Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings

Almadani, Basem; Orujov, Farid; Maskeliūnas, Rytis; Damaševičius, Robertas; Venčkauskas, Algimantas

doi:10.3390/s19092114

Cited by 71 publications

(50 citation statements)

References 76 publications

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“…In [27], a type-2 FL system was employed to determine the location of visually impaired persons based on the RSSI of the BLE wireless protocol in indoor circumstances. The mean localization error obtained using type-2 FL was about 0.43 m, with a navigation accuracy of 98.2%.…”

Section: Related Workmentioning

confidence: 99%

Neural Network-Based Alzheimer’s Patient Localization for Wireless Sensor Network in an Indoor Environment

et al. 2020

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The number of older adults with Alzheimer's disease is increasing every year. The associated memory problems cause many difficulties for Alzheimer's patients and their caretakers; patients may even become lost in familiar surroundings. In this paper, a proposed localization system based on a wireless sensor network (WSN) and backpropagation based artificial neural network (BP-ANN) was practically implemented to detect and determine the position of an Alzheimer's patient in an indoor environment. The proposed system consisted of four ZigBee-based XBee S2C anchor nodes and one mobile node carried by the Alzheimer's patient. The received signal strength indicator (RSSI) of the anchor nodes was collected by the mobile node using a laptop supported by X-CTU software. The obtained RSSI values were used as input for training, testing, and validation processes of the BP-ANN, while two-dimension (2D) locations (x and y) were used as the output of the ANN. The results showed that the obtained mean localization errors were 0.964 and 0.921m for validation and testing phases, respectively, after applying the ANN. Based on a comparison with state-ofthe-art technology, we deduced that the proposed ANN method outperformed other techniques in previous studies in terms of mean localization error.

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Section: Related Workmentioning

confidence: 99%

Neural Network-Based Alzheimer’s Patient Localization for Wireless Sensor Network in an Indoor Environment

et al. 2020

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“…• Novel methods and technologies for very precise indoor positioning of older people or impaired inhabitants using wireless local area networks (WLAN) [151], Bluetooth beacons [152], radio and ultrasound signals.…”

Section: Technological Potentialmentioning

confidence: 99%

A Review of Internet of Things Technologies for Ambient Assisted Living Environments

2019

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The internet of things (IoT) aims to extend the internet to real-world objects, connecting smart and sensing devices into a global network infrastructure by connecting physical and virtual objects. The IoT has the potential to increase the quality of life of inhabitants and users of intelligent ambient assisted living (AAL) environments. The paper overviews and discusses the IoT technologies and their foreseen impacts and challenges for the AAL domain. The results of this review are summarized as the IoT based gerontechnology acceptance model for the assisted living domain. The model focuses on the acceptance of new technologies by older people and underscores the need for the adoption of the IoT for the AAL domain.

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“…However, the system is specific to visually impaired persons. BLE beacons are also used for indoor localization via a fuzzy logic type-2 based fingerprinting algorithm [51]. It calculates the geometric distance between the beacon to a fingerprint point.…”

Section: Smartphone-based Indoor Navigationmentioning

confidence: 99%

A Generic Approach toward Indoor Navigation and Pathfinding with Robust Marker Tracking

2019

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Indoor navigation and localization has gained a key attention of the researchers in the recent decades. Various technologies such as WiFi, Bluetooth, Ultra Wideband (UWB), and Radio-frequency identification (RFID) have been used for indoor navigation and localization. However, most of these existing methods often fail in providing a reasonable solution to the key challenges such as implementation cost, accuracy and extendibility. In this paper, we proposed a low-cost, and extendable framework for indoor navigation. We used simple markers printed on the paper, and placed on ceilings of the building. These markers are detected by a smartphone’s camera, and the audio and visual information associated with these markers are used as a user guidance. The system finds shortest path between any two arbitrary nodes for user navigation. In addition, it is extendable having the capability to cover new sections by installing new nodes at any place in the building. The system can be used for guidance of the blind people, tourists and new visitors in an indoor environment. The evaluation results reveal that the proposed system can guide users toward their destination in an efficient and accurate manner.

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Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings

Cited by 71 publications

References 76 publications

Neural Network-Based Alzheimer’s Patient Localization for Wireless Sensor Network in an Indoor Environment

Neural Network-Based Alzheimer’s Patient Localization for Wireless Sensor Network in an Indoor Environment

A Review of Internet of Things Technologies for Ambient Assisted Living Environments

A Generic Approach toward Indoor Navigation and Pathfinding with Robust Marker Tracking

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