Approaching detection method adopts the manner to collect Cell-ID's related information and calculate the derived parameters, that is, mean of RSSI and standard deviation of RSSI, to help decide whether a user is approaching some POIs or not. Because some proposed fingerprinting-based positioning methods need to collect the cellular information about the whole experimental field, the cost is too high to implement fingerprinting-based positioning methods for the LBS in the whole area, that is, the whole area of a country. We propose ADM to solve the aforementioned problem for some specific purposes, that is, mobile advertisement system and tourist guidance system. In contrast with traditional fingerprinting-based positioning methods over cellular networks, ADM does not position a user's location, but provides a way to compute the existed probabilities of POIs that a user may approach on the basis of the established Cell-ID's related information at server's database.

Approaching detection method adopts the basic concept of the pattern matching method, in which some symbols used in ADM are defined in Table 1, and three components that ADM has are as follows: (1) neighboring Cell-ID mapping, (2) RSSI-scale mapping, and (3) POIs approaching decision.

#### 4.1 An illustration of approaching detection method

In Figure 4, there are totally *N* POIs in the fingerprinting database, and there are at most six Cell-IDs and its corresponding RSSI detected by the cellular phone in a POI per second. We measure Cell-ID's related information in each POI for a period of time, in which the default time length is 30 s. For example, we collect Cell-ID's related information in POI1 from *T*_{1} to *T*_{30}.

After measuring the Cell-ID's related information, it needs to compute the derived information, that is, mean of RSSI and standard deviation of RSSI. Both of them are defined as follows:

- Mean of RSSI: Given one neighboring Cell-ID, let there be different
*RSSI*. The value *i* is set from 1 to *m* that are detected by the cellular phone in the specific location for the time length *T*. Mean of RSSI (*Mean*_{RSSI}(*Cell-ID*)) is the average of those *RSSI*_{i} of one neighboring Cell-ID, which is given in Equation (1). - (1)

- Standard deviation (SD) of RSSI: Let there be different
*RSSI*_{i}. The value *i* is set from 1 to *m*, which is one neighboring Cell-ID and the derived mean of RSSI (Mean_{RSSI}(*Cell-ID*)) in the specific location for the time length *T*. Standard deviation of RSSI (SD_{RSSI}(*Cell-ID*)) of RSSI of one neighboring Cell-ID is given in Equation (2).

- (2)

Figure 4 depicts the table of the transformed fingerprinting database after calculating the derived attributes. For example, there are four different neighboring Cell-IDs, including 51331, 51957, 51958, and 51992 in the same location1 of POI1; their corresponding attributes are also depicted accordingly.

Three parts of ADM are (1) neighboring Cell-ID mapping, (2) RSSI-scale mapping, and (3) POIs approaching decision. In Figure 5, there are five Cell-ID sets received by the cellular phone of a user, that is, 51331, 51957, 51958, 51992, and 51994. Each Cell-ID set contains Cell-ID and RSSI. After transmitting Cell-ID's related information detected by the cellular phone of a user to the fingerprinting server, ADM does the process of neighboring cell-ID mapping first. Neighboring cell-ID mapping finds the number of matches of cell-ID set between a user and the fingerprinting database, and the number of matches is denoted as *N*_{coincidence_cellID}. In Figure 5, there are four Cell-IDs received by the cellular phone of a user that are identical to that of the fingerprint record, hence *N*_{coincidence_cellID} equals 4. Then, ADM computes the probability of approaching a POI (*P*_{approaching_cellID}) according to the parameter *N*_{coincidence_cellID}. The denominator of *P*_{approaching_cellID} represents the number of Cell-IDs received by the cellular phone of a user, and the numerator represents the number of matches of the Cell-ID set between a user and the fingerprinting database. In Figure 5, *P*_{approaching_cellID} equals 0.8.

After processing neighboring cell-ID mapping, ADM executes the process of RSSI-scale mapping. In Figure 5, RSSI-scale mapping mainly compares whether the user's RSSI belongs to the RSSI range of the fingerprinting database or not. The RSSI range of each Cell-ID is within (i) mean of RSSI (*Mean of RSSI*) minus SD of RSSI (*SD of RSSI*) and (ii) mean of RSSI (*Mean of RSSI*) plus SD of RSSI (*SD of RSSI*). Then ADM calculates *P*_{approaching_cellIDRSSI}, which represents the probability of POIs that a user may approach by comparing the similarity of RSSI among each matching Cell-IDs between a user's cellular information and fingerprint records of the fingerprinting database. In Figure 5, *P*_{approaching_cellIDRSSI} equals 0.5.

Finally, ADM operates the POIs approaching decision after having neighboring Cell-ID mapping and RSSI-scale mapping. In Figure 5, *P*_{approaching} is the product of *P*_{approaching_cellID} and *P*_{approaching_cellIDRSSI}, in which *P*_{approaching} represents the probability in which a user is approaching a POI based on Cell-ID mapping and RSSI-scale mapping. ADM sets the threshold of the probability of approaching a POI, if *P*_{approaching} is equal to the threshold or greater than the threshold, ADM puts the corresponding POI with *P*_{approaching} into the candidate list, that is, ADM will observe the probability of a user's approaching the POI for a period of time *T*. From our observation, the value of *T* should be set between 15 s to 45 s. If the value *T* is too small, ADM is hardly to find the correct POIs that a user is approaching. The reason is that the sampled signals of the user device are not stable enough during the sampling duration *T*, and thus many POIs that satisfy the searching criteria based on the unstable signals are imprecisely selected. If the value *T* is too big, the ADM may be inefficient because the user has to wait for longer time to obtain the correct POIs that the user is approaching. In addition, ADM can be used on different status of the user, that is, pedestrian, biker, or driver, as long as the fingerprinting database is made accordingly. That is, when a pedestrian/biker/driver-based fingerprinting database is made, ADM then can be used for pedestrians/bikers/drivers. During the time interval *T*, if there is the increasing or consistent trend of the probability that a user may approach the POI, ADM determines that a user is approaching this POI, which is depicted in Figure 5.

#### 4.2.2 Neighboring Cell-ID mapping

In this part, ADM computes the probability that a user may approach a POI, which can avoid the problem due to the reason of changing BSs, that is, a new BS is installed or a BS goes wrong. First, ADM finds the number of matches of neighboring Cell-IDs between a user and each fingerprint record of the fingerprinting database and compute the probability that a user approaches a POI (*P*_{approaching_cellID}), which is given in Equation (3). In Equation (3), *N*_{received_user_cellID} means the number of neighboring Cell-IDs that is received by the cellular phone of a user; *N*_{coincidence_cellID} represents the number that Cell-IDs of a user's cellular information are identical to fingerprint records of the fingerprinting database.

- (3)

#### 4.2.4 Point of interests approaching decision

After processing neighboring Cell-ID mapping and RSSI-scale mapping, ADM computes the probability that a user may approach a POI (*P*_{approaching}), in which *P*_{approaching} is the product of *P*_{approaching_cellID} and *P*_{approaching_cellIDRSSI}. In Equation (5), if *P*_{approaching} is equal to or greater than the threshold, ADM selects the corresponding POIs as the candidate, to which a user probably approaches. To accurately assure that a user approaches the candidate POIs, ADM observes each candidate POI for a period of time *T*. If there exists consistent or increasing trend of *P*_{approaching} for the time interval *T*, ADM determines that a user is approaching the POI. The judgment rule is given in Equation (6).

- (5)

- (6)