CN117941009A

CN117941009A - System and method for assigning medical assets to rooms using real-time Wi-Fi positioning

Info

Publication number: CN117941009A
Application number: CN202280061830.8A
Authority: CN
Inventors: A·S·富尔尼克; S·查特吉
Original assignee: Koninklijke Philips NV
Current assignee: Koninklijke Philips NV
Priority date: 2021-09-13
Filing date: 2022-09-07
Publication date: 2024-04-26

Abstract

A method and system for assigning assets to rooms in a medical environment using a Wi-Fi based real-time location system. The room is fingerprinted to determine a first representative location and a threshold distance of the room. Fingerprinting includes determining a first representative location of a room using location data over a first time period (e.g., 24 hours) and determining a set of second representative locations of the room using location data over a second time period (e.g., 1 hour). The threshold distance is found by comparing the first representative location to a set of second representative locations. The location data of the asset is used to find a current representative location for the asset and the current representative location is compared to a range of locations attributable to the fingerprinted room. The range of locations attributable to the room is based on the threshold distance. If the current representative location is within a range of locations attributable to the room, the asset is assigned to the room.

Description

System and method for assigning medical assets to rooms using real-time Wi-Fi positioning

Technical Field

The present invention relates to a real-time Wi-Fi positioning system in a medical/clinical environment and a method of asset tracking by means of a real-time Wi-Fi positioning system.

Background

As the population ages and the number of patients admitted worldwide increases, hospitals are under increasing pressure to better utilize their resources, including personnel, equipment and all medical facilities. Efficient resource planning is critical to improving hospital productivity, quality, and control or reduce costs. One way hospitals reduce cost and improve efficiency is by optimizing the inventory and use of physical assets. This is particularly true for mobile assets such as infusion pumps and wheelchairs.

To achieve asset optimization, a real-time location system (RTLS) may be used. More specifically, using RTLS may allow for efficient searching of assets and for gathering data about usage, movement, and behavior. This allows data-based decisions to be made in optimizing the inventory of assets. For example, calculating the utilization of a set of assets and noticing that the utilization is very low may mean that the inventory is too high.

Real-time location systems (RTLS) provide for immediate or real-time tracking and management of medical devices, personnel, and patients. Such solutions enable medical institutions to obtain workflow efficiency, reduce costs, and improve clinical quality. RTLS solutions include various tags and badges, platforms (Wi-Fi, infrared, ultrasound, and others), hardware infrastructure (readers and exciters), and other components (servers, middleware, and end-user software).

RTLS solutions typically consist of specialized fixed position sensors that receive wireless signals from small ID badges or tags attached to devices or personnel. Each tag transmits its own unique ID in real time and depending on the technology chosen, the system locates the tag and thus the location of the tagged entity. Depending on the solution, different degrees of granularity may be achieved. The basic RTLS solution can enable tracking in hospital wards or floors, while the clinical level system can enable room, bed, compartment and even shelf level tracking.

However, asset optimization using RTLS is easy to do, especially when hospitals use Wi-Fi based RTLS with lower accuracy. Because of the reduced room level accuracy of Wi-Fi based RTLS, it is difficult to confidently determine whether an asset is in a storage state and therefore not in use.

Disclosure of Invention

The invention is defined by the claims.

According to an example of an aspect of the invention, there is provided a method for assigning assets to rooms in a medical environment, the method using a Wi-Fi based real-time location system to determine the location of tags, the method comprising:

-Fingerprinting (FINGERPRINTING) the room, wherein the fingerprinting comprises:

receiving a plurality of fingerprint identification locations over a first period of time from a plurality of tags placed throughout a room;

calculating a first representative location based on the fingerprint identification locations over a first period of time;

Calculating a second set of representative locations from the fingerprint-identified locations over a plurality of shorter second time periods; and

Determining a threshold distance for the room by comparing the first representative location to the set of second representative locations;

receiving a plurality of locations of tags placed on an asset;

Calculating a current representative location from the plurality of locations;

comparing the current representative location to a range of locations attributable to the room, wherein the range of locations is determined using the threshold distance; and

Assets are assigned to the room in response to the current representative location being within a range of locations attributable to the room.

