Sensor Networks and Data Management in Healthcare: Emerging Technologies and New Challenges

Pike, Matthew; Mustafa, Nasser; Towey, Dave; Brusic, Vladimir

doi:10.1109/compsac.2019.00123

Cited by 24 publications

(15 citation statements)

References 48 publications

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“…Nos serviços de saúde mais modernos, existe uma grande quantidade de dados oriundos dos sensores de dispositivos IoT que monitoram em tempo real as operações dos vários sistemas. É importante mencionar que os dados gerados pelas redes de sensores são diferentes daqueles gerados por registradores de dados, porque os sensores individuais geram dados cooperativamente e esses dados são frequentemente processados e filtrados na fonte [Matthew Pike e Brusic, 2019]. Pode-se citar, como exemplo de redes de sensores, aqueles incorporados em smartphones e smartwatches, health bands, casas inteligentes, sistemas de seguranças, veículos como carros, ônibus e aviões.…”

Section: Sensoriamento De Eventos Na Assistência Em Saúde E Bem-estarunclassified

“…O uso de redes de sensores para o monitoramento de pacientes e transferência de dados médicos já é uma realidade [Matthew Pike e Brusic, 2019]. As aplicações de redes de sensores na área da saúde são cada vez mais amplas, como no monitoramento de sinais vitais, na atenção a acidentes, como quedas de idosos em suas residências, e ainda em aplicações médicas específicas para acompanhamento de doenças.…”

Section: Introductionunclassified

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Aplicações em redes de sensores na área da saúde e gerenciamento de dados médicos: tecnologias em ascensão

Santos¹,

Firmino²,

Soto³

et al. 2020

Minicursos SBCAS 2020

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Sensor networks have become increasingly popular in healthcare due to the widespread use of cell phones and accessories capable of capturing medical data and the growth of remote patient monitoring initiatives. Medical data captured by sensors are sensitive and require the guarantee of authenticity, confidentiality, and privacy in the context of the Brazilian regulations, according to "Lei Geral de Proteção de Dados" (LGPD). Besides, the management and guarantee of medical data interoperability depend on the use of syntax and semantics following international standards. Therefore, the cloud computing and the Internet of Things are enabling tools for digital technologies to improve patient care. In this chapter, we present and discuss sensor networks' main concepts and the collection, processing, and protection of data from sensitive medical data. Resumo As redes de sensores têm se tornado cada vez mais populares na área de saúde devido à ampla disseminação dos celulares e acessórios aptos a captar dados médicos e ao crescimento de iniciativas de monitoramento remoto de pacientes. Dados médicos são considerados dados sensíveis e como tal requerem a garantia de autenticidade, confidencialidade e privacidade no contexto da Lei Geral de Proteção de Dados (LGPD). Paralelamente, a gerência e garantia de interoperabilidade de dados médicos dependem do uso de sintaxe e semânticas de acordo com padronizações internacionais. Assim, a utilização da computação em nuvem e a Internet das Coisas são facilitadores para o desenvolvimento de tecnologias digitais para melhorar o atendimento ao paciente. Considerando esse cenário, este capítulo apresenta e discute os principais conceitos relacionados às redes de sensores e à coleta, tratamento e proteção de dados de médicos sensíveis.

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Section: Sensoriamento De Eventos Na Assistência Em Saúde E Bem-estarunclassified

Section: Introductionunclassified

Aplicações em redes de sensores na área da saúde e gerenciamento de dados médicos: tecnologias em ascensão

Santos¹,

Firmino²,

Soto³

et al. 2020

Minicursos SBCAS 2020

View full text Add to dashboard Cite

show abstract

“…Big Data accumulation, fueled by sensor networks and IoT devices, produces bottlenecks. This creates a need for a) real-time pre-processing of Big Data to reduce them to a workable size; b) synchronization of multiple data streams, extraction of critical information, and context awareness; c) new algorithms for real-time responses; and d) management of knowledge and its real-time deployment [20].…”

Section: G Capabilitiesmentioning

confidence: 99%

“…Sensor networks are used in healthcare as emergency response applications, smart home applications, and continuous monitoring applications in telemedicine [21]. Although SE is essential for the development of software systems and software components of complex systems, the literature on SE applications for sensor networks applications in health and their applications is sparse [20]. This article defines the basics of SE requirements and issues in this field.…”

Section: G Capabilitiesmentioning

confidence: 99%

Sensor Networks and Personal Health Data Management: Software Engineering Challenges

Zhang

Pike

et al. 2020

Advances in Intelligent Systems and Computing

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The advances of 5G, sensors, and information technologies enabled proliferation of smart pervasive sensor networks. 5G mobile networks provide low-power, high-availability, high density, and high-throughput data capturing by sensor networks and continuous streaming of multiple measured variables. Rapid progress in sensors that can measure vital signs, advances in the management of medical knowledge, and improvement of algorithms for decision support, are fueling a technological disruption to health monitoring. The increase in size and complexity of wireless sensor networks and expansion into multiple areas of health monitoring creates challenges for system design and software engineering practices. In this paper, we highlight some of the key software engineering and data-processing issues, along with addressing emerging ethical issues of data management. The challenges associated with ensuring high dependability of sensor network systems can be addressed by metamorphic testing. The proposed conceptual solution combines data streaming, filtering, cross-calibration, use of medical knowledge for system operation and data interpretation, and IoT-based calibration using certified linked diagnostic devices. Integration of blockchain technologies and artificial intelligence offers a solution to the increasing needs for higher accuracy of measurements of vital signs, high-quality decision-making, and dependability, including key medical and ethical requirements of safety and security of the data.

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“…Over the last years, the Internet of Things has evolved from a high-level vision of always-connected devices to a real cyber-physical system class that appears in many application domains, from healthcare Pike et al (2019) over smart cities Zanella et al (2014) to smart farming and precision agriculture Kamilaris et al (2016). IoT has introduced radical changes in the way data are processed.…”

Section: Introductionmentioning

confidence: 99%

Data-sharing markets for integrating IoT data processing functionalities

Kasrin

Benabbas

Elmamooz

et al. 2021

CCF Trans. Pervasive Comp. Interact.

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The recent evolution of the Internet of Things into a cyber-physical reality has spawned various challenges from a data management perspective. In addition, IoT platform designers are faced with another set of questions. How can platforms be extended to smoothly integrate new data management functionalities? Currently, data processing related tasks are typically realized by manually developed code and functions which creates difficulties in maintenance and growth. Hence we need to explore other approaches to integration for IoT platforms. In this paper we cover both these aspects: (1) we explore several emerging data management challenges, and (2) we propose an IoT platform integration model that can combine disparate functionalities under one roof. For the first, we focus on the following challenges: sensor data quality, privacy in data streams, machine learning model management, and resource-aware data management. For the second, we propose an information-integration model for IoT platforms. The model revolves around the concept of a Data-Sharing Market where data management functionalities can share and exchange information about their data with other functionalities. In addition, data-sharing markets themselves can be combined into networks of markets where information flows from one market to another, which creates a web of information exchange about data resources. To motivate this work we present a use-case application in smart cities.

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Sensor Networks and Data Management in Healthcare: Emerging Technologies and New Challenges

Cited by 24 publications

References 48 publications

Aplicações em redes de sensores na área da saúde e gerenciamento de dados médicos: tecnologias em ascensão

Aplicações em redes de sensores na área da saúde e gerenciamento de dados médicos: tecnologias em ascensão

Sensor Networks and Personal Health Data Management: Software Engineering Challenges

Data-sharing markets for integrating IoT data processing functionalities

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