TWM558910U - Wireless asset positioning device - Google Patents

Abstract

A server of a wireless communication system for wireless asset positioning is disclosed. The server comprises a storage device, for storing a programing code corresponding to a process, and a processor, coupled to the storage device, for processing the programing code for executing the process, wherein the process includes receiving a plurality of position information from a plurality of mobile devices, receiving a plurality of Bluetooth signal including RSSI and ID information associated to an asset proximity to the plurality of mobile devices, from the plurality of mobile devices, and calculating a position of the asset according to the plurality of position information of the mobile devices and the Bluetooth signal including RSSI and ID information.

Description

Wireless asset locator

The present invention relates to a communication device of a wireless communication system, and more particularly to a related device for wireless asset location.

Instruments and equipment are indispensable assets for manufacturing and medical centers. Organizations with scales need more equipment and equipment to help organizations operate, but asset management is increasingly difficult as the number of assets increases. In the hospital, millions of dollars are spent each year to make up for lost equipment. Medical staff, because of the uneven distribution of resources and wrong placement, spend 25-33% of their working hours every day to find medical equipment that is frequently used and mobile. Indirectly, medical personnel are unable to focus on patients and reduce the quality of medical services. Similarly, corporate R&D personnel often look for measuring instruments, reduce work efficiency, and delay product development time. Therefore, how to accurately grasp the movement of movable assets in the room and conduct asset tracking is an important issue for enterprise organizations.

With the emergence of wireless technology, the emergence of indoor positioning systems (IPSs) provides the possibility of asset positioning. The acquisition of asset positions through indoor positioning systems can reduce the time spent by employees to find assets and enhance employees' focus on products. R&D and services. However, in the indoor asset tracking system, the anchor node deployment affects the system performance. In the case of limited coverage of each anchor node, the number of anchor nodes will increase as the indoor space expands, and the system deployment cost increases. It also increases. Therefore, in recent years, the concept of crowdsourcing has made the indoor positioning system have a new thinking. The concept of crowdsourcing is to use the ubiquitous mobile device to increase the sensing range through group cooperation. For example, the smart phone can increase the system coverage through the mass perception and reduce the cost of arranging the anchor node.

Therefore, the main purpose of the present invention is to provide a related device for wireless asset location to solve the above problems.

The present invention discloses a server for a wireless communication system for wireless asset location, the server includes: a storage device for storing a code corresponding to a processing method; and a processing device coupled to the a storage device for processing the code to perform the processing method, the processing method comprising: receiving a plurality of location information of the plurality of mobile devices from a plurality of mobile devices of the wireless communication system; and from the plurality of mobile devices Receiving a Bluetooth signal information about a neighboring wireless asset, wherein the Bluetooth signal information includes a Bluetooth received signal strength and an identification code; and calculating the wireless based on the location information of the plurality of mobile devices and the Bluetooth signal information The location of the asset.

The present invention discloses a mobile device for wireless network positioning, the mobile device includes: a storage device for storing a code corresponding to a processing method; and a processing device coupled to the a storage device for processing the code to execute the processing method, the processing method comprising: establishing a signal pattern database, wherein the signal pattern database is used to record a plurality of reference grids pre-arranged in a region Each of the reference grid points measures a plurality of first received signal strengths transmitted from a plurality of access points of the wireless communication system, wherein the signal pattern database includes a plurality of signal pattern data clusters and a corresponding cluster center thereof Signal data; instantaneously measuring a plurality of second received signal strengths sent by the plurality of access points and a Bluetooth received signal strength sent by a neighboring wireless asset; and according to each cluster center signal pattern data and the plurality of second receiving signals Intensity, determining whether the plurality of second received signal strengths belong to the cluster of the plurality of signal patterns a signal pattern data cluster; obtaining a position information of the mobile device according to the determined plurality of first received signal strengths in the signal pattern data cluster and the instantaneously measured plurality of second received signal strengths; Transmitting the location information of the mobile device and the measured Bluetooth signal strength of the wireless asset to a server of the wireless communication system.

