A Location Technique Based on Hybrid Data Fusion used to Increase the Indoor Location Accuracy

Simões, Walter Charles Sousa Seiffert; Silva, Yuri Motta Lopes Rodrigues; Lucena, Vicente Ferreira de

doi:10.1016/j.procs.2017.08.346

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…A set of tests was realized, and the location obtained was sufficient for the purpose of this work, considering the limits of a conventional house. The location-precision acquired was better than 2 m. These results, as well as a comparison with other related works, can be found in [77,78]. In fact, this location algorithm has already been applied to other applications developed in our research group, such as a teleoperation system of an electric wheelchair [79].…”

Section: System Implementationsupporting

confidence: 66%

Commercial Devices-Based System Designed to Improve the Treatment Adherence of Hypertensive Patients

Silva

Souza

Cruz

et al. 2019

Sensors

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This paper presents an intelligent system designed to increase the treatment adherence of hypertensive patients. The architecture was developed to allow communication among patients, physicians, and families to determine each patient’s medication intake and self-monitoring of blood pressure rates. Concerning the medication schedule, the system is designed to follow a predefined prescription, adapting itself to undesired events, such as mistakenly taking medication or forgetting to take medication on time. When covering the blood pressure measurement, it incorporates best medical practices, registering the actual values in recommended frequency and form, trying to avoid the known “white-coat effect.” We assume that taking medicine precisely and measuring blood pressure correctly may lead to good adherence to the treatment. The system uses commercial consumer electronic devices and can be replicated in any home equipped with a standard personal computer and Internet access. The resulting architecture has four layers. The first is responsible for adding electronic devices that typically exist in today’s homes to the system. The second is a preprocessing layer that filters the data generated from the patient’s behavior. The third is a reasoning layer that decides how to act based on the patient’s activities observed. Finally, the fourth layer creates messages that should drive the reactions of all involved actors. The reasoning layer takes into consideration the patient’s schedule and medication-taking activity data and uses implicit algorithms based on the J48, RepTree, and RandomTree decision tree models to infer the adherence. The algorithms were first adjusted using one academic machine learning and data mining tool. The system communicates with users through smartphones (anytime and anywhere) and smart TVs (in the patient’s home) by using the 3G/4G and WiFi infrastructure. It interacts automatically through social networks with doctors and relatives when changes or mistakes in medication intake and blood pressure mean values are detected. By associating the blood pressure data with the history of medication intake, our system can indicate the treatment adherence and help patients to achieve better treatment results. Comparisons with similar research were made, highlighting our findings.

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Section: System Implementationsupporting

confidence: 66%

Commercial Devices-Based System Designed to Improve the Treatment Adherence of Hypertensive Patients

Silva

Souza

Cruz

et al. 2019

Sensors

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“…Then again, heterogeneous hardware, phone orientation effect, energy footprint and scalability testing are some of the limitations of the study which also contribute to the robustness of the operation. In addition, the use of ZigBee to track the landmarks using the inertial navigation system (INS) and Kalman filter are also introduced by [13] which increases the accuracy of location estimation. Still, it is limited to the indoor manufacturing environment and the use of a complex algorithm for filtering of RSS may contribute a negative effect to the efficiency of the system.…”

Section: Introductionmentioning

confidence: 99%

Modified fingerprinting localization technique of indoor positioning system based on coordinates

Dellosa

Fajardo

Medina

2019

IJEECS

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<span>The fingerprinting localization technique is the most commonly used localization technique of the indoor positioning system. It is used by several technologies for short and long range position estimation like wireless fidelity and radio frequency. There are several schemes used to estimate a location for the indoor environment but the drawbacks resulted in complexity issues. These drawbacks have negative effects on location estimation. In order to address these drawbacks, this work attempted to explore the fingerprinting localization technique for location estimation of the indoor environment that focuses on position estimation. Results showed that the simplicity of the design of position estimation without compromising the functionality of the operations was observed with 100% accuracy on position estimation.</span>

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Using phase shift fingerprints and inertial measurements in support of precise localization in urban areas

Elbes

Alkhatib

Al-Fuqaha

et al. 2019

Pers Ubiquit Comput

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Localization is an important primitive that is utilized in a number of important applications such as location-based mobile services, augmented reality, and autonomous mobile robotics. While the GPS technology is considered the de facto standard for outdoor localization, it is known to suffer from significant accuracy limitation in urban areas. In this work, we present a particle filter-based data fusion technique for localization in urban areas. The proposed localization technique provides more accurate location estimation results due to its ability to efficiently fuse together information collected from diverse sensor technologies. The novelty of our proposed approach stems from its ability to fuse data from diverse sources, namely, phase shift fingerprints collected from Low Power AM Radio (LPAM) towers and inertial measurement sensors. Our simulation results indicate that the proposed approach can achieve an accuracy of 0.5 m using a limited number of LPAM towers as low as 5. Also, the proposed approach requires the collection of a low number of LPAM phase shift fingerprints. Our simulations indicate that 30 fingerprints are enough to provide 0.5 m accuracy in a 100 × 100 m 2 deployment. Keywords Smart cities • Localization in urban areas • Data fusion • Fingerprinting • Channel state information 1 Introduction In recent years, several critical national infrastructures (such as the electric grid, intelligent transportation, water systems) Mohammed Elbes

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A Location Technique Based on Hybrid Data Fusion used to Increase the Indoor Location Accuracy

Cited by 5 publications

References 8 publications

Commercial Devices-Based System Designed to Improve the Treatment Adherence of Hypertensive Patients

Commercial Devices-Based System Designed to Improve the Treatment Adherence of Hypertensive Patients

Modified fingerprinting localization technique of indoor positioning system based on coordinates

Using phase shift fingerprints and inertial measurements in support of precise localization in urban areas

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