Bluetooth RSSI Measurement for Indoor Positioning

There’s a research paper by researchers from Taiwan on A practice of BLE RSSI measurement for indoor positioning. The paper looks into received signal strength (RSSI) to distance conversion, the significance of antenna plane (orientation) and measurements in two different situations, a low noise classroom and a more noisy manufacturing site workshop.

Techniques employed included developing a signal propagation model, trilateration, modification coefficients and Kalman filtering.

The hardware used included an Arduino Nano 33 (Bluetooth 5) and Linkit 7697 (Bluetooth 4.2). Over 1.6 million samples were collected generating over 13Mb of data.

“Multiple factors affected the RSSI, such as the device performance, antenna direction and radio wave refraction”

A positional accuracy of 10cm was achieved in ideal conditions dropping to meter level accuracy in more challenging setups and environments. The sensitivity of the (ceramic) antenna was found to fluctuate widely with orientation/topology. The researchers concluded that the key factor for reliable indoor positioning, based on RSSI, is maintaining good signal measurement quality.

Choosing a Real Time Locating System (RTLS)

A Real-time locating system (RTLS) automatically tracks the location of objects or people. Beacons, sometimes called tags, are placed on things that move and gateways, sometimes called locators, detect the beacons and send data to software either locally or in the cloud. A user interface shows the current locations.

Most organisations looking for a RTLS for the first time don’t know what aspects of systems are most important. People usually focus on maximum accuracy when, in fact, a system with maximum accuracy involves consequent undesirable compromises. Some suppliers’ marketing also focuses on performance that’s only achievable in a lab or factors that might seem important now but will become less important when other issues are known. In practice, every situation is different and you need to balance factors based on your needs.

Number of Assets

The number of assets you need to track usually has largest influence on the type of system you should consider. All systems are limited by how much data they can process. More accurate systems such as Ultra-Wideband (UWB) and Bluetooth AoA produce more data and hence support a lower maximum number of assets. However, the actual number depends on many factors such as the underlying hardware speed, the network speed (i.e. is local or in the cloud) and settings within the RTLS system itself.


When talking to vendors, it’s important they assess the number assets you will need in the future, as well as now, so as to not outgrow a system. Scalability isn’t only about assets. It also involves the number of gateways, the degree to which they overlap physical areas, thus producing more data for more accuracy, and the scalability of subsequent processing software.


The use of RTLS is much like the Internet of Things (IoT) in that everyone wants to get something slightly different out of the data. If you require something other than searching for assets, this means you or your vendor will need to write reports, scripts or use reporting tools such as Grafana to extract insights. The RTLS should have an API, usually using HTTP REST, to extract data. If you have local access to the system, it’s often more flexible and faster if you can also gain direct access to the underlying database for reporting. This also opens up the number of off-the-self reporting tools that can be used.

Most systems have a user interface where you can add and remove beacons and gateways. However, imagine doing this for 1000s of assets. Look for an API to allow you to add, modify and view beacons and gateways programmatically. This allows other programs such as apps, ERP, WMS, your custom systems and scripts to simplify integration.


In reality, systems tend to get re-used for more than one use case as the organisation’s digital maturity grows. Check the system provides suitable access to the data for future uses. Ensure various beacon models are available for those anticipated uses.


As previously mentioned, the best accuracy isn’t always the top consideration. Our article on microlocation accuracy explains the different kinds of system and corresponding accuracy. Note also, that many RTLS have settings that balance accuracy with latency and maximum number of assets.


Latency is how long it takes to know a new location after something has moved. A shorter latency requires the assets to send data more often thus decreasing asset battery life. More data also implies a fewer maximum number of beacons.

Battery Life

As mentioned, above, the frequency of beacons advertising their location directly impacts beacon battery life. Systems such as UWB and Bluetooth AoA tend to have beacons advertising more often to allow higher accuracy. However, look for beacons that have accelerometers that advertise more often only when moving thus saving battery life.

License Type

Consider if you need a system locally, in the vendor’s cloud or your own cloud. For thousands of assets, reporting frequently for low latency, you will need the system to be local. If you are using SaaS you will also need to consider issues such as the service level agreement (SLA) and the location of the server for privacy requirements such as GDPR. Another issue related to SaaS, particularly with VC start-ups, is the longevity of the solution. Is the vendor going to be providing the platform as long as your project? Some early beacon platforms have already closed. Others have been taken over by large companies that have other agendas.


You need to assess the security of the proposed system. This includes factors such as logins, SSL, secure APIs and the security related to the location/hosting of system.


As well as the headline price, also consider if the solution is financially scalable once you increase the number of assets and gateways. Also determine if future costs are known and acceptable.


Remember that the ‘best’ RTLS is not the one the vendor claims as best for some arbitrary feature but instead is the one that best suits your needs. You will need to balance the needs of the project with the capability of the RTLS that offers the best fit.

