Indoor Mobile Position Monitoring Model with iBeacon/Raspberry Pi 1 ― Overview

Information

Our indoor positioning system TPC_IPS Ver1.0 was released on April 1, 2022.

We also plan to release IPS application templates "QuickIPS" and "TPC_IPS Web API" which allow interactions with external IPSs/RTLSs in the future.

This post describes "The Indoor Mobile Position Monitoring Model" that Raspberry Pi terminals (hereinafter referred to as "terminals" or "monitoring terminals") scan beacons and calculate the positions of the beacons. This model has various names including "Indoor Positioning System," "Asset Management System," " Indoor Location (Tracking) System," "Indoor Positioning System (IPS)," "Asset Tracking System," "Real-time Location System(RTLS) ," and so on, depending on vendors and system purposes. This blog mainly uses IPS as a term to describe this model.

Related posts (in Japanese) on Fixed Beacons Monitoring Models:

Table of Contents

Submodels
1. [Memo] Drone Flight Control Model
System Overview

Trilateration
Things to Consider

RSSI Accuracy
Problems of Trilateration

Improvements Since April 2018 and IPS Market Trends

Positioning Methods
BLE5.1 AoA/AoD
UWB

IPS Related Blog Posts

Submodels

　The system model for mobile positioning can be divided into submodels depending on their required attributes.

Request attribute	Attribute description	value
Number of positioning targets	Whether there are many or few positioning targets	Few \| Many
Movement frequency	Movement frequency of positioning target	High frequency \| Low frequency
Moving Speed	Moving speed of positioning target	High speed ｜ Low speed
Positioning accuracy	Required positioning accuracy	High precision \| Low precision
Real-time	Time from positioning request to actual positioning	Real-time \| Non-real-time * 1
Positioning target	Things to be positioned	Beacons ｜ Mobile terminals
App device	Device for displaying positioning results	Management terminals ｜ Mobile terminals * 2

* 1: Non-real time allows a time difference of up to about one minute.
* 2: Management terminals can be mainly PCs and mobile phones.

The submodels include the following scenarios:

Displays the player's own position and other players' positions on the player's smartphone in indoor games.
Attributes: Few | High frequency | Fast | High precision | Real-time | Mobile terminals | Mobile terminals -> Indoor GPS model
Displays the positions of players on the PC and the like in indoor sports such as hockey.
Attributes: Many ｜ High frequency ｜ High speed ｜ High accuracy ｜ Real-time ｜ Beacons ｜ Mobile terminal -> Hockey model (Video of Quuppa, Finland)
Staff grasp the positions of patients and residents in hospitals and nursing homes.
Attributes: Many | High frequency | Low speed | Low accuracy | Non real-time | Beacons | Management terminasl -> Hospital model
Manags the positions of products in factory assembly lines.
Attributes: Many | High frequency | Low speed | Low precision | Non real-time | Beacons | Management terminals -> Factory process model
Detects the positions of products in warehouses and storage.
Attributes: Many | Low frequency | Low speed | Non real-time | Beacons | Management terminals -> Warehouse model

IPS specifications and operation methods also vary depending on the submodel. Our TPC_IPS under development targets the above 3 to 5 submodels.

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[Memo] Drone Flight Control Model

　 A lot of drones on the market are equipped with GPS to track their positions of themselves outdoors; however, GPS does not work indoors, near buildings, valleys, etc. where GPS signal reception is poor or unavailable. In such cases, using an IPS can be an option to track the positions of drones and control the flight. This allows program-controlled drones to transport goods, patrol and take photographs in unmanned buildings and factories late at night.

However, IPS using iBeacons (BLE4 beacons) may cause huge positioning gaps of 1 meter or more, so it would be difficult to control drones in offices.
In this respect, a system using BLE5.1AoA compatible beacons or Ultra Wide Band (UWB) tags will be more effective because the positioning gap can be narrowed down to 1 m to 10 cm.

When applying an IPS, it is important to determine how much positioning accuracy the system can achieve.

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System overview

The figure below shows a example that divides the area to be monitored into grids, places monitoring terminals (Raspberry Pi's, painted in pink in the figure) at the corner of each grid, and scans the beacon signals in the area. The blue marks in the figure describes beacons. These beacons are attached to mobile objects such as things and people. The distance between the Raspberry Pi's, that is, the length of the sides of each grid, should be smaller in places with many obstacles and people, or in environments where high positioning accuracy is required. On the contrary, the distance could be larger in places where there are few obstacles and people, or in environments where positioning accuracy is not important, and the number of terminals can be reduced.

