Study on Visitor Behaviour in Museums

There’s new research from the Department of Architecture and Design (DAD), Turin, Italy on Technology as a tool to study visitor behaviour in museums: positioning and neuropsychological detection to identify physical & cognitive barriers (pdf).

Inclusive communication projects in museums often rely on general principles of design without considering how unique a cultural experience it should be. It’s important to study all types of visitors, especially those who feel left out, to understand their experiences better and help them feel more included. However, tracking visitors in a museum can be difficult due to the indoor environment and the need to avoid affecting their behaviour.

To tackle this, the researchers used Bluetooth to study individual experiences. They used a Raspberry Pi that can located a user based on signals from Bluetooth beacons, providing a cheap way to track visitors indoors.


This system was tested at the National Etruscan Museum of Villa Giulia in Rome, Italy. About 60 visitors were tracked, and their emotional responses were measured using a special bracelet. This data was stored and analysed to understand how visitors’ locations in the museum might relate to their emotional experiences, such as spending more time near pieces of art that have a strong emotional impact.

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New Human Occupancy Sensor Beacon

The new INGICS iBS08 human detection sensor beacon uses a IT thermal sensor to detect occupancy. It’s better than a PIR sensor beacon in that it can detect the presence of a human even if they are not moving. It’s powered by a CR2450 battery and has a battery life of 1.8 years with a 30-second advertising interval.


There are two models with two distinct angles to cater to a variety of needs. The iBS08S model provides a wide field of view (FOV) of 35 degrees, making it perfect for shorter distance applications, with a detection range of up to 100cm. The iBS08L offers a narrower FOV of 10 degrees, tailored for longer distance applications and boasting a detection range of up to 250cm.

The device are equipped with the latest Bluetooth 5 technology, supporting Coded Phy, with a Bluetooth range of up to 100M.

This beacon is available by special order from BeaconZone.

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The Potential of BLE Beacons in Enhancing Road Safety

Road traffic accidents have been steadily increasing, raising concerns among authorities and the public alike. A significant number of these accidents can be attributed to factors such as driver error and a blatant disregard for obeying traffic signs. While these human-induced errors persist, there is a hope on the horizon in the form of Connected and Automated Vehicles (CAVs). These vehicles, equipped with advanced technology, are anticipated to drastically reduce the number of accidents by navigating roads more safely and efficiently than traditional vehicles.

A component in the deployment and effectiveness of CAVs is Vehicle-to-everything (V2X) communication. This encompasses infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communication, acting as a bridge to enhance road safety for vehicles driven both manually by humans and automatically by systems. These modes of communication ensure that vehicles are constantly in touch with their surroundings, be it other vehicles or the infrastructure, allowing them to make informed decisions.

Enter Bluetooth Low Energy (BLE) beacons, a technology that holds significant potential for I2V communication. Their appeal lies in their affordability, compactness, low energy consumption, wide compatibility with contemporary devices, and an impressively extensive range. Given these attributes, there’s growing interest in evaluating BLE beacons’ efficacy when used as roadside units (RSUs) attached to traffic signs. The goal? To seamlessly convey time-critical information to vehicles, especially in bustling urban settings.

A comprehensive study was conducted to look into this very potential. This involved integrating a CAV development platform to discern if the vehicle could aptly receive the beacon message from a distance that allows for sufficient reaction time, especially when adhering to the speed limits set for that particular road. The study was meticulous, taking into account the road’s geometry and the varying conditions it might present, from dry surfaces to wet terrains.

Furthermore, this research wasn’t just limited to understanding the capability of BLE beacons. It also looked into testing diverse BLE beacon configurations to pinpoint the optimal setup that ensured the required distance was met for all signs. This was imperative to ensure that CAVs could safely detect the signs and respond accordingly.

The findings were promising. The results demonstrated that BLE beacons, when positioned and configured appropriately, have immense potential to be employed in time-sensitive I2V communications on urban roads. Moreover, the study succeeded in identifying the optimal beacon configurations for signs, ensuring they are detected safely by CAVs, marking a significant stride towards safer urban roads in the future.

How Far Can a Bluetooth Beacon Measure Distance?

A common misconception is that beacons can measure distance. In reality, beacons, with the exception of some specialist social distancing beacons and sensor beacons with an additional distance sensor, are designed to send signals rather than receive them.

Instead, measuring distance happens on the receiving end. Devices such as smartphones are equipped to detect these beacon signals. When a beacon sends out its Bluetooth radio signal, the receiving device knows the received signal strength (RSSI). This RSSI can be used to infer the distance between the beacon and the device.

In the proximity of a few metres, the variation in RSSI is significant enough to deduce the distance with a reasonable degree of accuracy. However, as the distance increases, the variation in RSSI becomes less pronounced. This means that while you can determine if a beacon is close or far away, pinpointing an exact distance becomes challenging.

For example, the iOS programming API, CoreBluetooth, provides classifications for the detected beacon signals. These classifications are ‘immediate’, ‘near’, and ‘far’. They don’t give a precise measurement in metres or feet but rather a general idea of the beacon’s proximity.