Please refer to FIG. 1. FIG. 1 is a schematic diagram of an asset tracking system architecture according to a new embodiment. The new asset location system is an integrated wireless communication system, which includes wireless local area network technology (such as IEEE 802.11 specification, referred to herein as Wi-Fi technology), and Bluetooth Low Energy (Bluetooth Low Energy). In this paper, it is called BLE technology) and cellular communication technology (such as LTE system developed by 3GPP). As shown in Figure 1, the main components of the asset tracking system include a Wi-Fi access point Wi-Fi AP, an asset device configured with a low-power Bluetooth beacon (BLE beacon) function, and crowdsourcing users mobile. Device), user mobile device, and server. From the bottom up, in the first layer, it is mainly composed of assets and multiple Wi-Fi APs. The asset equipment is equipped with low-power Bluetooth beacon function for asset identification and asset location; Wi-Fi AP layout Provide positioning of mass mobile devices in the environment. The second layer includes the mass mobile device and the user mobile device, where the mass mobile device is a mobile device for the system user who assists in providing asset positioning information, and the user mobile device is an asset-seeking person, and the user can also provide asset positioning information. The mobile device will collect the received signal strength BLE RSSI and the beacon identification code BLE ID of the Bluetooth beacon sent by the assets in the environment. The identifier content includes three parts: the proximity universal unique identifier (proximity UUID), the main number The parameter (major) and the minor number parameter (minor), and the Wi-Fi RSSI and the identification code Wi-Fi ID of the Wi-Fi AP in the collection environment, and then transmit the collected data to the third through the wireless signal. Layer server. The server locates the asset through the mass personnel location information and asset location information, and provides the user with the location of the asset.

Please refer to FIG. 2, which is a schematic diagram of a communication device 20 according to a new embodiment. The communication device 20 can be a user mobile device or a mass mobile device (such as a smart phone supporting Wi-Fi technology and BLE technology) in FIG. 1 , and includes a processing device 200 , a storage device 210 , and a communication interface device . 220, comprising a Wi-Fi communication interface unit, a BLE communication interface unit, and a cellular communication interface unit. Processing device 200 can be a microprocessor or an application-specific integrated circuit (ASIC). The storage device 210 can be any data storage device for storing a code 214 and reading and executing the code 214 through the processing device 200. For example, the storage device 210 can be a subscriber identity module (SIM), a read-only memory (ROM), a flash memory, or a random access memory ( Random-access memory (RAM), CD-ROM (DVD-ROM), magnetic tape, hard disk, and optical data storage device, etc. Limited to this. The control communication interface device 220 can be a wireless transceiver that exchanges wireless signals with a network (such as an LTE network or a server) according to the processing result of the processing device 200.

The purpose of the present invention is to provide a wireless asset locating device that is highly accurate and can track assets in real time. The new asset tracking includes two parts: the mass personnel positioning process and the asset positioning process. The details are as follows.

Please refer to FIG. 3, which is a schematic diagram of a mass personnel positioning process 30 according to the new embodiment. The mass personnel positioning process 30 is used for the communication device 20 (such as the mass and user mobile devices in FIG. 1) for obtaining location information of the masses and user mobile devices. The crowd location process 30 can be compiled into the code 214 and stored in the storage unit 210, which includes the following steps:

Step 300: Start.

Step 310: Establish a signal pattern database, where the signal pattern database is used to record each reference grid point of a plurality of pre-arranged reference grids in a region, and measure multiple accesses from the wireless communication system. The plurality of first received signal strengths transmitted by the point, wherein the signal pattern database comprises a plurality of signal pattern data clusters and a corresponding cluster center signal pattern data respectively.

Step 320: Instantly measure a plurality of second received signal strengths transmitted by the plurality of access points and a Bluetooth received signal strength transmitted by a neighboring wireless asset.

Step 330: Determine, according to each cluster center signal pattern data and the plurality of second received signal strengths, which of the plurality of signal pattern data clusters of the plurality of second received signal strengths is measured.

Step 340: Obtain a position information of the mobile device according to the determined plurality of first received signal strengths in the signal pattern data cluster and the instantaneously measured plurality of second received signal strengths.

Step 350: Transmit the location information of the mobile device and the measured Bluetooth signal strength of the wireless asset to a server of the wireless communication system.

Step 360: End.

According to the mass personnel positioning process 30, the mobile device establishes a Wi-Fi signal pattern database (also referred to herein as a Wi-Fi signal pattern map) for use as a basis for locating the mobile device. It is worth noting that the Wi-Fi signal pattern map contains a plurality of signal pattern data clusters and a corresponding cluster center signal pattern data, which are used to reduce the calculation amount and time of calculating the location of the mobile device, thereby improving the performance of real-time tracking assets. . In addition, the mobile device measures the Bluetooth received signal strength of the adjacent asset and transmits its location information and Bluetooth received signal strength to the server for the server to locate the asset location.