The accuracy of Wi-Fi based real-time location systems (RTLS) is typically about 2m-4m. This means that the asset may be located in a different room than the room indicated by the RTLS location. This disadvantage of Wi-Fi based RTLS means that it becomes difficult to determine if the asset is in storage, as errors in location may indicate that the asset is located in a room near the storage room, which may also suggest that the asset is in use even if the asset is in storage.

Thus, the determination of the threshold distance during fingerprinting provides an indication of acceptable errors of the RTLS. In other words, the threshold distance indicates how far outside the room the Wi-Fi RTLS can display the asset while still assigning the asset to the room. This reduces false assignments to utilization (i.e., indicating that the asset is in use when in fact the asset is in storage).

"Assigning an asset to a room" means making an assessment of the asset in the room, i.e., assigning data to the asset indicating that the asset is in the room. This data may then be used to determine the utilization level of the asset if the asset is known to be unused while in the room.

Representative locations of the plurality of locations may be calculated by determining a centroid, an average, a median, a weighted average (e.g., the most recently location weighted higher), a geometric average, or other averaging tool of the locations received from the RTLS system.

In a preferred implementation, the first representative location and/or the second representative location may be a centroid of the corresponding fingerprint identification location.

Similarly, the current representative location may be a centroid of a corresponding plurality of locations.

Comparing the current representative location to a range of locations attributable to the room may include: a distance between the current representative location and the first representative location is calculated, wherein an asset is assigned to the room if the calculated distance is less than a threshold distance.

The room may be a storage room for storing assets.

The method may further comprise: utilization of the asset over the time horizon is calculated by determining a percentage of time the asset spends in the storage room over the time horizon.

The current representative position may be calculated every third time period, where the third time period is a time resolution of the Wi-Fi based real-time positioning system.

This provides a sliding window for the calculation of the current representative position, thereby improving the granularity of the center centroid measurement.

Thus, the combination of the above features provides a method for tracking assets in a medical environment using a Wi-Fi based real-time location system to determine the location of a tag, the method comprising:

Fingerprint identification is carried out to the apotheca, and wherein, fingerprint identification includes:

receiving a plurality of locations over a first period of time from a plurality of tags placed throughout a storage compartment;

calculating a first centroid of the location over the first time period;

calculating a set of second centroids for locations within a plurality of shorter second time periods; and

Determining a threshold distance for the reservoir by comparing the first centroid to the set of second centroids;

receiving a plurality of locations of tags placed on an asset;

calculating a third centroid of the location within the third time period;

calculating a distance between the third centroid and the first centroid; and

In response to the calculated distance being less than the threshold distance, the asset is assigned to the storage room.

The present invention also provides a computer program product comprising computer program code which, when executed on a computing device having a processing system, causes the processing system to perform all the steps of the method defined above.

The present invention also provides a system for assigning assets to rooms in a medical environment, the system using a Wi-Fi based real-time location system to determine the location of tags, the system comprising a processor configured to:

the room is fingerprinted, wherein the processor is configured to fingerprint by:

receiving a plurality of locations of tags placed on an asset;

Calculating a current representative location from the plurality of locations;

The first representative location and/or the second representative location may be a centroid of the corresponding fingerprint-identified location.

The current representative location may be a centroid of the corresponding location.

The processor may be configured to: the current representative location is compared to a range of locations attributable to the room by calculating a distance between the current representative location and the first representative location, wherein the asset is assigned to the room if the calculated distance is less than a threshold distance.

The room may be a storage room for storing assets.

The processor may be further configured to: utilization of the asset over a time horizon is calculated by determining a percentage of time the asset spends in the storage room over the time horizon.

These and other aspects of the invention will be apparent from and elucidated with reference to the embodiments described hereinafter.

Drawings

For a better understanding of the invention, and to show more clearly how it may be carried into effect, reference will now be made, by way of example only, to the accompanying drawings in which:

FIG. 1 shows a known CENTRAK RTLS system;

FIG. 2 shows steps for fingerprint identification; and

Fig. 3 illustrates a method for assigning assets to a room.

Detailed Description

The present invention will be described with reference to the accompanying drawings.

