and service rendering using Cloud service based models. In this chapter, we review the available CloudIoT literature and present a holistic vision on the CloudIoT based healthcare integration components. The chapter also presents seamless applications dispensed by CloudIoT platform and contemplates discussion on factors driving CloudIoT Health integration. The chapter presents a conceptual architectural framework for healthcare monitoring system that considers a range of aspects including data collection, transmission, and processing including cloud storage. The chapter also discusses a use case scenario that identifies actors and data flows responsible for transforming sensor data into real-time transmission to cloud. Also, a brief discussion on design considerations for healthcare architecture will be provided. The work in this chapter also highlights security issues affecting IoT layered architecture including vulnerabilities inherent in the Cloud. These vulnerabilities could render healthcare services non functional and critical patient information can be abused by malevolent users. Also a brief discussion on some potential mitigation measures will be provided. The chapter also elaborates discussion on various CloudIoT platforms that aim at solving heterogeneity issue between the Cloud and Things. Finally, the chapter concludes by identifying some open research issues and challenges hampering CloudIoT based healthcare adoption.
... They proposed this scheme to address some technical issues regarding uplink bandwidth management. The work introduced in [31] proposed the implementation of monitoring and control systems in hospice environment through the use of wireless sensors and actuators modules and through the storage of the data in the cloud within a hospital. The authors of [31] proposed the integration of cloud networking with wiFi and ZigBee to realize a Wireless Hospital Digital Interface (WHDI). ...
... The work introduced in [31] proposed the implementation of monitoring and control systems in hospice environment through the use of wireless sensors and actuators modules and through the storage of the data in the cloud within a hospital. The authors of [31] proposed the integration of cloud networking with wiFi and ZigBee to realize a Wireless Hospital Digital Interface (WHDI). The authors of [32] improved cost and power consumption figures of the introduced access network by introducing a novel network architecture. ...
In this paper, the energy efficiency of edge computing platforms for IoT networks connected to a passive optical network (PON) is investigated. We have developed a mixed integer linear programming (MILP) optimization model, which optimizes the placement and number of the cloudlets and VMs and utilizes energy efficient routes with the objective of minimizing the total IoT network and processing power consumption. Our results indicate that concentrating the VMs placement at the PON optical line terminal (OLT) that interconnects several IoT networks can help in saving power consumption when the VMs process raw data at low traffic reduction percentages. On the other hand, VMs should be placed in lower layer relays at high traffic reduction ratios. Our results indicate that up to 19% of the total power can be saved while utilizing PONs and serving heterogeneous VMs. For real time implementation, a heuristic is developed based on the MILP model insights with very comparable MILP-heuristic power consumption values. We considered three scenarios that represent different levels of homogeneous and heterogeneous VM CPU demands. Good agreement was observed between the heuristic results (17% power saving) and the MILP which results in 19% power saving.
... For many years traditional exams were the standard way to measure blood pressure, heart beat and glucose level in a specialized healthcare center. Conventional health monitoring models are inconvenient and time-consuming for all involved [5]. These models will be inadequate to overcome challenges of healthcare services in increasing ageing society. ...
In recent decade significantly rise in chronic diseases and ageing population ratio in world, demand efficient Health monitoring system (HMS) for comfort of people. This approach is not only cost effective but also a feasible alternative to traditional healthcare. The aged peoples and patients having chronic diseases refrain visit to health institutions (hospitals and nursing homes etc.) as a result it reduces burden on health institutions. In this paper we proposed IoT-based, intelligent HMS which continuously monitors patient's health parameters like blood pressure, heart beat and ECG. Data from blood pressure sensor, heart rate sensor and ECG sensor automatically monitored by Arduino UNO and Pi-camera attached to raspberry pi for video. Arduino UNO sends sensor data to raspberry pi which fed data to server's database using Wi-Fi, finally server sent data to webpage, which updates every 2 minutes. Doctor access data anywhere using internet and give feedback accordingly using text.
... Health monitoring is playing an important role in maintaining health for individuals, in particular for the elderly or people with chronic diseases because it can reduce hospitalisation and increase the quality of life [6]. Traditional health monitoring models are time-consuming and inconvenient for all involved [7]. These models will be insufficient to meet the need of medical services in our ageing society. ...
In light of the rising need for elderly care, this paper introduces a comprehensive integrated system centered on ensuring the safety of solitary senior individuals, leveraging the capabilities of the Internet of Things (IoT), deep learning, and sensor technology. We explore both wearable and non-wearable sensors for continuous monitoring. Recognizing the challenges associated with wearable devices - such as battery constraints, user discomfort, and potential inaccuracies - we highlight the benefits of visual object-based fall detection using environmental sensors. These include visual cameras and depth sensors optimally placed within living spaces to bypass the limitations of wearable devices and elevate monitoring precision.