Further, the mass personnel positioning process 30 of the present invention includes an offline stage and an online stage. In the offline phase, the main purpose is to collect the environment Wi-Fi signal pattern map, while the online positioning stage is to compare the Wi-Fi signal pattern map to estimate the location of the mobile device. See Figure 4A-4B for details on how the mass personnel location process 30 works. In the offline phase of the mass personnel positioning, as shown in FIG. 4A, in the offline phase, firstly, through the mobile device, such as a smart phone, the receiving signal strength Wi-Fi RSSI of the Wi-Fi AP in the environment is received, and then through data processing, The received signal strength Wi-Fi RSSI and ID measured in the indoor space are recorded in the signal pattern database or the signal pattern map. In addition, in order to reduce the computational complexity of the signal alignment data in the online positioning phase, the present invention proposes to use the k-means clustering to group the signal pattern maps, so that the grouped signals will be provided after the offline phase is completed. Pattern map and signal vector of each group center.

In the online positioning phase, as shown in FIG. 4B, each mobile device will instantly measure the received signal strength Wi-Fi RSSI and ID of the Wi-Fi AP and the received signal strength BLE RSSI and ID of the asset device. The mobile device will instantly measure the received signal strength Wi-Fi RSSI and ID comparison. The group center signal vector provided by the offline phase will classify the instantaneously measured received signal strength Wi-Fi RSSI into the most similar cluster. The location algorithm obtains the location of the mobile device, obtains the location, and transmits the signal strength BLE RSSI to the server together with the data processing device to receive the asset location process, and finally obtains the asset location.

The details of the Wi-Fi signal pattern map creation operation in the offline phase are as follows. The offline phase is divided into two steps. The first step is to arrange the reference grid points. As shown in Figure 5, the mobile device measures the vector of each reference grid signal to establish a signal pattern map. The measurement personnel measured the Wi-Fi AP reception signal strength value in all environments through the smart phone, and in order to reduce the influence of the smart phone receiving the Wi-Fi AP reception signal intensity value disturbance, the measurement is established. When the reference grid signal vector is used, the average filter will be used to reduce the received signal strength value of the Wi-Fi AP. The operation of the averaging filter is shown in Equation 3.1:  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> </td><td><img wi="76" he="58" file= "02_image001.jpg" img-format="jpg"></img><img wi="448" he="77" file="02_image003.jpg" img-format="jpg"></img></ Td><td> (3.1) </td></tr></TBODY></TABLE>

among them, Representing the reference grid, On behalf of time, N represents the number of documents, Representing the Wi-Fi AP in the environment, Representative at the reference grid Measured Wi-Fi AP First Pen RSS value. For example, N=10 means that the average is taken every 10 strokes.

Reference grid Measured After receiving the signal strength, the Wi-Fi Ap passes through the averaging filter and records it to become the reference grid signal vector R, which can be expressed by Equation 3.2: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td></td><td><imgwi="22"he="41"file="TWM558910U_D0010.tif"img-format="jpg"></img><imgwi="318"he="45"file="02_image015.jpg"img-format="jpg"></img></td><td> (3.2) </td></tr></TBODY></TABLE>

All reference grid points will be recorded after the first step in the offline phase is completed. And establish a Wi-Fi signal pattern map, Wi-Fi signal pattern map can be expressed by the formula: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td></td><td> M <img wi="161"he="56"file="02_image017.jpg"img-format="jpg"></img></td><td> (3.3) </ Td></tr></TBODY></TABLE>

After obtaining the Wi-Fi signal pattern map, in the second step, the Wi-Fi signal pattern map is used to k-means clustering, and the Wi-Fi signal pattern map is grouped to reduce the online positioning stage comparison reference grid. The number of points, the k-mean algorithm is a way of clustering data. Its main purpose is to find a similar cluster of data, so that the data of the same attribute is classified into a subset of the same cluster, in the k-average In the algorithm is The data is divided into k clusters, so that the sum of squares in the group is the smallest to satisfy the formula 3.4: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td></td><td><imgwi="267"he="97"file="02_image019.jpg"img-format="jpg"></img></td><td> (3.4) </ Td></tr></TBODY></TABLE>