It should be understood that the detailed description and specific examples, while indicating exemplary embodiments of the apparatus, system, and method, are intended for purposes of illustration only and are not intended to limit the scope of the invention. These and other features, aspects, and advantages of the apparatus, system, and method of the present invention will become better understood from the following description, appended claims, and accompanying drawings. It should be understood that the drawings are merely schematic and are not drawn to scale. It should also be understood that the same reference numerals are used throughout the drawings to indicate the same or similar parts.

The present invention provides methods and systems for assigning assets to rooms in a medical environment using a Wi-Fi based real-time localization system. The room is fingerprinted to determine a first representative location and a threshold distance of the room. Fingerprinting includes determining a first representative location of a room using location data over a first time period (e.g., 24 hours) and determining a set of second representative locations of the room using location data over a second time period (e.g., 1 hour). The threshold distance is found by comparing the first representative location to a set of second representative locations. The location data of the asset is used to find the current representative location of the asset and it is compared to a range of locations attributable to the fingerprinted room. The range of locations attributable to the room is based on the threshold distance. If the current representative location is within a range of locations attributable to the room, the asset is assigned to the room, i.e., the asset is assessed as being within the room.

One example of a known RTLS solution is the so-called CenTrak (trade mark) RTLS. Fig. 1 shows a CENTRAK RTLS system. CENTRAK RTLS have been used in a number of studies to automatically record and analyze workflow characteristics in emergency departments and other hospital departments, and this approach has also been used by applicant's asset tracking system, titled "PerformanceFlow", in commercial trials.

CenTrak System (www.centrak.com) is a clinical, commercially available system that fully acquires CE and FCC certification and has found application in more than 750 hospitals worldwide. CENTRAK RTLS the solution includes a beacon (including a "monitor (Monitors)" 106 and a "virtual wall (VirtualWalls)" 104) that transmits an Infrared (IR) code 114 representing a room or hallway, and a patient tag 108, asset tag 110 and personnel badge 112 that can detect the IR code 114 and send the code along with their own ID to a server 116 via a router ("Star") 102. Beacons 104 and 106 are battery powered and therefore do not need to be connected to a power source and can be located anywhere location data is needed. Since the IR signal 114 does not pass through a wall, the room location can be detected with certainty. The star 102, monitor 106 and virtual wall 104 are mounted on the ceiling, personnel tags 112 and patient tags 108 are worn using conventional hospital bracelets, and asset tags 110 are attached to the assets/devices to be tracked. All assets/devices are specifically designed for hospital use.

Tags 108, 110, and 112 communicate with star 102 via an RF link using a 900MHz channel. Similarly, virtual wall 104 and monitor 106 also communicate with star 102 via an RF link using a 900MHz channel. Typically, star 102 communicates with server 116 via a wired ethernet connection.

Depending on the context and purpose of the RTLS implementation, the monitor 106, virtual wall 104, and star 102 may be placed in an emergency room, corridor, examination room, operating room, or other area of a hospital.

The operation of Wi-Fi based RTLS is similar to that of the IR system used by CENTRAK RTLS. The main difference is that each tag communicates with a Wi-Fi Access Point (AP) rather than a monitor. The APs triangulate the location of the tag based on signal strength and report the location to the Centrak system to create a single stream of location information.

Wi-Fi based positioning is inaccurate compared to infrared. The system uses the Relative Signal Strength Indicator (RSSI) reported by the tag for each nearby access point to calculate the (X, Y) coordinate pair for each tag. However, this method alone is inadequate because it does not take into account specific environmental conditions, such as walls, the layout of a room, the number of objects in a room, or the movement of other objects or people in the vicinity.

When Wi-Fi based RTLS is used, this makes room-based utilization metrics difficult to trust as the room may be reported incorrectly.

It is an object of the present invention to solve the aforementioned problems in Wi-Fi based RTLS and to enable the creation of more trustworthy room-based metrics (e.g. utilization) for Wi-Fi based RTLS systems.

In most cases, there is a specialized asset-specific storage room in the hospital. In these areas, it may be assumed that the asset is not in use and is therefore a good proxy for computing utilization. More specifically, the calculation is:

u＝1-s

where u is the percent utilization of the asset over a given time frame and s is the percent of time the asset spends in the storage room over the same time frame.

For calculating s, a fingerprinting method may be used, wherein RTLS tags are stored in different areas of the room for a set period of time. This period of time may range from 24 hours to several weeks, depending on the degree of dynamics of the observed signal. The following example will use a 24 hour data collection period.