To address potential privacy concerns from ongoing video monitoring, we utilize advanced methods like human skeleton extraction and reversible visual data-hiding schemes. By camouflaging visual data, our proposed method ensures the content remains undetected by conventional means. This data-hiding scheme for videos and images encrypts media in a way that, to the general observer, it appears as random noise, yet it can be securely stored and transferred across platforms. Moreover, our encryption technique draws inspiration from water wave patterns and utilizes circular patterns derived from images, making the chance of brute force decryption nearly impossible. As a result, the system transforms human visuals into anonymous skeletal structures and encrypts visual data, safeguarding both privacy and data integrity.
In essence, our holistic system marries technological advancements with the principles of humane care, striving for a harmonious blend of comfort, precise monitoring, and rigorous privacy preservation.
The IoT patient health monitoring system powered
by solar panels is an innovative idea that uses the Internet of
Things (IoT) and renewable energy to electronically monitor
patient health. The system is comprised of various sensors that
are coupled to an ESP8266 microcontroller, which sends the
collected data to a central server (Thing Speak) via a Wi-Fi
module. The computer processes and analyses the data, and
healthcare practitioners can access the patient's health
information via an online dashboard or mobile app. The usage
of solar panels as a power source is unique to this project. The
system is ecologically benign and self-sufficient because it is not
connected to the mains. The system's solar panels make it ideal
for deployment in rural areas where power is in short supply. It
will help people become more aware of their health situation and
take proper action.
Keywords— Renewable, Thing Speak, Self-sufficient, Remote,
conscious, Solar-panel.
The healthcare industry has a growing record of using big data-related technologies such as data analytics, internet of things, and machine learning, especially in the clinical areas. However, healthcare institutions must also perform all of the administrative processes just as any other organization. Thus, like many other industries, healthcare has begun to apply these same technologies to improve their understanding of these internal operations and use them to make better decisions and run a more effective operation. This study takes a structured literature review approach to describe the current state of this literature and identify the major themes and priorities of both the research community and the healthcare industry as a whole. The contribution made by this study is to provide a comprehensive analysis of the state of the literature to use as a foundation for the future research opportunities noted in the paper.
The integration of cloud and IoT known as CloudIoT offers a novel approach for designing coherent and structured healthcare monitoring systems. With CloudIoT, diverse IoT-based healthcare applications interconnect and exchange information for dispensing efficient clinical healthcare solutions. As sensor-based communication has seen an exponential growth in recent years, humongous amounts of data gets generated, which becomes difficult to handle with limited processing and storage available in sensor nodes. To overcome this, cloud and IoT amalgamation known as CloudIoT provides an efficient solution for bridging communication between heterogeneous devices and handling increasing data demands in healthcare applications including seamless application deployment and service rendering. In this chapter, we review the available CloudIoT literature and present a holistic vision on CloudIoT-based healthcare integration components. The chapter presents seamless applications dispensed by CloudIoT platform and contemplates discussion on factors driving CloudIoT health integration. The chapter also presents a conceptual architectural framework for healthcare monitoring system that considers a range of aspects including data collection, transmission, and processing including cloud storage. The chapter also discusses a use case scenario including a brief discussion on design considerations for healthcare architecture. The chapter highlights security issues affecting IoT layered architecture including vulnerabilities inherent in the cloud which could render healthcare services nonfunctional and critical patient information can be abused by malevolent users. Also, a brief discussion on some potential mitigation measures will be provided. The chapter also elaborates discussion on various CloudIoT platforms available. Finally, the chapter concludes by identifying some open research issues and challenges hampering CloudIoT-based healthcare adoption.
Mobility has become a daily practice of physicians, so it is possible that they remain periods of time without contact with the teams that support them in the treatment of patients. Longer periods between communications can cause delays in performing procedures, drug prescribing, etc. Considering this scenario, this work has as objective the conception an approach, called I2VSM, exploring IoT features and integrating: (i) a platform for acquisition of vital signs, (ii) an environment for contextual processing, which through customizable rules builds the Situational Awareness of the patients; and (iii) a textual and graphic display interface for these signals. As a source of vital signs, the MIMIC-III database is being used, which has been widely accepted by the international community for this purpose. In turn, for the evaluation of I2VSM together with health professionals, we explored the Technology Acceptance Model (TAM), obtaining promising results.
