Author: Support

Underground Mine Truck Transport Analysis Using Beacons

There’s recent research into using Bluetooth beacons in mines. The paper by Department of Energy Resources Engineering, Pukyong National University, Korea on Analysis and Diagnosis of Truck Transport Routes in Underground Mines Using Transport Time Data Collected through Bluetooth Beacons and Tablet Computers analyses truck travel times.

Beacons are detected by truck mounted tablet computers and analysed by a cloud server. This was tested in a limestone mine located in Jeongseon, Korea. The system is able to detect sections of routes that are stable and unstable so as to highlight areas that need further analysis and remediation to improve transit flow.

View the beacon used in this research

Mesh-based Panic Button

There’s an article at business of business on how Yasmine Mustafa has created a new business Roar For Good that supplies smart panic buttons for hotel and hospitality workers.

This is one of the first applications of Bluetooth Mesh outside of lighting. Workers push the panic button if they need help. A nearby beacon is used to identify their location and a notification is sent to security or the hotel manager.

Read about Bluetooth Mesh

What are the Estimated Distances for Tx Powers?

Beacons allow you to set the transmit power to levels such as -30dBm, -20dBm, -16dBm, -12dBm, -8dBm, -4dBm, 0dBm and +4dBm. The number of actual setting values depends on the beacon. 0dbm is the default power recommended for normal use. Our article on Choosing the Transmitted Power explains these values and how they relate to distance.

We are often asked ‘What are the Estimated Distance/s for Tx Powers?’. This depends on the beacon, the environment and the receiver. An analogy is someone shouting a word. How loud does someone have to shout to be heard a certain distance? It depends on how clear the person shouts, how much noise there is and how well the person listening can hear. With beacons it depends on the beacon (mainly antenna) design, how much radio frequency (RF) noise there is, the degree of RF reflections, the receiving ability of the device (smartphone or gateway) you are using and even the weather.

The only way to determine the relationship between distance and power is experimentally and it will likely change over time as the environment changes.

Flutter Beacon Plugin

If you want to try Bluetooth beacon advertising from your iOS or Android smartphone there’s a Flutter plugin called beacon_broadcast:

Simulating a beacon from a smartphone is a great way to get started and explore Bluetooth LE prior to buying dedicated hardware devices. However, it’s not something you should progress to regular use because advertising in this way uses a lot of battery power.

Beacon_broadcast is open source and the source code can be found on GitHub.

Beacons Used by Hotel Panic Buttons

Hotel Management has an article mentioning how hotel panic button solutions are being used by Curator Hotel & Resort Collection.

Employees wear a cellular wireless panic button that can be pressed when help is needed. Bluetooth beacons are placed around the hotel that allow the worker to be located.

There are other ways to implement such systems without needing expensive, extra, cellular wireless. For example, it’s possible to piggy back on phones employees are already carrying, use beacons with 2-way radio or have gateways around the hotel to detect location.

A Beacon-Based Mobility Aid for People with Dementia

James Bayliss, a final year industrial design student at Loughborough University, has designed a smart mobility aid that uses beacons. It’s allows people with dementia to live safely in their own home for longer.

The system, called ‘AIDE’, comprises of a walking stick that works with Bluetooth beacons situated around the home.

It tracks the person’s movement and uses machine learning software to detect behaviours and actions that are out of the ordinary. The system also provides reminders to the person to help re-orient them if they have a confused episode.

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 iB005N 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.

Bluetooth LE Learning Resources

Bluetooth LE development is getting very popular with an increasing number of learning resources. Here are some that have appeared recently:

Erik Hellman, a developer, has two useful articles Bluetooth LE for modern Android Development part1 and part2. He covers Android versions, Bluetooth GATT, PHY, Android Device Manager, pairing and bonding.

Litum have a new article What is Bluetooth Low Energy (BLE)? How does BLE work? that’s higher level and less technical covering Bluetooth LE device discovery, differences to Classic Bluetooth, how positioning works, Bluetooth range , usecases and industries.

Zephyr, the embedded systems OS have also recently updated their Bluetooth documentation.