Note that in this case, the term "fingerprint" is used in the networking and network security sense of the word. In other words, fingerprinting refers to a collection of information that may be used to identify network protocols, operating systems, hardware devices, software, and other information. The term should be distinguished from the art that refers to the use of biometric fingerprints to distinguish between individual fingerprints. The fingerprinting step may be considered as a calibration phase of the system.

Fig. 2 shows the steps of fingerprint identification 200. Over a 24 hour period, the RTLS tag will report many different (X, Y) coordinate pairs indicating the fingerprint identification location. Wi-Fi based RTLS will receive the coordinate pairs in step 202. These coordinate pairs are grouped into hourly datasets and the centroid of each reservoir hourly is calculated in step 204. A centroid spanning the entire 24 hours is then calculated in step 206 and the distance of the centroid per hour is compared to the centroid for the entire 24 hours. This is done to see what the hourly centroid of the tag is assigned to the stored acceptable distance threshold. Thus, a threshold distance is determined based on the comparison in step 208. For example, the threshold distance is just large enough that all hourly centroids fall within the region defined by the threshold distance from the 24 hour centroid. A margin may be added to the threshold distance.

Fig. 3 illustrates a method for assigning assets to a room. In use, the location of each tag is received in step 302 and the hourly centroid for each tag is calculated in step 304. The hourly centroid is compared to the centroids of the plurality of reservoirs by calculating the distance of the centroids of the plurality of reservoirs from the hourly centroid in step 306. Each reservoir is represented as a long term (24 hours in this example) centroid location determined in the fingerprinting step.

In step 308, if the distance is small enough for a particular storage room (i.e., below the threshold distance calculated in fingerprinting step 200), then the asset is assigned to that storage room in step 310 for that hour.

A variation of the hourly centroid method uses a sliding window to allow finer granularity to be achieved from the resolution of Wi-Fi reports. The sliding window method is similar to the concept of determining a moving average of position data. The centroid is determined using a set of position data at a first time and, when a new pair of position coordinates is available, using a new set of position data, wherein the new set of position data is a set of previous position data that is "shifted forward" in time to include the new pair of position coordinates while remaining the same size as the previous set.

The resolution of Wi-Fi reporting is the resolution with respect to time. It is typically a user-adjustable feature that instructs Wi-Fi RTLS to provide the frequency of location updates. However, resolution directly affects battery life. It was found that time resolution much shorter than five minutes resulted in reduced battery life, making Wi-Fi RTLS impractical even though they provided finer granularity.

The challenge in using an hourly centroid to represent asset location is that any movement away from the storage chamber will only be detected when the next hourly centroid reports. This will produce a distortion result that does not reflect reality. In particular, despite such asset movement, the asset is not tracked as being in use until the next updated location report is pending.

The sliding window approach mentioned above addresses this limitation. Centroid is created every T minutes, where T is the time resolution (and shorter than the hour period) of Wi-Fi system. Once the asset moves out of the storage room, a new location will be reported within T minutes, and this will result in the average centroid location for the previous hour moving out of the range of locations attributed to the storage room. Thus, movement from the reservoir can be detected within T minutes even if the position is an average of 1 hour.

In some cases, the next report may not immediately identify the room change. However, the sliding window method provides a method of identifying movement more likely earlier than calculating the centroid only every hour. Additionally, in calculating the utilization of the asset, the delay in identifying the removal of the asset from the storage room may be offset by the delay in identifying the return of the asset to the storage room.

For example, if the Wi-Fi system reports once every 5 minutes and the entire desired period of time (1 hour in this example) involves creating multiple centroids, the centroids are caused to be calculated as follows:

Where i is a count indicating the coordinate pair at time t, cx _i,t is the X-coordinate of the centroid at time t, cy _i,t is the Y-coordinate of the centroid at time t, and a is the number of steps in the past you want to see. In this example, a would be equal to 12 (i.e., divided at 5 minute intervals every 60 minutes per hour).

Thus, the centroid still includes one hour of data while providing an updated centroid every 5 minutes. This increases the rate of centroid updates. Although there may be a delay between the asset leaving the storage room and the asset not being assigned to the storage room due to the sliding window approach, there may be a similar delay when the asset returns to the storage room. Thus, the two delays can cancel each other out and the percentage of time the asset is in the storage room is not significantly affected.

