New Reconstructed Database for Cost Reduction in Indoor Fingerprinting Localization (original) (raw)
Related papers
RF-Based Location Using Interpolation Functions to Reduce Fingerprint Mapping
Sensors, 2015
Indoor RF-based localization using fingerprint mapping requires an initial training step, which represents a time consuming process. This location methodology needs a database conformed with RSSI (Radio Signal Strength Indicator) measures from the communication transceivers taken at specific locations within the localization area. But, the real world localization environment is dynamic and it is necessary to rebuild the fingerprint database when some environmental changes are made. This paper explores the use of different interpolation functions to complete the fingerprint mapping needed to achieve the sought accuracy, thereby reducing the effort in the training step. Also, different distributions of test maps and reference points have been evaluated, showing the validity of this proposal and necessary trade-offs. Results reported show that the same or similar localization accuracy can be achieved even when only 50% of the initial fingerprint reference points are taken.
Wireless Indoor Localization Using Fingerprinting Technique
Journal of Advanced Research in Dynamical and Control Systems, 2020
Indoor positioning has gained more interest as one of the upcoming applications due to its use in a variety of services. Multiple technologies such as Bluetooth, Wi-Fi, RFID. However, Wi-Fi based localization in indoor environment offers significant advantages utilizing installed wireless infrastructures and good performances with low cost. With this study, we aim to provide a compromise between accurate positioning and feasibility of the system for practical applications. For this purpose, we minimize the fluctuations of Wi-Fi received signal strength (RSS) by filtering and we combine two approaches to locate a mobile user. At first, we implemeted the traditional fingerprinting technique that uses a real time matching of pre-recorded received signal strength (RSS) from the location data of the user transmitted to nearby access points (AP). Secondly, we used distance-based trilateration technique which determines positions using three known access points. The combination of the two methods provides enhancement of accuracy and wide indoor locating coverage. Regardless the locating data number, experiment confirmed a significant and a consistent performance in term of execution time and accuracy.
Robust Fingerprint Construction Based on Multiple Path Loss Model (M-PLM) for Indoor Localization
Computers, materials & continua, 2023
A robust radio map is essential in implementing a fingerprint-based indoor positioning system (IPS). However, the offline site survey to manually construct the radio map is time-consuming and labour-intensive. Various interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site surveys. This paper presents a novel fingerprint interpolator using a multi-path loss model (M-PLM) to create the virtual fingerprints from the collected sample data based on different signal paths from different access points (APs). Based on the historical signal data, the poor signal paths are identified using their standard deviations. The proposed method reduces the positioning errors by smoothing out the wireless signal fluctuations and stabilizing the signals for those poor signal paths. By considering multipath signal propagations from different APs, the inherent noise from these signal paths can be alleviated. Firstly, locations of the signal data with standard deviations higher than the threshold are identified. The new fingerprints are then generated at these locations based on the proposed M-PLM interpolation function to replace the old fingerprints. The proposed technique interpolates virtual fingerprints based on good signal paths with more stable signals to improve the positioning performance. Experimental results show that the proposed scheme enhances the positioning accuracy by up to 44% compared to the conventional interpolation techniques such as the Inverse Distance Weighting, Kriging, and single Path Loss Model. As a result, we can overcome the site survey problems for IPS by building an accurate radio map with more reliable signals to improve indoor positioning performance.
Practical Fingerprinting Localization for Indoor Positioning System by Using Beacons
Journal of Sensors
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. ...
Indonesian Journal of Electrical Engineering and Computer Science
Wireless sensor network (WSN) can be used as a solution to find out the position of an object that cannot be reached by global positioning system (GPS), for example to find out the position of objects in a room known as Indoor Positioning. One method in indoor positioning that can be used is fingerprinting. Inside there are two main work phases, namely training and positioning. The training phase is the process of collecting received signal strength indication (RSSI) data levels from each sensor Node reference that will be used as a reference value for the positioning phase. The more sensor Nodes used, the longer the processing time needed in the training phase. This research focussed on the duration of the training phase, the implementation of which are used 4 sensor Nodes, namely Zigbee (IEEE 802.15.4 protocol) arranged according to mesh network topology, one as Node X (positioning target) and 3 as reference Nodes. There are two methods used in the training phase, namely fixed tar...