Represents the number of clusters, Representation of information, Representing cluster centers, Represents a cluster collection, Signal pattern vector Group center The signal pattern vector Euclidean distance is defined as shown in Equation 3.5: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td><imgwi="301"he="123"file="02_image029.jpg"img-format="jpg"></img></td><td> (3.5) </td></tr></TBODY></TABLE>

In the k-mean algorithm, it is assumed that the initial Group center point The algorithm steps are alternated in the following two steps:

Distribution step

Each input data is assigned to each cluster to minimize the sum of squares in the group. This method uses the Euclidean distance to compare the input data with the group center to assign the data to the cluster with the highest similarity, as shown in Equation 3.6:  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td><img wi="475" he="56" file="02_image033.jpg" img- Format="jpg"></img></td><td> (3.6) </td></tr></TBODY></TABLE>

2. Update steps

Once the data is assigned to each cluster, each cluster center is recalculated, as shown in Equation 3.7:  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td><img wi="154" he="86" file="02_image035.jpg" img- Format="jpg"></img></td><td> (3.7) </td></tr></TBODY></TABLE>

Therefore, after completing the offline phase, the mobile device provides a grouped Wi-Fi signal pattern map and a group center signal pattern vector to provide information required for the online positioning phase.

During the online positioning phase, the mobile device measures the Wi-Fi RSSI of all Wi-Fi APs receiving the signal strength, and records the signal pattern vector of a test point. , as shown in Equation 3.8: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td></td><td><imgwi="18"He="41"file="TWM558910U_D0021.tif"img-format="jpg"></img><imgwi="318"he="45"file="02_image015.jpg"img-format="jpg"></img></td><td> (3.8) </td></tr></TBODY></TABLE>

Compare the test point signal vector to the cluster center, and get the most similar cluster through the Euclidean distance Reference point, The cluster center signal vector represented as k cluster, as shown in Equation 3.9: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td><img wi= "464"he="56"file="02_image043.jpg"img-format="jpg"></img></td><td> (3.9) </td></tr></TBODY></TABLE>

Get the most similar cluster After that, it is assumed that the cluster signal pattern map arch has j reference grid points, wherein each reference grid point can be expressed as Its vector is shown in Equation 3.10, and t represents the number of Wi-Fi Aps in the environment. <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td></td><td><imgwi="22"he="41" file= "TWM558910U_D0010.tif"img-format="jpg"></img><imgwi="407"he="46"file="02_image045.jpg"img-format="jpg"></img></Td><td> (3.10) </td></tr></TBODY></TABLE>

Computational cluster through Euclid distance Medium reference grid point j and test point distance , as shown in Equation 3.11: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td><imgwi="226"he="123" file= "02_image049.jpg"img-format="jpg"></img></td><td> (3.11) </td></tr></TBODY></TABLE>

The distance between the cluster reference point and the test point Euclid distance is arranged from large to small, the k distance minimum points are selected, and the Euclid distance of the point is obtained, and the point weight value is calculated. , versus In inverse proportion, when The bigger the weight, the smaller, The smaller the weight, the larger, as shown in Equation 3.12: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td><imgwi="153" he= "84"file="02_image053.jpg"img-format="jpg"></img></td><td> (3.12) </td></tr></TBODY></TABLE>

Estimated target coordinates Obtained by the k closest reference point coordinates and their weights, as shown in Equation 3.13: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td><img wi ="265"he="75"file="02_image057.jpg"img-format="jpg"></img></td><td> (3.13) </td></tr></TBODY></TABLE>

Therefore, after completing the online positioning phase, the mobile device provides the location information and the received signal strength BLE RSSI and ID processed by the data to the server for the asset positioning process.

Please refer to FIG. 6. FIG. 6 is a schematic diagram of an asset locating process 60 according to the new embodiment. The asset location process is used by the communication device 20 (such as the server in Figure 1) to obtain the location of the asset. The asset location process 60 can be compiled into the code 214 and stored in the storage unit 210, which includes the following steps:

Step 600: Start.

Step 610: Receive a piece of location information of the plurality of mobile devices from a plurality of mobile devices of the wireless communication system.

Step 620: Receive, from the plurality of mobile devices, a Bluetooth signal information about a neighboring wireless asset, wherein the Bluetooth signal information includes a Bluetooth received signal strength and an identification code.