[Fig. 1: Arrangement of Raspberry Pi monitoring terminals]

It is often impossible to place monitoring terminals in grids in a production environment.

Each Raspberry Pi keeps receiving beacon signals and sending the information to the application server; the server performs trilateration and calculates the position of each beacon based on the collected data.

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Trilateration

There are multiple methods for calculating the positions of beacons, and we use trilateration this time.
All monitoring terminals (Raspberry Pi1 to Pi16) in Figure 1 are constantly reading (scanning) the beacon signals. Beacon signals have the strongest strength when they are issued; however, they will be attenuated according to the distance as they propagate through space. Since each Pi obtains the signal strengths and RSSI (Received Signal Strength Indication), the distance between the beacon and the terminal (Pi) is calculated from the degree of attenuation of the RSSI.

In the "Before" section of the figure below, there are circles centered on the terminals Pi2, Pi5, and Pi6, and the radius of each circle is the distance to the beacon. Trilateration estimates that the position of the beacon is at the point where the circles Intersect, or in the center of the area where those three circles overlap. Terminals other than Pi2, Pi5, and Pi6 also detect this beacon; however, Pi2, Pi5, and Pi6 are the closest three terminals so the accuracy will be higher. Therefore, trilateration is performed based on these three circles.

Next, suppose this beacon moves to the "After" position. Due to the movement, the terminals with the shortest distance are Pi12, Pi15, and Pi16. At this time, trilateration is performed using the circles of these closest terminals (distance between the terminals and the beacon).

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Things to consider

At first glance, the positions of beacons seems to be easy to identify, but it is difficult to achieve the desirable results. The reasons are as follows:

RSSI accuracy

RSSI can measure the distance with reasonable accuracy when the distance between the terminal and the beacon is several tens of centimeters, but if it exceeds 1m, it is strongly affected by multipath (multipath propagation) or other factors, and the signals will not be attenuated as officially stated. It happens very often that the distances calculated based on RSSI are far from the actual distances.

Problems of Trilateration

As mentioned above, the distance based on RSSI is unreliable. Also, trilateration often fails since three circles do not intersect as expected. In such a case, alternative positioning methods should be applied instead of concluding it as a trilateration error.

In the next post, we will actually measure RSSI and consider the calculated distance error between the terminal and the beacon in question, and the difference from the actual distance. In addition, we will also describe our original RSSI/distance calibration method and the expansion of trilateration.

Improvements since April 2018 and IPS market trends

　This post was originally published in April 2018, and since then new products and technologies have been released. We also keep developing and testing new methods. Here are some pieces of information to share before closing up this post:

Positioning method

The next post (published on August 9, 2018) and the next post (published on July 12, 2019) describe the results of developing, testing, and verifying a prototype for RSSI, distance calibration, and trilateration. However, the positioning accuracy of trilateration based on RSSI And RSSI has its limit. In this respect, positioning using machine learning can improve the positioning accuraty compared to trilateration, although machine learning requires additional time and effort for learning. We also posted an article on December 26, 2020, regarding the positioning accuracy by machine learning, after creating a prototype system, testing and verifying it.

BLE5.1 AoA / AoD

Specifications Of BLE5.1 The AoA / AoD were announced in January 2019. This makes it possible for BLE5.1 compatible terminals (sensors) to acquire the direction (angle) where the beacon exists, in addition to the distance of the beacon itself. It is expected that the positioning accuracy will be narrowed down to 1m or less. However, even though more than two years have passed after the specifications were released, major vendors have not yet released BLE5.1 compatible transmitters and receivers (sensors).

UWB

At the end of April 2021, Apple released AirTag. iPhone 11/12 can can now perform AirTag positioning with high accuracy. The technology used for this positioning is called UWB, which is said to be capable of positioning with an error of 10cm. IPS's using UWB such as Ubisense and Zebra have been on the market for quite some time and have been having high reputations, however, they are quite expensive. Overseas IT-related media call AirTag "Game Changer," and it is expected that new IPS's using UWB will appear on the market in the near future.

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IPS Related Blog Posts

* indicates that original article translation into English has been completed by TPC.
"Google translate" indicates that clicking it will Google translate the original article, and may be translated into English in the near future by TPC.

TPC's IPS Products

IPS Application Templates for FileMaker ― QuickIPS ―

Information

Table Of Contents

What is IPS?
IPS User Application with FileMaker
Integrating QuickIPS with An External System

locLog Table Structure
Importing Data from an External Database into QuickIPS locLog Table

About Customizing QuickIPS
IPS Related Blog Posts

What is IPS?

