Tracking Forklift Trucks

Forklift trucks are a common theme or problem in warehouses. They are expensive, can cause damage and are potentially dangerous. Here are the top 3 scenarios we have come across when speaking to warehouse clients.

  • Tracking the usage of forklifts to make best use of what is an expensive resource. The solution is real-time monitoring of movement using a real time locating system (RTLS) to detect excessive durations of no movement.
  • Detecting if they crash into racking. For example, we had a customer with a warehouse storing dangerous chemicals. They needed to know about impacts with racking that could potentially displace and spill the chemicals. The solution is detecting unexpected excessive rack movement using a RTLS.
  • Detecting if they go missing. One client told us of forklifts going missing having been driven off in lorries in the cargo area. A RTLS can alert when forklifts go outside an area, inside an area or are no longer being seen.

These scenarios affect the company’s direct costs. Preventing just one incident can pay for the RTLS and more importantly prevent fines, injuries, lost days and medical bills.

Even when there aren’t accidents, a RTLS saves costs through improved efficiency.

Read about BeaconRTLS™

Learn about Beacons in Industry and the 4th Industrial Revolution (4IR)

Automatic Transport Ticketing Using Beacons

There’s new research from University of Cagliari, Italy on Beep4Me: Automatic Ticket Validation to Support Fare Clearing and Service Planning.

Integrated transport with single ticketing across bus, tram and train requires revenue sharing between service providers which, in turn, needs accurate usage data. Relying solely on user-provided data suffers from incomplete data because not all users always validate their ticket when checking out or when switching lines.

The researchers have created a system, Beep4Me, that collects usage data and interfaces with an existing mobile ticketing platform.

A smartphone app identifies the vehicle (bus, tram, or train) and automatically validates the ticket. It does this using Bluetooth LE beacons and location and orientation phone sensors to identify the patterns to clearly define modes of transport. Beacons are installed on buses:

The test data demonstrated almost perfect accuracy of event detection such as validation, transfer, choosing a ticket, purchasing a ticket and check-out.

Bluetooth Vehicle–Pedestrian Collision Warning

There’s recent research by Carleton University, Ottawa, Canada on Investigating Wi-Fi, Bluetooth, and Bluetooth Low-Energy Signal Characteristics for Integration in Vehicle–Pedestrian Collision Warning Systems.

The paper looks into the comparative performance of Wi-Fi, Bluetooth Classic (Bluetooth) and Bluetooth Low Energy (BLE) for integration in vehicle–pedestrian collision warning systems. More specifically, accuracy and functionality are considered with respect to signal strength indicator (RSSI) distance stability, rainfall effects on the signals, motion effects, non-line of sight effects and signal transmission rates.

The experiments identified the overall superiority of Bluetooth LE over Wi-Fi and Classic Bluetooth. Bluetooth LE provides fast collision warnings due to the frequent transmission and provides higher probability of simultaneous signal detection by multiple scanners.

The researchers say the results indicate the possibility of integration of Bluetooth LE technology in the design of vehicle–pedestrian collision warning systems in addition to currently used systems.

New Bluetooth Low Energy (LE) Primer

The Bluetooth LE specifications are very technical and not very approachable for those wishing to use, rather than create, devices using Bluetooth. Bluetooth SIG, who manage the Bluetooth specifications, have a new document by Martin Woolley titled The Bluetooth® Low Energy Primer. This is the definitive guide to better understanding Bluetooth LE.

This free document covers the history of Bluetooth LE and explains the various layers in the Bluetooth stack. It describes the protocols and profiles that make up Bluetooth LE. It also provides pointers to study guides, papers, hands-on resources and formal specifications for further reference.

Is There a Beacon That Works Without Bluetooth On?

We sometimes get asked if it’s possible that smartphones can detect beacons without Bluetooth being on. All beacons are based on Bluetooth LE that, in turn, relies on Bluetooth being switched on in the phone to scan for beacons. There’s no magic underling operating system mechanism on iOS nor Android that allows you to use Bluetooth without the user having Bluetooth on.

More users are leaving their Bluetooth on due to the proliferation of connecting with other devices such as cars, Bluetooth headphones and smart speakers. If you are writing an app you should take steps to detect if Bluetooth is on and prompt the user appropriately.

The phone and beacon industries need to better educate users that Bluetooth is no longer the heavy battery drainer it was in the early days of smartphones.

Passive Human Sensing Using Bluetooth

There’s new research from University of Catania, Italy on A Perspective on Passive Human Sensing with Bluetooth. The research identifies and discusses the factors and operating conditions that can result in varying accuracy.

The paper explains the advantages of Bluetooth over WiFi for passive human sensing. It also discusses the advantages and disadvantages of RFID, VLC, LoRa and LTE. The paper seeks to address the lack of search papers on considering Bluetooth as opposed to WiFi for detecting human presence.

The paper describes how human presence can influence a wireless signal and covers Bluetooth Direction Finding. It explains how Bluetooth is better suited for human detection because it is less subject to electromagnetic noise.

It’s mentioned how signals received on different Bluetooth different channels have different noise and attenuation characteristics:

“Another issue often highlighted in the literature is the impossibility of independently extracting the RSSI signal values from each advertising channel of the BLE beacons. The BLE beacons need to be modified at the hardware or firmware level in order to transmit on a certain preset channel and to allow the researcher to discriminate the variation in the signal due to the presence of a human body from other fading effects.”

What isn’t mentioned in the paper is that Bluetooth Direction Finding requires analysis of the IQ data rather than RSSI. This IQ data also varies depending on the Bluetooth channel. Direction finding receivers can (and must) independently extract and process the channel specific data.

Faraday Bags for Bluetooth

One of the most useful tools when deploying beacons is the Faraday Bag. A Faraday bag allows you purposely block beacons you haven’t yet placed so that they don’t affect testing. During development, it also allows you to simulate beacons or scanning devices going out of range without you even moving.

Faraday bags work by having a very thin gauze layer that block radio signals. Not all types of Faraday bag are the same. For BeaconZone Faraday bags, we had the manufacturer use two layers of gauze to block even the strongest Bluetooth beacons.

For any Faraday bag, the radio signal can leak through any larger holes in the gauze. This includes the opening that should be folded over and attached onto itself using the hook and loop fastening.

Faraday Bags

Detecting Moving Beacons

There’s a new question at GrindSkills on Can Bluetooth beacon be detected while it’s in motion? This deals with similar issues to our previous post on Using Bluetooth to Measure Travel Time.

Both scenarios don’t consider the scanning and advertising periods. Our previous post on Why Bluetooth LE Scanning Doesn’t Always See Devices (the First Time) explains the relationship between these timings.

In order to reliably detect moving beacons it’s necessary to scan more often and have smaller gaps between scanning. Also, if you have control over the advertising device, more frequent advertising will make detection more reliable.

BeaconZone Consultancy

Forest Modelling Using Beacons

Researchers from the University of Manouba, Tunisia have been looking into the analysis of individual forest trees to monitor the state of the forest. This is needed for forestry tasks such as characterisation, inventory, management of forest and fire behaviour modelling.

Airborne Laser Scanning (ALS) derived methods were applied for individual tree detection (ITD) based on a canopy height model (CHM). A Bluetooth beacon was used to collect trees coordinates.

View iBeacons