ZigBee-based Sensor Network for Indoor Location and Tracking Applications

Álvarez, Yuri; Las-Heras, Fernando

doi:10.1109/tla.2016.7587622

Cited by 40 publications

(19 citation statements)

References 20 publications

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“…Based on these data, the distance from the transmitter to the receiver can be estimated by converting the RSS data into the length between LEDs, or estimated locations can be inferred by combining RSS data and the fingerprinting method [2,14]. The RSS is a popular, simple approach that provides acceptable positioning error for indoor positioning applications [13]; This approach is also applied for other types of signals such as WIFI [15,16], Bluetooth [17,18], Lorawan [13], and Zigbee [19,20]. In the VLPS field, recent research based on the RSS platform have continued to improve [9,11,21].…”

Section: Introductionmentioning

confidence: 99%

High Precision Weighted Optimum K-Nearest Neighbors Algorithm for Indoor Visible Light Positioning Applications

Tran

2020

IEEE Access

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Enhancing the accuracy of indoor visible light positioning systems with simple, real-time, and stable methods is one of the interesting challenges in recent research. In this paper, a relatively minor mean positioning error of 8 mm and a 42-52% improvement in computational time could be achieved within a real space of 1.2 m x 1.2 m x 1.2 m by transcending the serious limitations of the traditional knearest neighbors (KNN) algorithm. These disadvantages (slow execution time, high error formation) are a result of finding the nearest neighbors from all the fingerprints, averaging the Euclidean distances, and the excessive passivity of the K value. To overcome the above limitations of KNN, we proposed a maximum received signal strength recognition (MRR) technique and weighted optimum KNN (WOKNN) algorithm, which is a combination of optimum KNN (OKNN) and weighted KNN (WKNN). While MRR was used to reduce the computational time, WOKNN was used to solve the remaining problems. Specifically, OKNN was used to automatically determine the best number of nearest neighbors for each position in the area under consideration, and WKNN helped improve the errors that come from the Euclidean distance averaging process. Based on positive experimental results and a meaningful comparison with various versions of KNN, we demonstrated that the improved conventional KNN algorithm can achieve very high positioning accuracy and is totally suitable for several specific 2-D indoor positioning applications.

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Section: Introductionmentioning

confidence: 99%

High Precision Weighted Optimum K-Nearest Neighbors Algorithm for Indoor Visible Light Positioning Applications

Tran

2020

IEEE Access

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“…The main drawback of GPS is that satellite signals become significantly weaker in indoor environments as buildings block the line of sight between the satellite and the receiver. Solutions for indoor settings have explored beacon-based approaches that use cameras [10,11], infrared sensors [12,13], radio frequency identification (RFID) tags [14,15], wireless communication devices [16,17], computer-aided design (CAD) maps [18], among others. The main challenge of the beacon approach is to install a dedicated network that efficiently covers the traveler's entire path.…”

Section: Introductionmentioning

confidence: 99%

An Outdoor Navigation System for Blind Pedestrians Using GPS and Tactile-Foot Feedback

et al. 2018

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This paper presents a novel, wearable navigation system for visually impaired and blind pedestrians that combines a global positioning system (GPS) for user outdoor localization and tactile-foot stimulation for information presentation. Real-time GPS data provided by a smartphone are processed by dedicated navigation software to determine the directions to a destination. Navigational directions are then encoded as vibrations and conveyed to the user via a tactile display that inserts into the shoe. The experimental results showed that users were capable of recognizing with high accuracy the tactile feedback provided to their feet. The preliminary tests conducted in outdoor locations involved two blind users who were guided along 380-420 m predetermined pathways, while sharing the space with other pedestrians and facing typical urban obstacles. The subjects successfully reached the target destinations. The results suggest that the proposed system enhances independent, safe navigation of blind pedestrians and show the potential of tactile-foot stimulation in assistive devices.

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“…At present, indoor positioning technology is roughly categorized into wireless and inertial positioning technology. Wireless positioning technologies include infrared [ 3 ], ultrasonic [ 4 ], Bluetooth [ 5 ], Wi-Fi [ 6 ], ZigBee [ 7 ], Radio Frequency Identification (RFID) [ 8 ], Ultra Wideband (UWB) [ 9 ], visual [ 10 ], and wireless network positioning technology [ 11 ]. These positioning technologies are affected by external factors such as non-line-of-sight factors and multipath factors [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

An Optimal Enhanced Kalman Filter for a ZUPT-Aided Pedestrian Positioning Coupling Model

Fan

Zhang

Sun

et al. 2018

Sensors

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Aimed at overcoming the problems of cumulative errors and low positioning accuracy in single Inertial Navigation Systems (INS), an Optimal Enhanced Kalman Filter (OEKF) is proposed in this paper to achieve accurate positioning of pedestrians within an enclosed environment. Firstly, the errors of the inertial sensors are analyzed, modeled, and reconstructed. Secondly, the cumulative errors in attitude and velocity are corrected using the attitude fusion filtering algorithm and Zero Velocity Update algorithm (ZUPT), respectively. Then, the OEKF algorithm is described in detail. Finally, a pedestrian indoor positioning experimental platform is established to verify the performance of the proposed positioning system. Experimental results show that the accuracy of the pedestrian indoor positioning system can reach 0.243 m, giving it a high practical value.

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ZigBee-based Sensor Network for Indoor Location and Tracking Applications

Cited by 40 publications

References 20 publications

High Precision Weighted Optimum K-Nearest Neighbors Algorithm for Indoor Visible Light Positioning Applications

High Precision Weighted Optimum K-Nearest Neighbors Algorithm for Indoor Visible Light Positioning Applications

An Outdoor Navigation System for Blind Pedestrians Using GPS and Tactile-Foot Feedback

An Optimal Enhanced Kalman Filter for a ZUPT-Aided Pedestrian Positioning Coupling Model

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