We have been developing a system called TPC_IPS. In a nutshell, IPS (Indoor Positioning System) can be described as an indoor GPS; a system that grasps the positions of people and things indoors. If the environment is indoors or underground, positioning is impossible with satellite technology like GPS, and positioning accuracy will not be satisfactory, so IPS performs indoor positioning. IPS is also one of the IoT (Internet Of Things) technologies.

[IPS/Asset Tracking System Overview]

The image above is an overview of IPS in a warehouse. Transmitters called beacons or tags are attached to people or things, the receiving terminals () read the signals () emitted by those beacons, and finally the computer analyzes the signal information in order to measure the positions of individual beacons. This positioning information can be referenced by internal or external users via the LAN/WAN. Such an IPS that administers many things as shown in the image below is sometimes called an Asset Tracking system.

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IPS User Application with FileMaker

The following figure is an IPS configuration example. In this example, the IPS is divided into two subsystems: Positioning and User Application. Positioning literally calculates the coordinates of individual beacons. As of May 2021, our product TPC_IPS, uses BLE4 beacons for positioning; however, UWB which was recently adopted by AirTag is gaining attention. USB products for IPS/Asset Tracking which are not limited to mere lost-and-found tags are expected to appear on the market in the upcoming years.

Note:
UWB IPS products such as Ubisense and Zebra have been available from some time ago, however, only some large companies have adopted them because they are quite expensive. The advent of AirTag and SmartTag may contribute to the widespread adoption of low-cost UWB IPS.

We have already posted the positioning using TPC_IPS before (see the link at the end), so in this article we are going to give you an overview of our -QuickIPS- user application template using FileMaker.

Note:
QuickIPS will be bundled with TPC_IPS. The standalone version will be released later this year.
* QuickIPS specifications and schedule are subject to change without notice.

[IPS configuration diagram]

Note:
The above diagram shows how a server computer performs positioning of beacons and tags attached to objects. This method is used for Asset Tracking (or Asset Management). Another way to achieve indoor positioning in a more GPS-like fashion is for a mobile app (device) to track its own position within a grid of fixed beacons and tags.

Typical User Applications

The previous diagram describes the flow that each beacon or tag sends its information to the server computer, the server computer calculates the location information based on the collected information, and the database stores the result location information along with the beacon IDs (or tag IDs).
Furthermore, the user application accesses the location data in the database to process the data according to user's preferences, and display the results on the computer or the smartphone. The following are three typical user applications.

Floor map - displays the positions of people and things on a floor map
Heatmap - displays the degree of congestion of people
Motion tracking - represents the consecutive movements of a person or a thing as a line

Of these, 1 and 2 can be developed in FileMaker alone. QuickIPS is a user-customizable template that implements these two.

The object tracking feature will be included in future versions of QuickIPS and TPC_IPS. Please read this post in out blog for more information on object tracking.

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QuickIPS Demo Video

Here is an 11 minute QuickIPS overview video.
Turn on CC to see English subtitles.

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Why FileMaker?

The reason is simple. FileMaker requires less man-hours than other tools to create a graphical application. FileMaker is also suitable for prototyping IPS user applications. The following is a detailed introduction to the QuickIPS features.

Floor Map Using Scatter Graph

The figure below is a floor map that displays the beacon positions using FileMaker's scatter graph feature. A map (an image file) for plotting location information is imported in the background of the FileMaker layout in advance, and a scatter graph is placed over the map.
The advantages of this method are rounding coordinates data (described later) is not required, and it is easy to create; however, this map also has disadvantages such as the beacon names may overlap when multiple beacons are detected in close proximity, and detailed beacon information cannot be desplayed.

The beacon names overlap when multiple beacons are detected.

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Floor Map Using Objects

In this method, SVG spot icons () and beacon information objects are placed at the coordinates (fixed point coordinates) predetermined by the user, whereas the information of the positioned beacon is displayed by these beacon information objects.

Unlike the scatter graph method, you can fine-tune this feature; multiple beacons on the same coordinates can be displayed, while those beacons which positions are different from the actual coordinates can be displayed in red, and the display font size can also be changed (using ◀ A ▶).

"Rounding" of Position Coordinates With an External System

TPC_IPS's Positioning feature can calculate the beacon coordinates by rounding the measured coordinates to the fixed point coordinates.
However, if you wish to use QuickIPS with an external system, you need to do this rounding on the external system.