Step 630: Calculate the location of the wireless asset according to the location information of the plurality of mobile devices and the Bluetooth signal information.

Step 640: End.

According to the asset location process 60, the server receives location information about the mobile device and asset location information from the mobile device, that is, the received signal strength BLE RSSI and ID of the Bluetooth beacon, and then receives according to the log-distance path loss model. The signal strength BLE RSSI is converted into a distance, and the location of the asset is obtained according to the location of the mobile device.

The detailed operation of the asset location process 60 is described in detail below. Please refer to FIG. 7. FIG. 7 is a schematic diagram of the path loss model conversion distance according to the new embodiment. It can be seen from the above that after the mobile personnel positioning process 30 is completed, the mobile device obtains the location information of the mobile device, such as the three human position coordinates (15, 6), (23, 4) and (16, 4) shown in FIG. ). In addition, the mobile device will measure the received signal strength of the asset BLE RSS based on the path loss model, and calculate the distance between the personnel position and the asset position as 1, 7.5 and 2, respectively, so the server can be based on the position coordinates of the personnel (15, 6) ), (23, 4) and (16, 4) and distance information, calculate the position coordinates of the assets as (16, 6).

It should be noted that, in an embodiment of the present invention, after obtaining the location information provided by the k most recent time personnel and receiving the signal strength BLE RSSI, the server considers the distance between the positions of the k crowded personnel and the asset as the adjustment weight. Based on the acquisition of the asset location. The details are as follows:

Get the Bluetooth RSS values on the k most recent time personnel locations and their assets, as shown in Equation 3.14:  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td><img wi="279" he="46" file="02_image059.jpg" img- Format="jpg"></img></td><td> (3.14) </td></tr></TBODY></TABLE>

Estimated asset coordinates Provide the location of the information personnel and their weights through the most recent time, as shown in Equation 3.15: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td><imgWi="265"he="75"file="02_image057.jpg"img-format="jpg"></img></td><td> (3.15) </td></tr></TBODY ></TABLE>

The weight value is adjusted according to the distance between the information personnel and the asset location, and the weight value Inversely proportional to the distance, the closer the distance is, the greater the weight, and the farther the distance is, the smaller the weight is, as in Equation 3.16: <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td><imgwi="219"he="113"file="02_image063.jpg"img-format="jpg"></img></td><td> (3.16) </td></ Tr></TBODY></TABLE>

The distance between personnel and assets is the conversion of the Bluetooth RSSI through the log-normal shadowing path loss model. The details are as follows:

Path loss refers to the attenuation of the received signal strength as the distance increases with distance, whether it is indoors or outdoors. This phenomenon can be expressed by the log-distance path loss model and also by the received signal strength. The exponential decay is presented, and the path average loss receiving power is proportional to the distance nth power, so the average loss relationship of the received power can be expressed by Equation 3.17.  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td><img wi="145" he="75" file="02_image065.jpg" img- Format="jpg"></img></td><td> (3.17) </td></tr></TBODY></TABLE>

If the distance between the transmitting end and the receiving end is d, the average power loss can be expressed as Equation 3.18, and its unit is decibel (dB).  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td><img wi="305" he="72" file="02_image067.jpg" img- Format="jpg"></img></td><td> (3.18) </td></tr></TBODY></TABLE>

Where n is the path loss index, and the value of n will vary from environment to environment. As shown in Fig. 8, Fig. 8 is a schematic diagram of the environmental path loss index of the new embodiment. The smaller the value of n, the smaller the loss of the signal as the propagation distance increases. For reference distances, the value usually chooses a very close transmitter distance.

However, in the propagation path loss model, only the received power loss caused by the distance is considered, and it is not considered that the transmission end and the receiving end are affected by different shieldings, and the change can be applied to the log-normal distribution (log- Normal distribution) means that when the number of samples is sufficient at the same distance, the received signal strength of the receiving end of different environments exhibits a log-normal distribution. Therefore, to estimate the received signal strength, a lognormal shadowing effect path loss model can be used. (log-normal shadowing path loss model) representation. As in formula 3.8

Said.  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td><img wi="358" he="72" file="02_image071.jpg" img- Format="jpg"></img></td><td> (3.19) </td></tr></TBODY></TABLE>

Where n is the path loss index and the value of n will vary from environment to environment, as shown in Table 3.1. In order to fall into the reference distance, Is a Gaussian random variable with an average of 0, standard deviation Different sizes represent the effects of the shadowing effect.

