How Machine Learning Could Detect Anomalies on Thinger.io Platform?

Sánchez-Pi, Nayat; Martí, Luis; Bustamante, Alvaro Luis

doi:10.1007/978-3-319-94779-2_23

Cited by 1 publication

(1 citation statement)

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“…The main benefit of using this platform, aside that it is open source, is the possibility to obtain a bi-directional communication with the devices, in real-time, by using standard REST-API interfaces. This way, it is possible to develop any application, i.e., desktop, mobile, Web service, that interacts with devices by using a well-known and proven interface based on REST [62]. Meanwhile, the devices can use more efficient (in terms of bandwidth, or memory footprint) binary protocols to communicate with the cloud.…”

Section: Iot Platforms For E-health Applicationsmentioning

confidence: 99%

Medical Data Processing and Analysis for Remote Health and Activities Monitoring

Vitabile

Marks

Stojanović

et al. 2019

Lecture Notes in Computer Science

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Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human's health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for

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Section: Iot Platforms For E-health Applicationsmentioning

confidence: 99%