Tracking group housed sows with an ultra-wideband indoor positioning system: A feasibility study

2020 ◽  
Vol 200 ◽  
pp. 176-187
Author(s):  
Shaojie Zhuang ◽  
Jarissa Maselyne ◽  
Annelies Van Nuffel ◽  
Jürgen Vangeyte ◽  
Bart Sonck
2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Santosh Subedi ◽  
Jae-Young Pyun

Recent developments in the fields of smartphones and wireless communication technologies such as beacons, Wi-Fi, and ultra-wideband have made it possible to realize indoor positioning system (IPS) with a few meters of accuracy. In this paper, an improvement over traditional fingerprinting localization is proposed by combining it with weighted centroid localization (WCL). The proposed localization method reduces the total number of fingerprint reference points over the localization space, thus minimizing both the time required for reading radio frequency signals and the number of reference points needed during the fingerprinting learning process, which eventually makes the process less time-consuming. The proposed positioning has two major steps of operation. In the first step, we have realized fingerprinting that utilizes lightly populated reference points (RPs) and WCL individually. Using the location estimated at the first step, WCL is run again for the final location estimation. The proposed localization technique reduces the number of required fingerprint RPs by more than 40% compared to normal fingerprinting localization method with a similar localization estimation error.


2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Taner Arsan ◽  
Mohammed Muwafaq Noori Hameez

There are several methods which can be used to locate an object or people in an indoor location. Ultra-wideband (UWB) is a specifically promising indoor positioning technology because of its high accuracy, resistance to interference, and better penetration. This study aims to improve the accuracy of the UWB sensor-based indoor positioning system. To achieve that, the proposed system is trained by using the K-means algorithm with an additional average silhouette method. This helps us to define the optimal number of clusters to be used by the K-means algorithm based on the value of the silhouette coefficient. Fuzzy c-means and mean shift algorithms are added for comparison purposes. This paper also introduces the impact of the Kalman filter while using the measured UWB test points as an input for the Kalman filter in order to obtain a better estimation of the position. As a result, the average localization error is reduced by 43.26% (from 16.3442 cm to 9.2745 cm) when combining the K-means algorithm with the Kalman filter in which the Kalman-filtered UWB-measured test points are used as an input for the proposed system.


2018 ◽  
Vol 173 ◽  
pp. 01021
Author(s):  
Hanyu Liu ◽  
Yanhan Zeng ◽  
Ruguo Li ◽  
Huajie Huang

In this paper, a high-accuracy indoor positioning system based on the ultra-wideband (UWB) technique is proposed. The proposed system uses a simple ranging process to obtain the distance between the mobile node and the fixed base stations. Besides, an improved time of arrival (ToA) algorithm with Kalman filtering is proposed to improve the positioning accuracy. Measurements have been performed in the real indoor 13m*7.6m environment with many obstacles and the root-mean-square error (RMSE) is less than 0.3m. The proposed system offers a wide range of application in robotics, industrial automation, post-sorting system and so on.


Author(s):  
Phatham Loahavilai ◽  
Chayut Thanapirom ◽  
Patharakorn Rattanawan ◽  
Thawatchart Chulapakorn ◽  
Sirawit Yanwicharaporn ◽  
...  

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