Example:
You have set the fixed point coordinates ( x ) as shown in the figure below. Then, the external system detects the beacons as follows. The x and y coordinates are shown in parentheses.

Beacon A (0.2, 1.1)
Beacon B (3.2, 3.6)
Beacon C (1.5, 2.1)

Suppose the closest fixed point coordinates (x) to each positioning coordinate are determined as the coordinate of each beacon (this is the rounding process). In this example, beacon A (0.2, 1.1) is rounded to the fixed point coordinate (1,1), beacon B (3.2, 3.6) is rounded to (3, 3), and beacon C (1.5, 2.1) is rounded to (2, 2) respectively.

Note:
You may code your own program to find the closest fixed point coordinates (the nearest neighbor points), but if you can use K-nearest neighbor (k = 1) libraries, you can achieve it quite easily. It may be possible to create a knn custom function in FileMaker and apply it to the rounding process when retrieving data from an external database, however, it will be quite difficult.
Even that famous Brian Dunning's custom function publishing site has not shared any knn custom functions so far.
TCOT (Two-Circle Oriented Trilateration), the positioning algorithm in TPC_IPS, calculates the coordinates with a trilaterational approach, so that the raw positioning coordinates do not almost always match the fixed point coordinates. For this reason, when executing TCOT, KNeighbors of scikit-learn provides an option to round to fixed point coordinates.

By nature of trilaterational approaches, there is a certain degree of errors from the fixed point coordinates. To correct such deviations, we provide an option to use the KNeighbors algorithm of scikit-learn to round coordinates to the closest fixed coordinates during the TCOT process.

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Heatmap Using Objects

Heatmap displays the state of many people and things in the same place in different colors. Heatmap also requires rounding position coordinates.

The density of people and things is displayed in the order of blue, yellow, and red.

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Error Graph

Error graph displays the errors between the actual coordinates of the beacons in a stationary state and the positioning coordinates as a line graph. This feature is useful for positioning system engineers to check the accuracy of positioning.

The horizontal axis is the scanning time, the vertical axis is the error; the smaller the error value, the higher the positioning accuracy.

When the beacons to be displayed on the graph is selected from the picker floating window (described later), the positioning error is displayed on the vertical axis within the time range specified by [Time].

During the test before operating an IPS, this feature becomes useful for checking whether the positioning accuracy that suffices the operation. In addition, the accuracy of positioning varies due to changes in the indoor environment, so use this feature in a timely manner to check the positioning accuracy.

Note:
When the automatic update button ● is running in AUTO mode, or the update button is clicked in MANUAL mode, the error graph is updated with the latest positioning information.

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About The Basic Operation of QuickIPS

This section explains basic operations of QuickIPS.

Three modes: AUTO, MANUAL and HISTORY

QuickIPS has three operational modes: AUTO, MANUAL, and HISTORY. Each mode is selected from the pull-down menu by clicking "Execution mode" in the figure below.

AUTO Mode

● button will be displayed in the upper right corner of the screen. Click it to automatically update the Floor map, Heatmap, and Error graph with the latest data. Click ■ to stop automatic update.

MANUAL Mode

This mode, unlike AUTO mode, does not update the information automatically. To update with the latest information, click displayed in the upper right corner of the screen.

HISTORY Mode

In this mode, Floor map, Heatmap, and Error graphs can be displayed based on the past coordinate data.

Header Part

This section explains how to use the header part at the top of the screen.

Submenu button	Click to display the pop-up menu. Select from the following menu items: Scatter map (floor map using scatter graph) Floor map (floor map using objects) Heatmap Error graph (distance error graph)
Execution mode	Select from AUTO, MANUAL, and HISTORY described earlier.
Time	Specify the range of ScanCode (date and time when the scan was executed in YYMMDDMMDDSS format). Note: ScanCode is automatically generated by TPC_IPS.
ScanCode navigation	Buttons for moving/selecting between ScanCodes within the range specified in [Time] \| <: Move to first >: Move to next <: Move to previous > \|: Move to last
Picker button	Display a picker/floating window (described later) for selecting the target beacon and ScanCode.
Error summary button	Display the error summary floating window (described later) that displays the details of the positioning error.

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Picker Floating Window

This window is used for selecting the target beacon(s) and ScanCode in the Floor map, Heatmap, and Error graph. This window is always in the foreground until it is closed with the x button.