Cisco and Aruba Based Real Time Location Systems (RTLS)

A growing number of WiFi access point vendors such as Cisco and Aruba are offering Real Time Location Systems (RTLS). While using existing hardware might seem compelling, it’s sometimes not practical. Here are some questions to be answered when considering such systems:

  • Does your site have access points from mixed vendors? If so, the RTLS won’t work across them.
  • Does your site have enough (overlapping) access points to support the RTLS?
  • What will be the latency? Hardware providing WiFi access point functionality and Bluetooth scanning can’t provide optimal throughput leading to much lower latency to find items typically in minutes rather than seconds.
  • What is the location technology? Access point systems use RSSI based locating rather than angle of arrival (AoA) that’s typically accurate to 5m rather than sub 1m. They also don’t provide the the breadth of IoT sensing provided by dedicated-hardware RTLS systems.
  • What is the maximum number of assets? Non-dedicated hardware doing the scanning for beacons severely reduces throughput and hence the maximum possible number of assets.
  • Is it SaaS? Are the future subscription costs known? What is the SLA? Where is the server? Does it meet regulatory and your company privacy needs? Does it scale financially with the number of assets? Is the SaaS platform likely to be around as long as your project needs?
  • What is the vendor competency? Many Aruba and Cisco resellers are more interested and experienced in selling hardware rather than solving RTLS and Bluetooth related problems.

Read about BeaconRTLS™

Read about PrecisionRTLS™

Using RTLS to Determine Human Behaviours

Our BeaconRTLS™ and PrecisionRTLS™ produce a lot of historical data. How this data is used varies considerably from project to project. One use of the data is for determining human behaviour. For example, consumer behaviour, workplace safety behaviour, developmental child behaviour or other health-based analysis.

There’s recent research into Indoor Location Data for Tracking Human Behaviours: A Scoping Review that’s meta research in that it’s an analysis of past RTLS-based human behaviour research. The Canadian researchers looked into the varied ways behaviour can be extracted from RTLS data and the features that can extracted. They examined 79 studies using RTLS data to describe aspects of human behaviour. The most common use was to monitor health status, followed by analysing consumer behaviours, increasing safety, operational efficiency and investigating developmental child behaviours.

The main behaviour features were found to be dwell time, trajectory and proximity. While many papers were able to detect features and hence behaviours, few continued to clinically validate their findings. Beyond activity recognition, few took the opportunity to create models for use in their respective fields, for example, “detecting abnormal behaviours in older adults”. Such models might be used to provide useable baselines for behaviour and health monitoring.

The paper mentions using different locating technologies for different granularity. More specifically, RFID and IR technologies provide too low a level of granularity in location tracking that can prevent extraction of behaviours or continuous movement patterns. Conversely, UWB needs constant battery changing or recharging that can make data collection difficult.

The researchers conclude that while RTLS technologies provide a valuable tool to analyse patterns of human behaviours, future studies should use more complex feature analysis methods to make more of the richness of location-based data.

Asset Tracking For Manufacturers

Today’s just-in-time and busy manufacturing processes means that manual tracking of pallets for inbound and outbound shipments often can’t keep pace with the speed of production. Production and assembly requires the quick locating of components. Delays and inaccuracies due to lost components lead to increased costs, employee frustration and ultimately customer disappointment.

Competitive pressures are also driving the need to reduce labour thus reducing the capacity to manually search for items. Customisation using configured options and demand-driven production is also increasing the degree of inbound component searching that exacerbates the problems.

Even those companies using legacy tracking solutions find that location is only as good as the last barcode or RFID scan. Humans get lazy, make mistakes and don’t scan, causing pallets, crates and boxes to get lost. Many RFID readers don’t work reliably near metal components. Relying on a system that can’t find just a few items can be worse that a manual system that works but is slower. Bluetooth asset tracking solves these problems because the location is automatically collected in real-time and is continually updated.

Asset tracking can be applied to items such as components, pallets, cases, tools, returnable assets such as racks and cages as well as items on loan to ensure they are returned on time. It can improve worker safety and provide alerts in cases of congestion, perimeter deviation and lone worker distress. It can ensure forklifts are being fully utilised, are taking an optimum route, haven’t crashed into racking and haven’t gone out of an area.

The real-time visibility allows connected systems to generate confirmation and exception alerts and automatically trigger shipping processes, replacing costly manual workflows. Tracking outputs also allows confirmation that the correct things are loaded on the correct transport.

A Bluetooth-based real time location system (RTLS) increases visibility and allows the manufacturing process to adapt in real-time to short term business needs. It provides cost savings, greater efficiency and business intelligence that can be used to derive larger scale changes based on data rather than gut instinct. Overall reporting of input and outputs provides input to management reporting to monitor the business.

Read about BeaconRTLS™
Read about PrecisionRTLS™

Real Time Location System (RTLS) ROI

If you are an owner or manager considering implementing a RTLS you might need to justify the return on investment (ROI). In some cases this is easy but in others a quantitative assessment of ROI can be tricky.

