A smart wireless sensor network for AAL

Andò, B.; Baglio, Salvatore; Malfa, Salvatore La; Trigona, Carlo

doi:10.1109/iwmn.2011.6088493

Cited by 35 publications

(8 citation statements)

References 7 publications

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“…The validation of the UEI tool has already been addressed in [23] and its ability to estimate the user position with an accuracy of the order of 1 cm has been largely discussed.…”

Section: Resultsmentioning

confidence: 99%

“…Due to the above features, the supervisor is updated with the user's position while the UEI generates candidate messages for the user, with an assigned priority, assuring an efficient and safe mobility task. Details on the above paradigms can be found in [22] [23].…”

Section: An Overview Of the System Developedmentioning

confidence: 99%

“…The assistive system discussed in [23] and detailed through this paper represents an improvement with respect to the architecture proposed in [22]. The proposed approach allows for distributed monitoring of the environmental status (in terms of hazards such as fires, gas leakage, smoke), the user's position and the user's inertial behavior (posture and dynamic).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Smart Multi-Sensor Approach to Monitoring Weak People in Indoor Environments

Andò¹,

Baglio²,

Pistorio³

2014

JST

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This paper deals with a novel system to assist weak people while exploring indoor environments. The proposed architecture is aimed to monitor the position and inertial behavior of users as well as environmental status (e.g. temperature, humidity, gases leakage, or smoke). The system is based on a Wireless Sensor Network and smart paradigms which extract relevant information from data collected through the multi-sensor architecture. The data collected are then processed to build awareness of User-Environment Interaction and User-Environment Contextualization. This knowledge is used to build information that is useful to the user for safe and efficient exploitation of the environment and to the supervisor for a suitable assessment and management of hazard situations. The paper mainly focuses on the multi-sensor system architecture and smart paradigms used to implement the User-Environment Contextualization feature.

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“…The validation of the UEI tool has already been addressed in [23] and its ability to estimate the user position with an accuracy of the order of 1 cm has been largely discussed.…”

Section: Resultsmentioning

confidence: 99%

Section: An Overview Of the System Developedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Smart Multi-Sensor Approach to Monitoring Weak People in Indoor Environments

Andò¹,

Baglio²,

Pistorio³

2014

JST

Self Cite

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“…The system confirmed the potential of usage for WSNs on the medical care field, however it lacks of portability. In the paper of "a smart wireless sensor network for AAL" [3] the author implemented a novel system to assist weak people in exploring indoor environment. The system extracts suitable information through the multi-sensor based on a WSN and smart paradigm.…”

Section: Related Workmentioning

confidence: 99%

An Extensible Healthcare Context Engine Based on Smart Phones

Guangbin¹,

Awan²,

Kim³

2014

LNSE

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Abstract-Population aging problem has become a severe challenge worldwide and will become even severer in the near future. Meanwhile the technology of smart phones and various sensors is developing by leaps and bounds in the last few years. In order to help people who have difficulty in living independently, especially the senior citizens and facilitate efficient use of these sensors, it is worthwhile to explore the possibility of making use of smart phones to manage these sensors and provide valuable information. In this paper, a context engine run on the Android platform is introduced. The context engine targets healthcare usage, collecting healthcare related information from three kinds of sensors: ambient sensors, wearable sensors, and embedded sensors, with the attention of providing real time reminders, sharing information to other applications and recording the user's daily life. Experiment result shows that average accuracy of reminders can reach 82% in user's daily life within the context engine. The results are expected to be improved with more sensors and more accurate sensors involved in the system. Compared to other similar work, this context engine focuses on the mobile platform that can cover most of user's time in daily time while maintaining portability.

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“…Existing solutions often rely on the fusion of information from multiple sensors. In particular, some of the most widely used sensor types are inertial navigation systems [2] and imaging systems, such as cameras or infrared sensors [3], ultrasonic ranging sensors [4], and radio-based positioning technologies.…”

Section: Introductionmentioning

confidence: 99%

Characterization of a Flexible UWB Sensor for Indoor Localization

Angelis

Dwivedi

Händel

2013

IEEE Trans. Instrum. Meas.

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This paper presents research to develop an ultrawideband ranging sensor for personnel indoor localization based on the measurement of the pulse round-trip time. An approach combining flexibility, a high measurement update rate, and asynchronous operation with digital processing capability has been employed in the design of the sensor. The principle of operation, the architecture of the realized sensor, and the experimental setup are described. Finally, the results of a ranging calibration and validation test are presented and discussed. In the validation procedure, a root-mean-square error of 29 cm and a maximum absolute error of 81 cm with an operational range of approximately 10 m were observed.

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A smart wireless sensor network for AAL

Cited by 35 publications

References 7 publications

A Smart Multi-Sensor Approach to Monitoring Weak People in Indoor Environments

A Smart Multi-Sensor Approach to Monitoring Weak People in Indoor Environments

An Extensible Healthcare Context Engine Based on Smart Phones

Characterization of a Flexible UWB Sensor for Indoor Localization

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