scholarly journals Calibration of Beacons for Indoor Environments based on a Digital Map and Heuristic Information

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 670
Author(s):  
David Gualda ◽  
Jesús Ureña ◽  
José Alcalá ◽  
Carlos Santos

This paper proposes an algorithm for calibrating the position of beacons which are placed on the ceiling of an indoor environment. In this context, the term calibration is used to estimate the position coordinates of a beacon related to a known reference system in a map. The positions of a set of beacons are used for indoor positioning purposes. The operation of the beacons can be based on different technologies such as radiofrequency (RF), infrared (IR) or ultrasound (US), among others. In this case we are interested in the positions of several beacons that compose an Ultrasonic Local Positioning System (ULPS) placed on different strategic points of the building. The calibration proposal uses several distances from a beacon to the neighbor walls measured by a laser meter. These measured distances, the map of the building in a vector format and other heuristic data (such as the region in which the beacon is located, the approximate orientation of the distance measurements to the walls and the equations in the map coordinate system of the line defining these walls) are the inputs of the proposed algorithm. The output is the best estimation of the position of the beacon. The process is repeated for all the beacons. To find the best estimation of the position of the beacons we have implemented a numerical minimization based on the use of a Genetic Algorithm (GA) and a Harmony Search (HS) methods. The proposal has been validated with simulations and real experiments, obtaining the positions of the beacons and an estimation of the error associated that depends on which walls (and the angle of incidence of the laser) are selected to make the distance measurements.

Proceedings ◽  
2020 ◽  
Vol 39 (1) ◽  
pp. 18
Author(s):  
Nenchoo ◽  
Tantrairatn

This paper presents an estimation of 3D UAV position in real-time condition by using Intel RealSense Depth camera D435i with visual object detection technique as a local positioning system for indoor environment. Nowadays, global positioning system or GPS is able to specify UAV position for outdoor environment. However, for indoor environment GPS hasn’t a capability to determine UAV position. Therefore, Depth stereo camera D435i is proposed to observe on ground to specify UAV position for indoor environment instead of GPS. Using deep learning for object detection to identify target object with depth camera to specifies 2D position of target object. In addition, depth position is estimated by stereo camera and target size. For experiment, Parrot Bebop2 as a target object is detected by using YOLOv3 as a real-time object detection system. However, trained Fully Convolutional Neural Networks (FCNNs) model is considerably significant for object detection, thus the model has been trained for bebop2 only. To conclude, this proposed system is able to specifies 3D position of bebop2 for indoor environment. For future work, this research will be developed and apply for visualized navigation control of drone swarm.


2021 ◽  
Author(s):  
Luca Santoro ◽  
Davide Brunelli ◽  
daniele fontanelli ◽  
matteo nardello

Determining assets position with high accuracy and scalability is one of the most investigated technology on the market. The accuracy provided by satellites-based positioning systems (i.e., GLONASS or Galileo) is not always sufficient when a decimeter-level accuracy is required or when there is the need of localising entities that operate inside indoor environments. Scalability is also a recurrent problem when dealing with indoor positioning systems. This paper presents an innovative UWB Indoor GPS-Like local positioning system able to tracks any number of assets without decreasing measurements update rate. To increase the system’s accuracy the mathematical model and the sources of uncertainties are investigated. Results highlight how the proposed implementation provides positioning information with an absolute maximum error below 20 cm. Scalability is also resolved thanks to DTDoA transmission mechanisms not requiring an active role from the asset to be tracked.


Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4420 ◽  
Author(s):  
Lu Huang ◽  
Xingli Gan ◽  
Baoguo Yu ◽  
Heng Zhang ◽  
Shuang Li ◽  
...  

Since the signals of the global navigation satellite system (GNSS) are blocked by buildings, accurate positioning cannot be achieved in an indoor environment. Pseudolite can simulate similar outdoor satellite signals and can be used as a stable and reliable positioning signal source in indoor environments. Therefore, it has been proposed as a good substitute and has become a research hotspot in the field of indoor positioning. There are still some problems in the pseudolite positioning field, such as: Integer ambiguity of carrier phase, initial position determination, and low signal coverage. To avoid the limitation of these factors, an indoor positioning system based on fingerprint database matching of homologous array pseudolite is proposed in this paper, which can achieve higher positioning accuracy. The realization of this positioning system mainly includes the offline phase and the online phase. In the offline phase, the carrier phase data in the indoor environment is first collected, and a fingerprint database is established. Then a variational auto-encoding (VAE) network with location information is used to learn the probability distribution characteristics of the carrier phase difference of pseudolite in the latent space to realize feature clustering. Finally, the deep neural network is constructed by using the hidden features learned to further study the mapping relationship between different carrier phases of pseudolite and different indoor locations. In the online phase, the trained model and real-time carrier phases of pseudolite are used to predict the location of the positioning terminal. In this paper, by a large number of experiments, the performance of the pseudolite positioning system is evaluated under dynamic and static conditions. The effectiveness of the algorithm is evaluated by the comparison experiments, the experimental results show that the average positioning accuracy of the positioning system in a real indoor scene is 0.39 m, and the 95% positioning error is less than 0.85 m, which outperforms the traditional fingerprint positioning algorithms.