In terms of maximum range, depending on the specific beacon, it can be detected from distances up to 50m or even 100m. However, as mentioned earlier, at these longer ranges, the RSSI doesn’t provide a clear indication of exact distance. Instead, it offers a more general sense of whether the beacon is nearer or farther away.

Location System Anchor Optimisation

Researchers from Department of Computer Science, University of Jaén, Spain have a new paper on OBLEA: A New Methodology to Optimise Bluetooth Low Energy Anchors in Multi-occupancy Location Systems.

This paper introduces a new methodology called OBLEA, which aims to optimise BLE anchor configurations in indoor settings. It takes into account various BLE variables to enhance flexibility and applicability to different environments. The method uses a data-driven approach, aiming to obtain the best configuration with as few anchors as possible.

The OBLEA method offers a flexible framework for indoor spaces where the occupants are fitted with wrist activity bracelets (beacons) and BLE anchors are set up. The anchors then collect and aggregate data, sending it to a central point (fog node) via MQTT.

A dataset was generated with the maximum number of anchors in the indoor environment, and different configurations were then trained and tested based on this dataset. The best balance between fewer anchors and high accuracy was chosen as the optimal configuration.

This methodology was tested and optimised in a real-world scenario, in a Spanish nursing home in Alcaudete, Jaén. The experiment involved seven inhabitants in four shared double rooms. As a result of this optimisation, the inhabitants could be located in real time with an accuracy of 99.82%, using a method called the K-Nearest-Neighbour algorithm and collating the signal strength (RSSIs) in 30-second time windows.

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What is the Difference Between iBeacon and Eddystone?

iBeacon, a standard developed by Apple, was introduced in 2013 as part of the iOS 7. It’s based on Bluetooth Low Energy (BLE), a power-efficient variant of Bluetooth technology. The strength of iBeacon lies in its background support on iOS devices, which allows for easier detection of beacons.

Google introduced Eddystone in 2015. This protocol for beacons was developed to embrace a broader range of uses. Eddystone offers multiple frame types to cater to various data needs like URLs, unique identifiers and sensor data. One most distinctive feature of Eddystone was the Eddystone-URL, where the beacons could send out a web address. However, this has been limited by the discontinuation of Google Nearby in Android.

Despite the differences in their design and features, both iBeacon and Eddystone share common ground in their use of standard Bluetooth advertising. They send different data in the same standard Bluetooth advertising packets. This shared aspect of technology ensures that they can both communicate effectively to both iOS and Android.

While Eddystone’s versatile frame types and open protocol initially made it appealing, it has seen a decline since the discontinuation of Nearby in Android. Currently, most new systems requiring smartphone applications to detect a beacon opt for iBeacon.

However, when it comes to locating and detection using gateways rather than smartphones, iBeacon vs Eddystone becomes less relevant and the beacons’ Bluetooth MAC addresses are usually used. The advertising packets can instead be used for sensor data, for example, temperature and humidity.

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Monitoring Sheep Location Using Bluetooth Beacons

There’s new research from Scotland, UK on Calibration of a novel Bluetooth Low Energy (BLE) monitoring device in a sheep grazing environment. Knowing an animal’s location and proximity can offer insights into landscape use, animal performance, behaviour and social contacts. However, the technologies currently used to collect these data are costly and challenging to implement, particularly due to the low value of individual animals and typically large flock sizes.

A device was specifically designed for a study to assess the relationship between the Received Signal Strength Indicator (RSSI) of a BLE beacon and BLE reader and to develop a distance prediction model. This model was then applied in a static situation and on-sheep studies, using a multi-lateration approach to determine a beacon’s location within a field setting. A purpose-built Wearable Integrated Sensor Platform (WISP) was developed for the study, featuring a BLE reader and other sensors. It was designed to report the identity and RSSI of the 16 ‘closest’ beacons seen for each duty cycle.

The findings revealed that the height of the device had an impact, with fewer beacons reported at a shorter distance in WISPs at the lower height of 0.3 m. RSSI can vary greatly based on factors like transmission power, device orientation, enclosure and the operating environment.

Using the distance prediction and adjusted distance prediction, beacon locations could be estimated for most of the beacons. Not all beacons could be located due to issues such as being reported by too few WISPs or the resulting multi-lateration circles not intersecting.

The study suggests that BLE can potentially be used for sheep localisation in outdoor environments. The multi-lateration approach is dependent on receiving RSSI readings from multiple readers at a similar timepoint, it could offer more information about localisation and movement than simple proximity ranges or presence/absence. Locating a sheep to within about 30 m in a field environment represents a significant step forward.

Does Bluetooth Signal Go Through Walls?

One question that often comes up is whether Bluetooth signals can go through walls. The answer is a bit more nuanced than a simple yes or no.