The simpler usecases where RTLS is used to automate manually finding items can be easily assessed. For example, workers might be spending a lot of time finding the right pallet in a warehouse or a nurse might be spending too long looking for a shared piece of expensive equipment. Not knowing where things are is increasingly becoming unacceptable for businesses. Times and salaries can be measured, totalled and estimated RIOs calculated to prove ROI.

However, say for example, an RTLS is used to monitor hospital medicines to ensure they in refrigerators and don’t exceed a measured temperature. What are the costs of not doing this? Apart from the cost of the medicines themselves how do you assess the cost of someone dying because the medicines weren’t kept cold? Still in the hospital, how do you assess the gain in being able to find wheelchairs in a hospital? How do you put a price on customer satisfaction?

Things can also get more complicated when, as it usually the case, a RTLS system starts being used for more than one purpose. For example, a recent education client purchased a system for tracking room occupancy but subsequently extended it for lone worker SOS. It’s often the case that just initial usecase justifies the initial investment and follow-on uses are a bonus.

Follow on benefits usually come through reporting and subsequent process improvement. Questions typically revolve around ‘Where has my asset been?’ or ‘What’s happened at particular location?’. The answers, in the form of data, provide insights that drive improvements in processes that can’t always be easily measured or quantified.

Focussing on ROI on its own can be misleading and it’s instead necessary to take a wider view of the qualitative benefits and opportunities.

Using Multi Bluetooth iBeacon Trilateration For Increased Accuracy

There’s a new paper from the journal Telkomnika Telecommunication, Computing, Electronics and Control on Smartphone indoor positioning based on enhanced BLE beacon multi-lateration (pdf). The paper by Ngoc-Son Duong of Vietnam National University describes a relatively simple method to improve location accuracy.

The paper starts by describing trilateration and the author voices the opinion that another method, fingerprinting, requires a lot of effort and isn’t feasible for practical implementation.

The new method makes use of the fact that accuracy is usually good when the received signal strength (RSSI) is -70 dBm or better. The use of more beacons and basing calculations on ‘reliable circles’ of higher signal strength, when available, provides for more accuracy.

The data is also filtered using a Kalman filter to reduce signal noise by about 37%.

Read about Determining Location Using Bluetooth Beacons

Real Time Location Systems (RTLS) in Healthcare

Due to the pandemic, hospitals and care facilities have been experiencing greater patient numbers leading to pressures to accelerate digital transformation to increase efficiency. At BeaconZone, these are the main reasons customers have been using locating systems:

  • To save time searching for equipment, particularly highly mobile equipment such as wheelchairs
  • To monitor the location and temperature of medicines
  • To monitor the location of hospital porters
  • To track the location of vulnerable patients
  • To audit the visiting of care givers to patients

However, there are many more areas suitable for increasing efficiency and safety:

  • Tracking expensive assets such as beds and medical devices
  • Tracking rental/borrowed equipment to ensure they are returned on time to avoid unintended costs
  • Staff distress SOS for increased safety
  • Hygiene management, for example, on hand washing stations
  • Inventory counts and stock checks
  • Analysis of workflows to detect choke points and streamline processes
  • Production of key metrics such as time being spent with patients, patient throughput and wait times

Time saved improving the above activities leads to more time being spent with patients and hence potentially saved lives.

Here are some considerations if you are comparing solutions:

  • Tag costs – Prefer commodity rather than proprietary hardware to reduce costs and allow 2nd sourcing to reduce future risk
  • Real time – Prefer systems that detect continuously over those that rely on error-prone manual scanning
  • Scalable – Prefer software systems that will scale financially, particularly in large hospitals
  • Ongoing costs – Prefer systems that have known future system costs – ideally with a one-off licence rather than varying subscription.

One final tip. It’s our experience that healthcare providers under-estimate the human element in attempting to implement new systems. There are often internal problems as to who will be responsible for a) purchasing, b) installing and c) running new systems. Work these out and agree up-front before embarking on these transformative changes so as to prevent your project becoming blocked.

Read about BeaconRTLS™

Read about BluetoothLocationEngine™

An AI Machine Learning Beacon-Based Indoor Location System

There’s a recent paper by researchers at DeustoTech Institute of Technology, Bilbao, Spain and Department of Engineering for Innovation, University of Salento, Lecce, Italy on Behavior Modeling for a Beacon-Based Indoor Location System.

The research compares two different approaches to track a person indoors using Bluetooth LE technology with a smartphone and a smartwatch used as monitoring devices.

The beacons were AKMW-iB005N-SMA supplied by us and it’s the first time we have been referenced in a research paper.

The research is novel in that it uses AI machine learning to attempt location prediction.

The researchers were able to predict the user’s next location with 67% accuracy.

Location prediction has some interesting and useful applications. For example, you might stop a vulnerable person going outside a defined area or in an industrial setting stop a worker going into a dangerous area.