Healthcare Framework for Smarter Cities with bio-sensory data

Enler, Emirhan; Pentek, Istvan; Adamkó, Attila

doi:10.1109/coginfocom50765.2020.9237838

Cited by 7 publications

(4 citation statements)

References 9 publications

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“…Based on the ideas presented, we feel that the implementation of SOA and MSA depends on the capabilities and needs of organizations (e.g., performance, flexibility, availability, interoperability or other characteristics in return for known and unknown consequences) [33,63]. Therefore, within the eHealth context and based on the results obtained, we observe that MSA is capable of meeting the majority of needs in support of medical decision making and is adaptable to different types of clinical systems (e.g., EHR, IoHT or telemonitoring systems) and various infrastructure solutions (e.g., nursing homes, hospitals and public health management) [16,62,117]; however, this brings with it many challenges [51,74,94,99,105].…”

Section: Discussionmentioning

confidence: 80%

Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy eHealth Applications in Cloud Computing Environment

et al. 2021

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This article proposes a new framework for a Cloud-based eHealth platform concept focused on Cloud computing environments, since current and emerging approaches using digital clinical history increasingly demonstrate their potential in maintaining the quality of the benefits in medical care services, especially in computer-assisted clinical diagnosis within the field of infectious diseases and due to the worsening of chronic pathologies. Our objective is to evaluate and contrast the performance of the architectural patterns most commonly used for developing eHealth applications (i.e., service-oriented architecture (SOA) and microservices architecture (MSA)), using as reference the quantitative values obtained from the various performance tests and their ability to adapt to the required software attribute (i.e., versatile high-performance). Therefore, it was necessary to modify our platform to fit two architectural variants. As a follow-up to this activity, corresponding tests were performed that showed that the MSA variant functions better in terms of performance and response time compared to the SOA variant; however, it consumed significantly more bandwidth than SOA, and scalability in SOA is generally not possible or requires significant effort to be achieved. We conclude that the implementation of SOA and MSA depends on the nature and needs of organizations (e.g., performance or interoperability).

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Section: Discussionmentioning

confidence: 80%

Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy eHealth Applications in Cloud Computing Environment

et al. 2021

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“…It is for these reasons that we believe efficient transportation to be a critical element of a smart city. Finogeev et al (2020) Professional data collection and processing system infrastructure (measurement equipment, photoelectric radar complex, road surveillance cameras, etc.) can be used to track the elements of road transportation.…”

Section: Smart Transportationmentioning

confidence: 99%

“…In (Enler et al, 2020) we discover an extensible, maintainable Service-Oriented Architecture (SOA) (Fig. 3).…”

Section: Smart Healthcarementioning

confidence: 99%

Integrating Data Mining Methods Across all Domains of a Smart City

Dave¹,

Xu²,

Arneberg³

et al. 2022

Journal of Computer Science

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As modern cities continue to develop, smart devices are being used to improve citizens' lives. As these devices become more sophisticated, the amount of information that they collect increases. A Smart City is a city that uses a large amount of generated data to constantly improve the services offered to the people that live there. Data mining techniques can be used to sift through the data and mine out meaningful patterns. Our research project focused on seven different disciplines within a Smart City, surveying the current state of research in each category. Smart Transportation is focused on decreasing congestion, increasing efficiency in public transportation, and improving the safety of pedestrians. Smart Healthcare is focused on modern healthcare monitoring systems and ambulance dispatch services. Smart Energy is focused on decreasing energy consumption and promoting green energy through WiFi thermostat optimization and a smart electric grid. Smart City Utilities is focused on creating algorithms to improve waste collection techniques and air quality. Smart City Planning is focused on land use and the placement of green spaces. Smart Networks and Privacy is focused on secure networks. Lastly, the Smart IoT (Internet of Things) Application is focused on next-generation networks like 5G.

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“…Such fields have in common that they are built upon concepts and technologies such as ubiquitous computing, context awareness, embedded systems and human-centric computer interaction design [4,5]. These kind of solutions are typically employed in home environments, but may also be employed for other kinds of purposes, such as healthcare [6], cognitive robotics [7], education [8] and public safety [1]. However, a common problem of the aforementioned proposals is the absence of a common framework for deploying the solutions.…”

Section: Introductionmentioning

confidence: 99%

Cognitive Pervasive Service Composition Applied to Predatory Crime Deterrence

et al. 2021

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Pervasive service composition is useful in many scenarios, for instance, in urban planning or controlled harvest. Currently, there is no standard to develop solutions using pervasive service composition. However, big companies propose their frameworks to develop complex services, but their frameworks are appropriate in specific applications, such as home automation and agriculture. On the other hand, there are different very well-grounded academic proposals for pervasive service composition. However, these do not solve the problems of traditional approaches that are appropriate to specific areas of application, and adaptation is needed to deal with the dynamism of the environment. This article presents a cognitive approach for pervasive service composition where InfoCom devices and the implementation of cognitive functions interact to create pervasive composite services. Our central hypothesis is that cognitive theory can help solve actual problems requiring pervasive service composition, as it addresses the above-mentioned problems. To test our approach, in this article we present a case of urban insecurity. Specifically, in different countries, street robbery using firearms is one of the problems with a high impact because of its frequency. This article proposes to compose a pervasive service for deterring criminals from committing their crimes. The results obtained by simulating our proposal in our case study are promising. However, more research needs to be achieved before applying the proposed approach to actual problems. The research needed ought to address various problems, some of which are discussed in this article.

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Healthcare Framework for Smarter Cities with bio-sensory data

Cited by 7 publications

References 9 publications

Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy eHealth Applications in Cloud Computing Environment

Evaluating Service-Oriented and Microservice Architecture Patterns to Deploy eHealth Applications in Cloud Computing Environment

Integrating Data Mining Methods Across all Domains of a Smart City

Cognitive Pervasive Service Composition Applied to Predatory Crime Deterrence

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