An indoor localization algorithm in a small-cell LED-based lighting system

2012 ◽  
Author(s):  
Anna Maria Vegni ◽  
Mauro Biagi
Keyword(s):  
Indoor Localization ◽  
Small Cell ◽  
Localization Algorithm ◽  
Lighting System

Indoor Localization Algorithm Research in Intelligent Lighting

2013 ◽  
Vol 765-767 ◽  
pp. 763-767
Author(s):  
Sien Lai ◽  
Ting Shu ◽  
Guang Hui Yang ◽  
Rui Lin Zhang
Keyword(s):  
Indoor Localization ◽  
Historical Data ◽  
Motion Path ◽  
Localization Algorithm ◽  
Lighting System ◽  
Movement Path ◽  
Path Design

Due to existing indoor intelligent lighting system lack of the movement path predictionand the boundary of the space detection,thispaperpresents an idea to predict the location and distinguish the boundary of the space based on the historical data of someone's motion path; Indoor positioningisappliedtointelligent lighting system, according to the existing indoor localization algorithm, combined with the historical data of motion path, design an suitable algorithm for indoor intelligent lighting system, which can predict location and distinguish the boundary of the space.

scholarly journals Indoor Localization Based on VIO System and Three-Dimensional Map Matching

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2790 ◽  
Author(s):  
Jitong Zhang ◽  
Mingrong Ren ◽  
Pu Wang ◽  
Juan Meng ◽  
Yuman Mu
Keyword(s):  
Random Field ◽  
Indoor Localization ◽  
Conditional Random Field ◽  
A Priori ◽  
Three Dimensional ◽  
Map Matching ◽  
Localization Algorithm ◽  
Position Information ◽  
Feedback Information ◽  
Poor Lighting

High-precision indoor localization plays a vital role in various places. In recent years, visual inertial odometry (VIO) system has achieved outstanding progress in the field of indoor localization. However, it is easily affected by poor lighting and featureless environments. For this problem, we propose an indoor localization algorithm based on VIO system and three-dimensional (3D) map matching. The 3D map matching is to add height matching on the basis of previous two-dimensional (2D) matching so that the algorithm has more universal applicability. Firstly, the conditional random field model is established. Secondly, an indoor three-dimensional digital map is used as a priori information. Thirdly, the pose and position information output by the VIO system are used as the observation information of the conditional random field (CRF). Finally, the optimal states sequence is obtained and employed as the feedback information to correct the trajectory of VIO system. Experimental results show that our algorithm can effectively improve the positioning accuracy of VIO system in the indoor area of poor lighting and featureless.

Single Beacon Indoor Localization System Based on Counter-Synchronized Compass and RSSI

2014 ◽  
Vol 627 ◽  
pp. 217-222
Author(s):  
Kok Seng Eu ◽  
Kian Meng Yap ◽  
Tiam Hee Tee
Keyword(s):  
Indoor Localization ◽  
Target Item ◽  
Optimal Solution ◽  
Research Area ◽  
Target Object ◽  
Localization Algorithm ◽  
Distance Information ◽  
Localization Method ◽  
Localization System ◽  
Lost And Found

Indoor localization system has been a popular research area in recent decades and many of them are based on multiple beacons localization method. However, there are some special applications to which the multiple beacons method is not an optimal solution due to its overdesign and cost of redundancy. Multiple beacons method uses at least three transducers and each transducer’s location must be known to find the location of a target object by using either Triangulation or Trilateration calculation. When the multiple beacons method is applied in an items lost and found system, the precise Cartesian coordinates of a target item can be found, but it is definitely overdesign and incurring redundant cost. It is due to the fact that the target item requires only two simple information i.e. Clock orientation and distance information; therefore, single beacon is enough for the task. In this paper, we propose a single beacon localization method to optimize the solution in the items lost and found system by utilizing clock orientation and estimated distance information. The proposed single beacon localization algorithm has been demonstrated and proven that it can be one of the optimal solutions for items lost and found system.

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