The method of assigning assets to rooms may be used in a particular department or in an entire organization, e.g., a hospital radiology department, an entire hospital, an office building, etc.

The proposed method provides a technique that uses X-coordinate and Y-coordinate reports of Wi-Fi based RTLS propagated over time to better estimate the time an asset spends in a storage room.

In the above example, there is a single position obtained from a 24 hour period (first period), an hourly position (second period) where a threshold distance can be determined, and a5 minute sliding window (third period) for the tag position. However, these are merely examples.

More generally, any suitable first time period may be used for the plurality of fingerprint-identified locations to obtain a first representative location, and any suitable shorter second time period may be used to obtain a second representative location from which a threshold distance is determined. The tag location, i.e., the current representative location, may be received at a rate corresponding to any desired third time period that is shorter than the second time period.

The first representative location, the second representative location, and/or the current representative location may be calculated by calculating an average, median, centroid, time-weighted average, etc. of the corresponding locations.

The range of locations attributable to the room may be determined by determining an area (e.g., a circle having a radius of a threshold distance) around the first representative location. Alternatively, the location range may be an area that includes the entire area within the room and additional areas outside the room (e.g., additional distances from the edge of the room equal to a threshold distance or a percentage thereof). In some cases, the location range may be a circle with a radius around the physical center of the room at a threshold distance (or a multiple/fraction thereof).

If the location range is a circle having a radius r (where r depends on the threshold distance) from a particular location (e.g., the first representative location), comparing the current representative location to the location range may include: the difference between the current representative location and the particular location is determined and the difference is compared to the radius. Other methods (e.g., using a search table that includes all locations within a range of locations) may also be used.

The location ranges may be for all assets in the room, or different areas may be for different assets. This is because different assets can be placed consistently in different parts of a room.

The room may be a storage room or any other type of room. For example, the room may be an operating room or an emergency room. Thus, assigning assets to these rooms can provide information about who most commonly uses the assets and where most commonly use the assets. This information may further inform the user where it is preferable to store particular assets so that they are near where they are most commonly used.

The first period of time may be, for example, 4 hours, 10 hours, 24 hours, days or possibly even a week. Of course, the longer the first period of time, the more accurate the first representative location.

The second period of time may be, for example, 30 minutes, 1 hour, 2 hours, 4 hours, or may even be an entire day, as long as it is shorter than the first period of time. The second time period should be at least half of the first time period such that at least two second representative locations may be determined within the first time period.

The threshold distance may be based on a modulus of the difference between the average value of the second representative location and the first representative location or a multiple/fraction thereof. The particular method for determining the threshold distance using the first representative location and the second representative location may depend on particular accuracy requirements or personal preferences of the user. For example, if two tracked rooms are relatively close to each other, they may require a relatively small threshold distance such that an asset cannot be assigned to both rooms at the same time. The same reasoning can also be applied for the determination of a location range, wherein the exact range and/or shape of the range can depend on the specific needs of the user and the nearby environment (e.g. the nearby tracked room).

Because of the inherent inaccuracy of the positioning system, an asset may be determined to be in a storage room when the asset is actually being used in an adjacent room. This situation can be detected using time analysis. For example, if an asset appears to be in the storage room area only for a short period of time between longer periods of time in adjacent rooms, this may be ignored if the shorter period of time is less than the threshold time taken to move the asset into and out of the storage room. This means that the asset simply looks in the storage room due to inaccuracy of the positioning system. Thus, time analysis may improve the accuracy of whether an asset is assigned to a storage room or not.

The skilled person will be able to readily develop a processor for performing any of the methods described herein. Accordingly, each step of the flowchart may represent a different action performed by the processor and may be performed by a corresponding module of the processor.

As described above, the system performs data processing with a processor. The processor may be implemented in a number of ways by software and/or hardware to perform the various functions required. A processor typically employs one or more microprocessors that may be programmed using software (e.g., microcode) to perform the required functions. A processor may be implemented as a combination of dedicated hardware for performing some functions and one or more programmed microprocessors and associated circuitry for performing other functions.