The novel uses the log-distance path loss model to convert the measured Bluetooth signal strength BLE RSSI measured by the user into a distance, and then considers the distance as the adjustment weight according to the formula 3.20, and derives the formula 3.21 according to the weighted calculation, so that the distance asset The information provider who is closer to the low-power Bluetooth beacon can have a larger weight, and the asset location location can also be closer to the asset-providing personnel. The more information personnel provide, the more the actual location of the asset can be met.  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td><img wi="180" he="56" file="02_image079.jpg" img- Format="jpg"></img></td><td> (3.20) </td></tr><tr><td><img wi="588" he="116" file="02_image081 .jpg" img-format="jpg"></img></td><td> (3.21) </td></tr></TBODY></TABLE>

among them In order to provide the weight of the asset personnel, In order to provide the Bluetooth receiver signal strength measured by the asset personnel, n is the path loss index.

Referring to FIG. 9, it is a schematic diagram of a scenario in which an asset tracking system is used in the new embodiment. The new asset tracking system can be used in large indoor spaces, such as medical centers, manufacturing companies, and outsourced users for the system, such as medical center medical staff, system users carry personal smart mobile devices And can return the location information of the mobile device (through the mass personnel positioning process 30) and the surrounding asset location information to the server, and the server calculates the assets through the asset positioning process 60 and the asset positioning algorithm proposed by the new model. Location, ultimately looking for asset personnel can get asset location through the server

All of the above steps, including the suggested steps, can be implemented by means of hardware, carcass (ie, a combination of a hardware device and a computer command, data in a hardware device is a read-only software) or an electronic system. The hardware can include analog, digital, and hybrid circuits (ie, microcircuits, microchips, or germanium wafers). The electronic system may include a system on chip (SOC), a system in package (Sip), a computer on module (COM), and a communication device 20.

In summary, this new model proposes a mass outsourcing asset positioning method that integrates Wi-Fi technology and BLE technology to achieve the purpose of mass outsourcing indoor asset tracking, and uses a wide range of smart phones as anchor nodes to sense asset positions. Increase system coverage and reduce the cost of arranging anchor nodes. In simple terms, combined with the Wi-Fi signal pattern positioning method, the mass mobile phone is first positioned in a large indoor space, and then the low-power Bluetooth beacon is installed on the asset (the smart phone provides the support advantage) to provide the mass mobile device. Obtain asset information and identify assets. Finally, locate the assets through the path loss model based on the path loss model and the measured Bluetooth asset information. Therefore, the wireless asset locating device proposed by the present invention can improve the positioning efficiency with the increase of the number of providing personnel compared with other positioning devices, and highlights the advantages of the mass outsourcing positioning system for indoor asset tracking.

BLE RSSI&ID‧‧‧Bluetooth Beacon Received Signal Strength and Identification

Receive signal strength and identification of Wi-Fi RSSI&ID‧‧‧ Wi-Fi signals

Wi-Fi AP‧‧ Wi-Fi access point

30, 60‧‧‧ Process

300-360, 600-640‧‧‧ steps

20‧‧‧Communication device

200‧‧‧Processing device

210‧‧‧Storage device

214‧‧‧ Code

220‧‧‧Communication interface device

FIG. 1 is a schematic diagram of an asset tracking system architecture of a new embodiment. Figure 2 is a schematic view of a communication device of the new embodiment. Figure 3 is a schematic diagram of the positioning process of the mass personnel in the new embodiment. Figure 4A-4B is a schematic diagram of the operation of the mass personnel. Fig. 5 is a schematic view showing a reference grid of an environment arrangement according to a new embodiment. FIG. 6 is a schematic diagram of an asset positioning process according to a new embodiment. Figure 7 is a schematic diagram showing the conversion distance of the path loss model of the new embodiment. Figure 8 is a schematic diagram of an environmental path loss index of the new embodiment. Figure 9 is a schematic diagram of the use scenario of the asset tracking system of the new embodiment.

