iBeacon, Eddystone, Bluetooth, IoT sensor beacons, apps, platforms
We have the LW003-B Bluetooth LoRaWAN® Probe in stock that scans for Bluetooth LE devices and sends detected advertising via LoRaWAN®. This extends Bluetooth sensing up to 15Km.
LoRa provides relatively low throughout so it’s important not to send data for unwanted detected devices. The probe provides extensive filtering options to ensure only the data required for specific Bluetooth devices is sent via LoRa:
There’s recent research from Korea on Particle Filtering-Based Indoor Positioning System for Beacon Tag Tracking. The paper looks into how to improve positioning accuracy, reduce system complexity and reduce deployment cost through the use of a Particle Filter-based Indoor Positioning System (PFIPS).
A Kalman Filter is used to preprocess collected Received Signal Strength Indication (RSSI) data followed by a Particle Filter (PF) to approximate the location of a tag which improves the location certainties.
Simulations and experiments showed the system outperformed the legacy indoor positioning systems in terms of location accuracy by 24.1% and achieved median accuracy of 1.16 m.
Read Using Beacons, iBeacons for Real-time Locating Systems (RTLS)
There’s recent research into Sensor placement optimization for critical-grid coverage problem of indoor positioning (PDF). The paper investigates how to reduce deployment cost by placing more sensors in areas that require higher accuracy rather than using a uniform deployment scheme.
Areas are differentiated as either being ‘critical’ or ‘common’. For example, in a railway station, critical areas are elevator entrances, boarding gates, toilets and the service centre. Critical and common areas have different positioning needs leading to different sensor deployment densities.
The paper examines the variation of RSSI with distance and develops a critical-grid coverage model. A NSGA-II algorithm is used to optimise the placement of iBeacon nodes.
The results showed that the new placement scheme obtained a lower error and a greater reduction of sensor deployment cost than the uniform deployment scheme. The proposed method reduced the cost of sensor deployment while ensuring the accuracy of indoor positioning for critical areas.
Digital signs can be found inside retail stores, shopping malls and increasingly at transit locations and even on the street. A growing number of digital signs use Bluetooth beacons.
iBeacon transmissions allow digital signs to work with apps. An app detects the Bluetooth transmission and displays appropriate content in the app. This allows the app to react with what’s being shown on the sign and even control the digital sign. A way of achieving two way communication is to have the app send messages back to a server that causes new data to be shown on the smart sign:
If you are a smart sign manufacturer, the easiest way to add iBeacon support is to use a USB beacon. All your smart sign needs is a spare USB slot. Once set up, the beacon is usually ‘Set and forget’ but there are additional interaction possibilities if the smart sign can send out different advertising at different times and thus become a dynamic beacon. This can be arranged by using a USB beacon that can be controlled via a UART COM port. In this scenario the USB port is used for control as well as power.
There’s new research into Developing a Solution for Mobility and Distribution Analysis Based on Bluetooth and Artificial Intelligence.
The paper describes an efficient solution for locating, tracking, analysing distribution and flow of people and/or vehicles. Filters and algorithms including artificial intelligence and angle of arrival (AoA) were employed.
The resultant system provided for analysis of location, traffic flow and passenger movement along routes.
The researchers found that accuracy was improved when multiple measuring stations were used. Improved positioning was achieved using geometry algorithms (Voronoi) and the k-mean cluster algorithms. Artificial intelligence allowed for deeper analysis of the data for more accurate positioning, trajectory estimation and density evaluation.
Modblue is a new open source Bluetooth library for nodejs that supports central and peripheral mode using hci and dbus. It supports Linux, OS and Windows native via WinRT/UWP.
The library can be used to advertise, scan, connect via GATT, discover services, characteristics and read/write values.
Acrylic have a new Windows-based Bluetooth LE Analyzer that can be used to check for and test Bluetooth devices. The application has a scanner showing the Bluetooth signal strength range (RSSI):
It also provides analysis using dynamic and customizable graphs showing RSSI (signal strength), signal distribution over time and approximate device distance. A BLE beacon viewer shows detailed information on Low Energy Bluetooth devices. The BLE Packet Analyzer explores Bluetooth packet contents:
There’s also an inventory system to keep track of your devices. The free version scans, detects iBeacons and visualises signal strength. The licensed version has the packet analyzer, inventory and advanced filtering.
INGICS, the manufacturer of some of the Bluetooth gateways we supply, has a new open source DemoBoard that can be used to demonstrate and test their gateways.
The software supports M2M (TCP) and MQTT connections.
The dashboard shows the number of messages and beacons:
Clicking on the number of messages shows a log of the received messages:
Clicking on a message shows parsed values:
You can also drill down on the beacons:
While AirTags use Bluetooth (and Ultra Wideband UWB), the Bluetooth transmission isn’t in iBeacon format. The advertising is more complex and involves a rotating key scheme for enhanced security.
The Find My mechanism has been reverse engineered (pdf) by the Secure Mobile Networking Lab of Technical University of Darmstadt.
The researchers have an open source framework called OpenHaystack on GitHub that demonstrates how to create your own tracking tags by installing Bluetooth firmware on Linux, ESP32 or Nordic nRF51.
If you are a manufacturer wanting to use the Find My mechanism, you shouldn’t rely on reverse engineering that can change and should instead join Apple’s Find My network accessory program.
Elektor Magazine has a webinar Rapid Prototyping BLE Android Apps Using MIT App Inventor taking place on June 10, 2021 at 1600 CEST.
MIT App Inventor is a cloud-based tool that allows you to build apps in the web browser. It provides a visual programming block-based environment allowing anyone, even children, to build fully functional apps for smartphones and tablets.
The first 50 registrants are being entered into a raffle to win 10 PIC-IoT boards and vouchers worth €10 and €25 for the Elektor Store.
