Smart collaborative system using the sensors of mobile devices for monitoring disabled and elderly people

Sendra, Sandra; Granell, Emilio; Lloret, Jaime; Rodrigues, Joel J. P. C.

doi:10.1109/icc.2012.6364935

Cited by 14 publications

(8 citation statements)

References 6 publications

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“…We will now detail some of the work that uses sensors integrated into the smartphone for patient monitoring [14][15][16]. A new intelligent collaborative system that uses smartphone sensors to monitor disabled and elderly people has been proposed by Sendra et al [17]. Wang and Lee [18] are developing a new concept of a blood glucose sensor for advanced control and monitoring of blood sugar in patients.…”

Section: Related Workmentioning

confidence: 99%

A Smart Glucose Monitoring System for Diabetic Patient

et al. 2020

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Diabetic patients need ongoing surveillance, but this involves high costs for the government and family. The combined use of information and communication technologies (ICTs), artificial intelligence and smart devices can reduce these costs, helping the diabetic patient. This paper presents an intelligent architecture for the surveillance of diabetic disease that will allow physicians to remotely monitor the health of their patients through sensors integrated into smartphones and smart portable devices. The proposed architecture includes an intelligent algorithm developed to intelligently detect whether a parameter has exceeded a threshold, which may or may not involve urgency. To verify the proper functioning of this system, we developed a small portable device capable of measuring the level of glucose in the blood for diabetics and body temperature. We designed a secure mechanism to establish a wireless connection with the smartphone.

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Section: Related Workmentioning

confidence: 99%

A Smart Glucose Monitoring System for Diabetic Patient

et al. 2020

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“…Therefore, our system considers the following statements:  Difference of sensor values with respect to the previous values. 9  Difference of the current state with the sensor values of the neighbors.  The combination of several alarms, to distinguish between a true emergency situation and a situation that has generated a false positive.…”

Section: System Operationmentioning

confidence: 99%

Smart Collaborative Mobile System for Taking Care of Disabled and Elderly People

et al. 2013

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Official statistics data show that in many countries the population is aging. In addition, there are several illnesses and disabilities that also affect a small sector of the population. In recent years, researchers and medical foundations are working in order to develop systems based on new technologies and enhance the quality of life of them. One of the cheapest ways is to take advantage of the features provided by the smartphones. Nowadays, the development of reduced size smartphones, but with high processing capacity, has increased dramatically. We can take profit of the sensors placed in smartphones in order to monitor disabled and elderly people. In this paper, we propose a smart collaborative system based on the sensors embedded in mobile devices, which permit us to monitor the status of a person based on what is happening in the environment, but comparing and taking decisions based on what is happening to its neighbors. The proposed protocol for the mobile ad hoc network and the smart system algorithm are described in detail. We provide some measurements showing the decisions taken for several common cases and we also show the performance of our proposal when there is a medium size group of disabled or elderly people. Our proposal can also be applied to take care of children in several situations.

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“…One of the inhibitors is the relative difficulty in personalization of such systems. Consider the following scenario: Various sensors have been developed for elderly people to assist them in having an independent life [2]. Examples of such sensors are: wearable sensors that measure vital signs and detect movements, such as falling down, visual sensors that monitor movement and behavior, vocal sensors that detect distress sounds, sensors attached to furniture and doors that detect locking status and physical behavior, and sensors attached to medication cases that detect medication consumption.…”

Section: Introductionmentioning

confidence: 99%

On the Personalization of Event-Based Systems

Etzion

Forunier

2014

Proceedings of the 1st ACM International Workshop on Human Centered Event Understanding From Multimedia

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In this paper we describe our position about personalization as a paradigm shift that is going to affect life in many areas. For Internet of Things applications, personalization is a critical success factor, especially in detecting situations in real-time. We discuss the need for personalization, and compare the Internet of Things to the traditional Internet to draw conclusions on the gaps. We also discuss "The Event Model" as a direction towards such personalization. Finally we present multi-disciplinary research challenges for enabling personalization for Internet of Things applications.

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Smart collaborative system using the sensors of mobile devices for monitoring disabled and elderly people

Cited by 14 publications

References 6 publications

A Smart Glucose Monitoring System for Diabetic Patient

A Smart Glucose Monitoring System for Diabetic Patient

Smart Collaborative Mobile System for Taking Care of Disabled and Elderly People

On the Personalization of Event-Based Systems

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