Examples of circuitry that may be employed in various embodiments of the present disclosure include, but are not limited to, conventional microprocessors, application Specific Integrated Circuits (ASICs), and Field Programmable Gate Arrays (FPGAs).

In various implementations, the processor may be associated with one or more storage media, such as volatile and non-volatile computer memory, e.g., RAM, PROM, EPROM and EEPROM. The storage medium may be encoded with one or more programs that, when executed on one or more processors and/or controllers, perform the required functions. Various storage media may be fixed within a processor or controller or may be transportable such that the one or more programs stored thereon can be loaded into a processor.

Variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality.

The functions implemented by a processor may be implemented by a single processor or by a plurality of separate processing units that together may be considered to constitute a "processor". In some cases, such processing units may be remote from each other and communicate with each other in a wired or wireless manner.

The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

A computer program may be stored/distributed on a suitable medium, such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems.

If the term "adapted to" is used in the claims or specification, it should be noted that the term "adapted to" is intended to be equivalent to the term "configured as (configured to)". If the term "arrangement" is used in the claims or the specification, it should be noted that the term "arrangement" is intended to be equivalent to the term "system", and vice versa.

Any reference signs in the claims shall not be construed as limiting the scope.

Claims

1. A method for assigning assets to rooms in a medical environment, the method using a Wi-Fi based real-time location system to determine the location of tags, the method comprising:

-fingerprinting (200) a room, wherein the fingerprinting comprises:

Receiving (202) a plurality of fingerprint identification locations over a first period of time from a plurality of tags placed throughout the room;

-calculating (206) a first representative location from the fingerprint-identified locations within the first time period;

Computing (204) a second set of representative locations from the fingerprint-identified locations over a plurality of shorter second time periods; and

Determining (208) a threshold distance for the room by comparing the first representative location to the set of second representative locations;

Receiving (302) a plurality of locations of tags placed on the asset;

calculating (304) a current representative location from the plurality of locations;

comparing (308) the current representative location with a range of locations attributable to the room, wherein the range of locations is determined using the threshold distance; and

The asset is assigned (310) to the room in response to the current representative location being within the range of locations attributable to the room.

2. The method of claim 1, wherein the first and/or second representative locations are centroids of corresponding fingerprinted locations.

3. The method of claim 1 or 2, wherein the current representative location is a centroid of a corresponding plurality of locations.

4. A method according to any one of claims 1 to 3, wherein comparing the current representative location with a range of locations attributable to the room comprises: a distance between the current representative location and the first representative location is calculated (306), wherein the asset is assigned to the room if the calculated distance is less than the threshold distance.

5. The method of any one of claims 1 to 4, wherein the room is a storage room for storing the asset.

6. The method of claim 5, further comprising: utilization of the asset over a time horizon is calculated by determining a percentage of time the asset spends in the storage room over the time horizon.

7. The method of any of claims 1-6, wherein a current representative location is calculated every third time period, wherein the third time period is a time resolution of the Wi-Fi based real-time positioning system.

8. A computer program product comprising computer program code which, when executed on a computing device having a processing system, causes the processing system to perform all the steps of the method according to any one of claims 1 to 7.

9. A system for assigning assets to rooms in a medical environment, the system using a Wi-Fi based real-time location system to determine the location of tags, the system comprising a processor configured to:

-fingerprinting (200) a room, wherein the processor is configured to fingerprint by:

Receiving (302) a plurality of locations of tags placed on the asset;

10. The system of claim 9, wherein the first and/or second representative locations are centroids of corresponding fingerprinted locations.

11. The system of any of claims 9 or 10, wherein the current representative location is a centroid of a corresponding location.

12. The system of any of claims 9 to 11, wherein the processor is configured to: -comparing (306) the current representative location with a range of locations attributable to the room by calculating a distance between the current representative location and the first representative location, wherein the asset is assigned to the room if the calculated distance is less than the threshold distance.

13. The system of any of claims 9 to 12, wherein the room is a storage room for storing the asset.

14. The system of claim 13, wherein the processor is further configured to: utilization of the asset over a time horizon is calculated by determining a percentage of time the asset spends in the storage room over the time horizon.

15. The system of any of claims 9 to 14, wherein a current representative location is calculated every third time period, wherein the third time period is a time resolution of the Wi-Fi based real-time positioning system.