# BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning
## 4 Usage Examples
### Positioning Accuracy  
BLE RSS-based positioning methods are commonly affected by factors like the environment, beacon configuration, beacon deployment, and the receiving smartphone. Some of the methods found in literature address one or several of those factors [43]. To explore those factors in this work, two simple methods were tested: the weighted centroid method (applicable and used in BLE-based positioning because the beacon deployment positions are known) and the k-Nearest Neighbors (kNN) method commonly used in fingerprinting for indoor positioning. The weighted centroid method, hereinafter WC, has been used in several studies of BLE-based positioning, although with other names [11; 44]. The WC method estimates a 2D position for a BLE (operational) fingerprint by averaging the positions of the \(1\leq k\leq n\) beacons detected with the highest RSS values in the fingerprint, being \(n\) the number of beacons deployed in the target area. The kNN method [45], hereinafter FP, has been widely used in RSS-based indoor positioning. It assumes the existence of a previously collected database of labeled training fingerprints. The method finds the \(k\) fingerprints in the training database that are the closest ones to the (operational) fingerprint. The 2D position estimation is then computed as the centroid of the position labels of the selected \(k\) fingerprints. Given that the data in database described in this paper was not collected separately for training and estimation purposes, the scrips shipped with the data provides several suggestions for training-test data partitioning. It is advised to follow those suggestions, because the common way of selecting a percentage of the total data may not be practical given that every collection point has several (even 13) fingerprints that are similar between them. The accuracy of a RSS-based positioning method is computed in terms of the positioning error, i.e., the difference between the estimated position and the actual position where a fingerprint was taken. In this work, that difference is the 2D Euclidean distance. The accuracy metric mainly used for this work is the 75 percentile of the positioning error, which has been adopted as a comparison metric \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Zone** & \(\rho\) & \(p\)**-Value** & **Beacon** \\ \hline Geotec & \(-0.14\) & \(0.04\) & \(2\) \\ Library & \(-0.14\) & \(0.12\) & \(18\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Pearson correlation test between detection delays and distance to a beacon. Values correspond to the beacon reporting the \(\rho\) value farthest from zero, considering data captured by the A5 smartphone and a \(-12\) dBm beacon power setting). Figure 6: Times elapsed between two consecutive beacon detections while active registration of BLE advertisements. Measurements correspond beacon 1 broadcasting at \(-12\) dBm in the Library zone. In (**a**), thet \(\times 200\) ms (\(t\geq 1\)) detection delay pattern is shown. In (**b**), a comparison of detection capability among the three smartphones is presented. in recent research works and competitions [46], although the comparison of empirical cumulative distribution function plots is also used. The BLE RSS data from the Library zone allows positioning error analyses for different phones (Figure 7a,b), and the data from the Geotec zone allows positioning error analyses for different beacon transmission powers (Figure 7c,d). For the WC positioning method, the usage of data from A5 leads to more noticeable errors than when data from BQ and S6 are used. However, when the FP method is used, the positioning errors are similar among the three phones. In general, the phone that provides the most suitable BLE measurements for positioning is the BQ. Regarding the comparison of different transmission powers, the usage of data captured with the \(-20\) dBm power setting leads to a better accuracy for the WC method, and to a notably worse accuracy for the FP method, than when the data of other two powers are used.