2021 ◽  
Author(s):  
Luca Santoro ◽  
Davide Brunelli ◽  
daniele fontanelli ◽  
matteo nardello

Determining assets position with high accuracy and scalability is one of the most investigated technology on the market. The accuracy provided by satellites-based positioning systems (i.e., GLONASS or Galileo) is not always sufficient when a decimeter-level accuracy is required or when there is the need of localising entities that operate inside indoor environments. Scalability is also a recurrent problem when dealing with indoor positioning systems. This paper presents an innovative UWB Indoor GPS-Like local positioning system able to tracks any number of assets without decreasing measurements update rate. To increase the system’s accuracy the mathematical model and the sources of uncertainties are investigated. Results highlight how the proposed implementation provides positioning information with an absolute maximum error below 20 cm. Scalability is also resolved thanks to DTDoA transmission mechanisms not requiring an active role from the asset to be tracked.


2018 ◽  
Vol 7 (3.25) ◽  
pp. 1 ◽  
Author(s):  
Hameedah Sahib Hasan ◽  
Mohamed Hussein ◽  
Shaharil Mad Saad ◽  
Mohd Azuwan Mat Dzahir

Positioning system like global position system (GPS) and Local position system (LPS) have become very important in a large number of applications such as monitoring and tracking, etc. Because of the limitations of GPS in indoor environments due to the lack of line of sight (LoS), the use of LPS has become a true necessary to estimate user’s or object position with a good accuracy. In order to choose the best LPS system, a compromise between accuracy, precision, power consumption, coverage and cost should be taken into account. This paper introduces an overview of LPS performance parameters, current technologies, techniques and methods used by LPS. On the other hand, the comparison between LPS technologies and techniques used based on those technologies are also discussed. Furthermore, the LPS’s applications that have been done by previous researches such as human tracking, object tracking, animal tracking and automatic guide vehicle (AGV) tracking will be discussed. We believe this paper would catalyze further investigation by the researcher which is interested on the LPS field. 


Author(s):  
Laurentiu Predescu ◽  
Daniel Dunea

Optical monitors have proven their versatility into the studies of air quality in the workplace and indoor environments. The current study aimed to perform a screening of the indoor environment regarding the presence of various fractions of particulate matter (PM) and the specific thermal microclimate in a classroom occupied with students in March 2019 (before COVID-19 pandemic) and in March 2021 (during pandemic) at Valahia University Campus, Targoviste, Romania. The objectives were to assess the potential exposure of students and academic personnel to PM and to observe the performances of various sensors and monitors (particle counter, PM monitors, and indoor microclimate sensors). PM1 ranged between 29 and 41 μg m−3 and PM10 ranged between 30 and 42 μg m−3. It was observed that the particles belonged mostly to fine and submicrometric fractions in acceptable thermal environments according to the PPD and PMV indices. The particle counter recorded preponderantly 0.3, 0.5, and 1.0 micron categories. The average acute dose rate was estimated as 6.58 × 10−4 mg/kg-day (CV = 14.3%) for the 20–40 years range. Wearing masks may influence the indoor microclimate and PM levels but additional experiments should be performed at a finer scale.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2896
Author(s):  
Pratham Singh ◽  
Michael Esposito ◽  
Zach Barrons ◽  
Christian A. Clermont ◽  
John Wannop ◽  
...  

One possible modality to profile gait speed and stride length includes using wearable technologies. Wearable technology using global positioning system (GPS) receivers may not be a feasible means to measure gait speed. An alternative may include a local positioning system (LPS). Considering that LPS wearables are not good at determining gait events such as heel strikes, applying sensor fusion with an inertial measurement unit (IMU) may be beneficial. Speed and stride length determined from an ultrawide bandwidth LPS equipped with an IMU were compared to video motion capture (i.e., the “gold standard”) as the criterion standard. Ninety participants performed trials at three self-selected walk, run and sprint speeds. After processing location, speed and acceleration data from the measurement systems, speed between the last five meters and stride length in the last stride of the trial were analyzed. Small biases and strong positive intraclass correlations (0.9–1.0) between the LPS and “the gold standard” were found. The significance of the study is that the LPS can be a valid method to determine speed and stride length. Variability of speed and stride length can be reduced when exploring data processing methods that can better extract speed and stride length measurements.


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