Claims (11)

A wireless asset locating device for use in a wireless communication system for wireless asset location, the wireless asset locating device comprising: a storage device for storing a code corresponding to a processing method; and a processing device And the storage device is configured to process the code to execute the processing method; wherein the processing method comprises: receiving, from a plurality of mobile devices in the wireless communication system, a location of the plurality of mobile devices Receiving, from the plurality of mobile devices, a Bluetooth signal information about a neighboring wireless asset, wherein the Bluetooth signal information includes a Bluetooth received signal strength and an identification code; and the location information according to the plurality of mobile devices and The Bluetooth signal information calculates the location of the wireless asset. The wireless asset locating device of claim 1, wherein the calculating the location of the wireless asset based on the location information of the plurality of mobile devices and the Bluetooth signal information comprises: receiving the Bluetooth according to the Bluetooth signal information Signal strength, and a path loss model conversion for the Bluetooth received signal strength, calculating a distance between the plurality of mobile devices and the wireless asset; and determining the location information of the plurality of mobile devices and the wireless asset This distance gives the location of the wireless asset. The wireless asset locating device of claim 2, wherein the processing method further comprises: configuring the corresponding weight value to the location information of the plurality of mobile devices according to the distance between the plurality of mobile devices and the wireless asset ;as well as The location of the wireless asset is calculated based on the location information of the plurality of mobile devices, the weight value of the corresponding configuration, and the distance from the wireless asset. The wireless asset locating device of claim 1, wherein the identification code comprises a proximity universal unique identification code, a primary numbering parameter, and a secondary numbering parameter. The wireless asset locating device of claim 1, wherein the wireless communication system comprises a wireless local area network technology, a Bluetooth technology, and a cellular communication technology. The wireless asset locating device of claim 1, wherein the processing method further comprises: receiving, from a mobile device in the wireless communication system, a request message for finding a location of the wireless asset. The wireless asset locating device of claim 1, wherein the calculating the location of the wireless asset based on the location information of the plurality of mobile devices and the Bluetooth signal information comprises: selecting the plural received in the most recent time The location information of the mobile device and the Bluetooth signal information of the mobile device calculate the location of the wireless asset, wherein the number of the mobile devices is determined by the wireless communication system arrangement range. A wireless asset locating device for use in a wireless communication system for wireless asset location, the wireless asset locating device comprising: a storage device for storing a code corresponding to a processing method; and a processing device And coupled to the storage device, configured to process the code to execute the processing method; wherein the processing method includes: Establishing a signal pattern database for recording each reference grid point of a plurality of pre-arranged reference grid points in a region, and measuring the transmission from a plurality of access points of the wireless communication system a plurality of first received signal strengths, wherein the signal pattern database comprises a plurality of signal pattern data clusters and a corresponding cluster center signal pattern data; and the plurality of second received signal strengths sent by the plurality of access points are measured instantaneously And a Bluetooth receiving signal strength sent by a neighboring wireless asset; determining, according to each cluster center signal data and the plurality of second receiving signal strengths, that the plurality of second receiving signal strengths belong to the plurality of signal data clusters Which of the signal patterns is clustered; a position of the mobile device is obtained based on the determined first received signal strength in the signal pattern cluster and the instantaneously measured second received signal strengths Information; and transmitting the location information of the wireless asset locating device and the instantaneously measured wireless asset Tooth signal strength to a server of the wireless communication system. The wireless asset locating device of claim 8, wherein the processing method further comprises: performing a data grouping process on the plurality of received signal strengths, and distributing the plurality of first received signal strengths recorded to the plurality The signal pattern data cluster; and the cluster center signal data is calculated according to the first received signal strength assigned to each signal pattern data cluster. The wireless asset locating device of claim 8, wherein the wireless device is determined according to the determined plurality of first received signal strengths in the signal pattern data cluster and the instantaneously measured plurality of second received signal strengths. The steps of the location information of the asset locator include: Calculating a plurality of reference grid points corresponding to the plurality of first received signal strengths and the complex number according to the plurality of first received signal strengths in the signal pattern data cluster and the instantaneously measured plurality of second received signal strengths a plurality of distances between a test point corresponding to the second received signal strength; arranging the plurality of distances according to the size; selecting a plurality of minimum distances, and configuring a corresponding weight value according to the size; and according to the selected plurality of weights The reference grid point corresponding to the minimum distance and the weight value are used to calculate the location information of the wireless asset locating device. The wireless asset locating device of claim 8, wherein the processing method further comprises: transmitting a request message for finding the location of the wireless asset to the server.