Accurate Indoor Proximity Zone Detection Based on Time Window and Frequency with Bluetooth Low Energy

Kim, Dae-Yeob; Kim, Soo-Hyung; Choi, Daeseon; Jin, Seunghun

doi:10.1016/j.procs.2015.07.199

Cited by 28 publications

(10 citation statements)

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“…To obtain a more stable RSS, Kim [26] proposed an accurate indoor proximity zone detection technique based on the time window and frequency of the RSS. Ozer [27] improved the performance of BLE indoor positioning using the Kalman filter to make the RSS smoother.…”

Section: Related Workmentioning

confidence: 99%

A Robust Indoor Positioning Method based on Bluetooth Low Energy with Separate Channel Information

Huang

Liu

Sun

et al. 2019

Sensors

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Among the current indoor positioning technologies, Bluetooth low energy (BLE) has gained increasing attention. In particular, the traditional distance estimation derived from aggregate RSS and signal-attenuation models is generally unstable because of the complicated interference in indoor environments. To improve the adaptability and robustness of the BLE positioning system, we propose making full use of the three separate channels of BLE instead of their combination, which has generally been used before. In the first step, three signal-attenuation models are separately established for each BLE advertising channel in the offline phase, and a more stable distance in the online phase can be acquired by assembling measurements from all three channels with the distance decision strategy. Subsequently, a weighted trilateration method with uncertainties related to the distances derived in the first step is proposed to determine the user’s optimal position. The test results demonstrate that our proposed algorithm for determining the distance error achieves a value of less than 2.2 m at 90%, while for the positioning error, it achieves a value of less than 2.4 m at 90%. Compared with the traditional methods, the positioning error of our method is reduced by 33% to 38% for different smartphones and scenarios.

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Section: Related Workmentioning

confidence: 99%

A Robust Indoor Positioning Method based on Bluetooth Low Energy with Separate Channel Information

Huang

Liu

Sun

et al. 2019

Sensors

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“…As RSSI grows stronger between a sensor and a receiver, locality, motion, intention and proximity can be determined (Kim et al, 2015). Among the challenges of using proximity for Activity RPM is the use of RSSI.…”

Section: Figure 1: Proximity Ranges From Emitter To Approaching Receivermentioning

confidence: 99%

Developing a Sensor based Homecare System - The Role of Bluetooth Low-Energy in Activity Monitoring

Power

Jackson

Dunnett

2018

Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies

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• This is a conference paper. Home healthcare systems have become a focus of research due to the shifting care requirements of the elderly.Malnourishment, independence and activity are becoming vital metrics when monitoring in patient's illness. Monitoring devices described in research however express issues in the consistent remote capture of these metrics. This work presents the role of Bluetooth Low-Energy Beacons (BLE) in community based healthcare by examining how passive activity monitoring can assist patients coping with independence and disease management within their homes as an Indoor Proximity System (IPS). BLE sensors will be placed on the patient, in their home and on objects of interest (OOI) such as water bottles, kettles and microwaves. Research described in this paper will focus on accuracy of BLE beacons as an IPS for lifestyle monitoring and its application to intelligent healthcare. This is achieved by creating a model of patient care requirements structured using activities of daily living (ADL) which is evaluated using patient activity pattern recognition in captured sensor data. Pattern analysis uses the changing distance values between BLE sensors to determine movement, motion and location which contribute to the activity, sensor based care model. Results support efficacy when using BLE beacons as an IPS with patient activity patterns becoming observable through monitoring with a consistent ability to distinguish interactions in activity patterns captured. Future experiments will focus on analysing captured sensor metrics to determine care outcomes.

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“…Localization is necessary to provide a physical context to sensor readings for services such as intrusion detection, inventory and supply chain management. It is also a fundamental task for sensor network services such as geographic routing and coverage area management [1,2]. Over the last few decades, localization technologies have undergone significant progress and they now play a crucial role for many location-and context-aware services and applications such as navigation, robotics, patient monitoring and emergency response systems.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, the physical environment can have a great impact on the performance of a chosen localization algorithm. For example, while global positioning system (GPS) has been the primary localization approach for outdoor environments, indoor environments (and all other GPS-denied areas) face severe challenges such as the limited accuracy of techniques like cellular-based positioning [2] and radio propagation characteristics that can differ significantly from outdoor environments [3]. Therefore, as one of the most challenging topics in localization, indoor localization has attracted the attention of many researchers both in industry and academia.…”

Section: Introductionmentioning

confidence: 99%

“…Most such techniques rely on the received signal strength indicator (RSSI) as the main parameter to extract distance information with acceptable accuracy [7]. Infrared-based indoor localization [8], signal fingerprint-based localization [9] and image-based indoor localization [10] are examples of localization that do not rely on RSSI or other similar signal or link measurement for distance determination.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Radio Frequency-Based Indoor Localization in Ad-Hoc Networks

Golestanian¹,

Siva²,

Poellabauer³

2017

Ad Hoc Networks

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The increasing importance of location-aware computing and context-dependent information has led to a growing interest in low-cost indoor positioning with submeter accuracy. Localization algorithms can be classified into range-based and range-free techniques. Additionally, localization algorithms are heavily influenced by the technology and network architecture utilized. Availability, cost, reliability and accuracy of localization are the most important parameters when selecting a localization method. In this chapter, we introduce basic localization techniques, discuss how they are implemented with radio frequency devices and then characterize the localization techniques based on the network architecture, utilized technologies and application of localization. We then investigate and address localization in indoor environments where the absence of global positioning system (GPS) and the presence of unique radio propagation properties make this problem one of the most challenging topics of localization in wireless networks. In particular, we study and review the previous work for indoor localization based on radio frequency (RF) signaling (like Bluetooth-based localization) to illustrate localization challenges and how some of them can be overcome.

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Accurate Indoor Proximity Zone Detection Based on Time Window and Frequency with Bluetooth Low Energy

Cited by 28 publications

References 1 publication

A Robust Indoor Positioning Method based on Bluetooth Low Energy with Separate Channel Information

A Robust Indoor Positioning Method based on Bluetooth Low Energy with Separate Channel Information

Developing a Sensor based Homecare System - The Role of Bluetooth Low-Energy in Activity Monitoring

Radio Frequency-Based Indoor Localization in Ad-Hoc Networks

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