Bluetooth operates on a 2.4 GHz ISM (Industrial, Scientific, and Medical) radio frequency band. This frequency is also shared by other wireless technologies like Wi-Fi. Bluetooth signals are designed to be robust but are generally short-range, typically extending up to 50 metres. As it uses the same frequency as Wi-Fi which most people have a knowledge of range of, a very rough approximation is to think of Bluetooth as being similar to Wi-Fi.

The material of the wall plays a significant role in how well a Bluetooth signal can pass through it. Materials like drywall, glass and wood are generally more permeable to Bluetooth signals. In contrast, concrete, brick and metal can severely limit or block the signal altogether.

The strength of the Bluetooth signal also matters. Higher-powered Bluetooth devices can transmit signals that are more likely to pass through walls. However, even with a strong signal, the quality may degrade as it passes through obstacles.

The distance between the transmitting and receiving devices will also impact the signal’s ability to pass through walls. The closer the devices are to each other, the more likely it is that the signal will successfully penetrate the wall.

In practical terms, while it’s possible for Bluetooth signals to go through walls, the quality and reliability of the connection can be compromised.

So, does Bluetooth signal go through walls? The answer is yes, but with caveats. The type of wall, the strength of the signal, interference from other devices, and the distance between the connected devices all play a role in determining how well a Bluetooth signal can penetrate walls.

Can I Set the Maximum Distance the Beacon Transmits?

Many people inquire about adjusting the transmission distance of a beacon. They often wish to either conserve battery or restrict the range at which a beacon is detectable.

While some third-party platforms and SDKs offer distance settings, it’s a misconception to think you can directly set the distance. What you’re actually adjusting is the transmission power, which in turn influences the transmission distance. But since this involves radio waves, which are prone to reflections and interference, it’s impossible to guarantee that a specific power will equate to a precise distance.

When using an app to detect beacons, you can employ the Received Signal Strength Indicator (RSSI) to focus on those within a desired range. However, it’s challenging to precisely correlate RSSI with the actual distance.

Some wonder if they can set the distance in terms of centimetres, similar to NFC. Typically, this isn’t feasible because even at their lowest power setting, most beacons transmit over a distance of about a metre.

Rather than asking if the transmitter’s distance can be minimised, it might be more practical to configure the receiver to disregard detections from further away. By using the RSSI value on the receiving app or another Bluetooth scanning device, you can filter out distant beacons. Specifically, you can dismiss detections with an RSSI below a certain threshold, allowing you to focus on detections within a centimetre range.

We have an article on Choosing the Transmitted Power.

The Limitations of Bluetooth Mesh

Earlier this year, we made the decision to retire SensorMesh™, a product that was built on top of the standard Bluetooth mesh framework. At first glance, Bluetooth mesh appeared to be a promising technology—serverless, open, adaptable and with an extended range compared to standard Bluetooth LE. However, as we got into its implementation and use, we found that the limitations outweighed the benefits.

Our SensorMesh™ was designed to be a versatile solution for various applications. It provided a new Bluetooth Mesh model that allowed the participation of any Bluetooth beacons or other devices without them requiring firmware updates. The system also allowed for payload filtering and time-based control to manage throughput. It was capable of transmitting data from a variety of sensors, such as location, movement, button press, temperature, humidity, air pressure, light level, open/closed status, and proximity, over the mesh network:


One of the first issues we encountered was the complicated provisioning and setup process. Unlike turnkey solutions, Bluetooth mesh required a provisioner, usually an app on a smartphone, to store encryption keys. This made the initial setup far from straightforward and ongoing management difficult.

Another significant limitation was the very low throughput, which was in the order of a few thousand bits (yes bits!) per second. For most applications, especially those requiring IoT data transmission, this was not sufficient. In many cases, using gateways proved to be a more effective solution.

The Bluetooth SIG’s chosen flooding architecture, while excellent for low latency, consumed too much power for battery-operated devices. As a result, we had to resort to installing firmware on USB dongle -style devices, which were permanently powered. This was inconvenient for many applications we saw from potential clients where mesh networks would have been ideal, such as in mines, hospitals, factories, farms and even battlefields where existing networks are already congested or non-existent.

We also found that Bluetooth GATT clients at the edge of the mesh, responsible for relaying the mesh data somewhere else, easily became congested despite the low throughput. Our workaround involved using USB dongle with mesh firmware and a COM port rather than GATT.

Bluetooth mesh offered no way to trade latency for less power consumption. Its throughput was too limited for most uses, a problem inherent to the technology. Since its announcement in 2017, Bluetooth mesh hasn’t seen many implementations outside the lighting industry. We believe this is because it was driven, designed and optimised for lighting scenarios, which require low latency and permanent power but can tolerate low throughput. Sadly, enhancements recently provided by Mesh 1.1, such as directed forwarding, device firmware update, remote provisioning and subnet bridging have come about mainly to solve problems found in Network Lighting Control (NLC).

In the end, we retired SensorMesh™ because it didn’t have a good product-market fit. The underlying characteristics of Bluetooth mesh were too limiting to make it a useful solution for the applications our customers envisioned. While Bluetooth mesh may have its niche uses, we believe its limitations make it currently unsuitable for broader applications.