An indoor localization solution using Bluetooth RSSI and multiple sensors on a smartphone

Lee, Keonsoo; Nam, Yunyoung; Min, Se Dong

doi:10.1007/s11042-017-4908-2

Cited by 23 publications

(14 citation statements)

References 13 publications

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“…The Rfduino microcontroller used for the prototype development enables programmers to configure the Tx power, which is directly coupled with the power utilized for BLE [14]. RSSI expressed in dBm is used to measure the strength and reception of BLE signals on the smartphone [15]. A simple experiment is conducted by hand-carrying the smartphone and moving away from the instructor glasses for different Tx powerlevel settings.…”

Section: Resultsmentioning

confidence: 99%

“…A simple experiment is conducted by hand-carrying the smartphone and moving away from the instructor glasses for different Tx powerlevel settings. The RSSI value for different distances and Tx power levels are recorded to avoid data packet losses, which requires preventing RSSI value from falling below -80dBm, [15]. For various Tx power levels, Figure 8 provides plots of distance versus RSSI value.…”

Section: Resultsmentioning

confidence: 99%

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Wearable Smart Glasses for Assessment of Eye-Contact Behavior in Children With Autism

RajKumar¹,

Arora²,

Katz³

et al. 2019

2019 Design of Medical Devices Conference

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To promote eye contact learning and behavior in children with autism, there exist specialized environments as well as smartphone applications. However, few currently available techniques support the assessment of desired behavioral improvement during learning. In this paper, we describe recently developed wearable smart glasses instrumented with mechatronic sensors and controllers. The mechatronics glasses, worn by both an instructor and a child, quantitatively measure the eye contact behavior of the child. The instructor glasses connect with a smartphone application through Bluetooth low energy. A user interface is created and hosted on the smartphone to enable the instructor to customize the reward to the child based on improvements in eye contact behavior. Specifically, the smartphone application quantifies the eye contact duration, frequency, latency, and session time, allowing instructors, therapists, and clinicians to monitor and track the child’s progress in eye contact behavior. The results from preliminary user testing of the device with control subjects show that the device is capable of recording sessions details and supporting eye contact behavior assessment.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Wearable Smart Glasses for Assessment of Eye-Contact Behavior in Children With Autism

RajKumar¹,

Arora²,

Katz³

et al. 2019

2019 Design of Medical Devices Conference

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“…where in indicates the number of nodes in the input layer, out shows the number of nodes in the output layer, hide is the number of nodes in the hidden layer, and α is a constant in the range [1,10].…”

Section: Hidden Layermentioning

confidence: 99%

“…Nowadays, there are many ways to achieve an indoor location, such as Bluetooth, radio frequency identification (RFID), and Wi-Fi. As an example of Bluetooth-based indoor location technologies, Lee et al [1] used a Bluetooth receiver, an accelerometer, a magnetic field sensor, and a barometer on a smartphone to propose an indoor localization solution. Xinlong Jiang et al [2] used Wi-Fi signal and Bluetooth low energy signal into a unified model to introduce a fusion semisupervised extreme learning machine.…”

Section: Introductionmentioning

confidence: 99%

A method for indoor Wi-Fi location based on improved back propagation neural network

Chen¹,

Dong²,

He³

et al. 2019

Turk J Elec Eng & Comp Sci

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In order to achieve high precision on indoor location, a Wi-Fi indoor location method based on improved back propagation (BP) neural network is proposed. The classical BP neural network is optimized in real time by the ant colony optimization algorithm. Meanwhile, the momentum term is introduced to construct an improved four-layer BP neural network model. The model uses the Wi-Fi signal feature as the input of the BP neural network and succeeds in the area classification under multiple Wi-Fi signal features. The experimental results demonstrate that the improved BP neural network can increase the classification accuracy of the classifier effectively, and achieve a high-precision indoor area location. Furthermore, it performs better practical results while ensuring the time complexity. The advantages of this method are high practicability, low cost, high prediction classification accuracy, and robust stability, which can achieve the efficient classification of the short-range area.

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“…The options for indoor positioning are quite varied. RFID badges (Ortakci et al, 2015), cameras (Sun et al, 2016) or even Bluetooth (Lee et al, 2017) can all provide positioning information. However, these sensors either do not work when there is smoke or require people to wear something, making them prone to failure when their information is most required and possibly privacy sensitive.…”

Section: Introductionmentioning

confidence: 99%

An Ultrasonic Sensor for Human Presence Detection to Assist Rescue Work in Large Buildings

Groeningen

Driessen

Söhl

et al. 2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> When the fire brigade arrives at a burning building, it is of vital importance that people who are still inside can quickly be found. Smart buildings should be able to expose this location data to the fire brigade working in a smart city. In this paper the feasibility is researched of using ultrasonic sound sensors for human presence detection in smoke-filled spaces. This type of sensor could assist the fire brigade when evacuating a large building by directing them to the places where their help is most needed. The advantage of ultrasonic sound over other sensors or cameras is that its signal is able to pierce through smoke, does not require badges or other wearable devices and introduces little privacy and security risks. In addition, ultrasonic sensors are very inexpensive making it possible to equip every room of a building with an ultrasonic presence detector. In this research both a preliminary ultrasound measuring device and signal processing algorithm have been designed. Testing results show that the walking movement of a person in an indoor area can be detected with the combination of the sensor and the algorithms. In addition, tests of the signal strength in smoke have shown that ultrasound is capable of “looking through” the smoke. The algorithm based on a particle filter allows for more information to be extracted from the relatively simple sensor signal by detecting human walking movement specifically and opens up the way for an ultrasound based indoor positioning system that can be used in emergency situations.</p>

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An indoor localization solution using Bluetooth RSSI and multiple sensors on a smartphone

Cited by 23 publications

References 13 publications

Wearable Smart Glasses for Assessment of Eye-Contact Behavior in Children With Autism

Wearable Smart Glasses for Assessment of Eye-Contact Behavior in Children With Autism

A method for indoor Wi-Fi location based on improved back propagation neural network

An Ultrasonic Sensor for Human Presence Detection to Assist Rescue Work in Large Buildings

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