Beacon list	List of beacons. Click to select or deselect. The selected beacons are displayed in pink. The selected beacons will be displayed on the Floor map. Up to six beacons can be displayed in the Error Graph.
Beacon name format	Click to switch the format of the beacon name displayed on the floor map. Name: Display only beacon name MM/Name: Display Major-Minor and beacon name
All button	Select all beacons
None button	Deselect all beacons
ScanCode list	A list of ScanCodes within the range specified by [Time]. Click to select and the floor map and heatmap will be displayed based on the coordinate data with that ScanCode.

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Error Summary Floating Window

The error summary floating window displays a summary of the positioning errors of the selected beacon(s) from the picker floating window. The line chart of the error graph can display up to 6 beacons at a time, but there is no limit to the number of beacons that can be selected in this summary.
This window is always in the foreground until it is closed with the x button.

Positioning error summary	The positioning error of the beacons in the stationary state is displayed for each beacon. Displays the average, maximum, minimum, and standard deviation of the positioning error of the beacon selected from the beacon list. The last line shows the aggregated value of all selected beacons. The aggregation target is the time range specified in [Time].
Error type	The buttons for selecting the type of error and the error calculation formula when each button is selected are as follows: Distance: Sqrt((ax - ex)^2 + (ay - ey)^2) Coordinates: Abs(ax - ex) + Abs(ay - ey) Note: ・ ax, ay: feal coordinate x, y ・ ex, ey: positioning coordinate x, y

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Use on iPhone/iPad

Two types of Floor maps, Heatmap, and Error graph features are also available on iPhone/iPad (iOS). These screens use the same screens as those for PCs, so that cost-effective development will be possible.

QuickIPS on iPhone

You need to take an extra care on PC/iOS representation when developing an IPS application

Integrating QuickIPS With an External System

QuickIPS has a table called locLog that stores coordinates data; the data in locLog is retrieved and processed for the QuickIPS features described earlier.
If the database on the external system has a table or view that is compatible with locLog, then the data can be imported into locLog table for QuickIPS.

locLog Table Structure

When using QuickIPS with an external database other than TPC_IPS, create a table based on the QuickIPS locLog table schema.

Field name	Data type	Input	Remarks
uuid	text	Mandatory	Beacon uuid
major	numeric	Mandatory	Major assigned to the beacon
minor	numeric	Mandatory	Minor assigned to the beacon
beaconName	text		Beacon name, required for displaying beacon information
x	numeric	Mandatory	X coordinate of the positioned beacon
y	numeric	Mandatory	The y coordinate of the positioned beacon
actual_x	numeric		The actual x coordinate of the beacon [Note 1]
actual_y	numeric		The actual y coordinate of the beacon [Note 1]
scanCode	numeric	Mandatory	12-digit number representing the scan time stamp (YYMMDDHHMMSS) [Note 2]
timestamp	timestamp		Date and time the record was created

Note:

actual_x and actual_y are the coordinates of the actual beacon used during the positioning accuracy test. The positioning error is calculated using these values and the measured coordinate values.
When using QuickIPS, a scanCode generated for each scan is required. When generating scanCode on an external system, make sure that each sensor executes the scan at the same timing, and set the same value (YYMMDDHHMMSS) to scanCode for each scan. For example, when the beacon/tag signal is scanned at 2022/1/1 0:0:0, "220101000000" is stored to the scanCode of each record on the server etc. regardless of the clock of the sensor/receiver.

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Importing Data From an External Database into QuickIPS locLog Table

The external table data as described above can be imported into QuickIPS locLog table in the following manner:

Register the given DSN with the ODBC driver for the external database on the computer running QuickIPS
Specify the table name to be fetched and the field names of the external table corresponding to the locLog table.
Perform data import using External Data Import screen

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About Customizing QuickIPS

The floor map using objects mentioned earlier can be customized as described in the figure below.
SVG spot icons and the beacon information objects (painted in pink in the figure for visibility, but they are actually transparent) have coordinate attributes respectively, so they need to be placed according to the coordinate attributes. For example, the object of the coordinate (2, 8) needs to be placed at coordinate (2, 8) on the floor map.

When creating a floor map for a large facility, the floor map image needs to be splitted, so that those floor map images will be imported on the newly created multiple layouts, tabs, and slides respectively.

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QuickIPS will be released separately from TPC_IPS as a FileMaker template.
* QuickIPS specifications and schedule are subject to change without notice.

NuckyT

IPS Related Blog Posts

* indicates that original article translation into English has been completed by TPC.
"Google translate" indicates that clicking it will Google translate the original article, and may be translated into English in the near future by TPC.

Menu bar

TPC's IPS Products

QuickIPS Demo Video

AUTO Mode

MANUAL Mode

HISTORY Mode

TPC's IPS Products