Int'l J. of Communications, Network and System Sciences, 2009
This paper proposes efficient techniques that allow the deploying of high precision location applications for indoor scenarios over Wireless Local Area Networks (WLAN). Firstly, we compare the use of radio frequency (RF) power levels and relative time delays based on ray-tracing as detection methods to estimate the localization of a set of mobile station using the fingerprint technique. Detection method play an important role in applications of high frequencies techniques for locations systems based on current and emerging standards such as Wi-Fi (802.11x) and Wi-Max (802.16x). The localization algorithm computes the Euclidean distance between the samples of signals received from each unknown position and each fingerprint stored in the database or radio-map obtained using the FASPRI simulation tool. Experimental results show that more precision can be obtained in the localization process by means of relative delay instead of RF power detection method. Secondly, the Euclidean distance has been compared with others similarity distance measures. Finally, an interpolation algorithm between the fingerprinting weighing based on the distances has been implemented in order to eliminate those fingerprints that do not contribute to the improvement in the accuracy. These techniques allow obtaining more precision in the localization of indoor mobile devices over WLAN networks.
The Novel Performance Evaluation Method of the Fingerprinting-Based Indoor Positioning
IEICE Transactions on Information and Systems, 2016
In this work, the novel fingerprinting evaluation parameter, which is called the punishment cost, is proposed. This parameter can be calculated from the designed matrix, the punishment matrix, and the confusion matrix. The punishment cost can describe how well the result of positioning is in the designated grid or not, by which the conventional parameter, the accuracy, cannot describe. The experiment is done with real measured data on weekdays and weekends. The results are considered in terms of accuracy and the punishment cost. Three well-known machine learning algorithms, i.e. Decision Tree, k-Nearest Neighbors, and Artificial Neural Network, are verified in fingerprinting positioning. In experimental environment, Decision Tree can perform well on the data from weekends whereas the performance is underrated on the data from weekdays. The k-Nearest Neighbors has proper punishment costs, even though it has lower accuracy than that of Artificial Neural Network, which has moderate accuracies but lower punishment costs. Therefore, other criteria should be considered in order to select the algorithm for indoor positioning. In addition, punishment cost can facilitate the conversion spot positioning to floor positioning without data modification.
Mobile Information Systems, 2016
Fingerprinting-based algorithms are popular in indoor location systems based on mobile devices. Comparing the RSSI (Received Signal Strength Indicator) from different radio wave transmitters, such as Wi-Fi access points, with prerecorded fingerprints from located points (using different artificial intelligence algorithms), fingerprinting-based systems can locate unknown points with a few meters resolution. However, training the system with already located fingerprints tends to be an expensive task both in time and in resources, especially if large areas are to be considered. Moreover, the decision algorithms tend to be of high memory and CPU consuming in such cases and so does the required time for obtaining the estimated location for a new fingerprint. In this paper, we study, propose, and validate a way to select the locations for the training fingerprints which reduces the amount of required points while improving the accuracy of the algorithms when locating points at room level ...
2018
The conventional way of finding the closest pair of points is the use of brute force method that simply computes the distances of all pair of points in the plane and finds the points with the minimum distance. An improved version of this method was the use of divide and conquer algorithm. However, the expedition for improving the computational cost of this problem continues to grow because of potential applications in location estimation and sequence matching. This paper attempted to develop and analyze a new method called closest coordinate scheme to determine the estimated position for indoor positioning system. The enhanced fingerprint localization technique was linked with the closest coordinate scheme to test its value in terms of accuracy and efficiency. Results showed that the closest coordinate scheme is efficient and accurate. Future endeavor may focus on the time and space complexities of closest coordinate scheme and find out similar applications.
Modified fingerprinting localization technique of indoor positioning system based on coordinates
Indonesian Journal of Electrical Engineering and Computer Science
The fingerprinting localization technique is the most commonly used localization technique of the indoor positioning system. It is used by several technologies for short and long range position estimation like wireless fidelity and radio frequency. There are several schemes used to estimate a location for the indoor environment but the drawbacks resulted in complexity issues. These drawbacks have negative effects on location estimation. In order to address these drawbacks, this work attempted to explore the fingerprinting localization technique for location estimation of the indoor environment that focuses on position estimation. Results showed that the simplicity of the design of position estimation without compromising the functionality of the operations was observed with 100% accuracy on position estimation.