We sometimes get asked “What is iBeacon Technology?”. In terms of the beacon itself, iBeacon doesn’t imply much. The underlying Bluetooth does most of the hard work. iBeacon is only one of many possible formats of standard Bluetooth advertising.
The iBeacon advertising consists of three identifiers UUID, major and minor. We have an article explaining how these are usually set up.
The more useful functionality is in iOS itself. Apps can declare an interest in particular beacons and be triggered even when the app is not running. The triggering is usually used to cause a notification on the phone that the user can tap on to do more. If the app is already open, it can look for beacons and display appropriate app content.
Android may also trigger and scan for iBeacons but this is in the context of scanning for Bluetooth advertising as opposed to specific iBeacons.
This is part 2 of a 3 part series that explains what’s inside a beacon. In this part we take a look at the System on a Chip (SoC), in particular the Nordic nRF range, found in many beacons.
In part 1 we identified the Nordic nRF52832 SoC. The nRF52 is a newer version of the Nordic nRF51 that has been used in millions of beacons. The new version has more memory, uses less power and includes NFC. The extra memory is useful for applications such as Bluetooth Mesh.
nRF52832
The Nordic nRF52832 SoC wasn’t created just for beacons. It’s a general purpose device for any electronics that needs to have 2.4GHz wireless communications and software processing. The nRF51 and nRF52 series can be found in many fitness trackers and wearables. For example, the BBC micro:bit, the Polar GPS multisport watch and Garmin’s child activity monitor.
The SoC is a stand alone computer having an ARM® Cortex™-M4 CPU with a floating point unit. The NFC-A Tag can be used in pairing and payment solutions which makes it suited for use with smartphone apps. The SoC also has digital peripherals and interfaces such as PDM and I2S for digital microphones and audio.
nRF52832 Block Diagram
It has very low power consumption via an on-chip adaptive power management system. It uses between 0.3 μA and 1.9 μA, depending on the mode, and can still respond to events. For beacons, it periodically wakes up for about 1ms, during which it uses about 5.3 mA (at 0 dBm power output).
Power use during iBeacon advertising
The SoC supports ANT™, IEEE 802.15.4, Thread, and proprietary protocols operating in the 2.4 GHz bandwidth as well as Bluetooth®.
The marking on the chip denotes the variant with different RAM and flash combinations:
The image in part 1 shows the i7 beacon has the QFAA variant with 64 kB RAM 512 kB Flash. As with SSDs, the flash can only be erased and written so many times. For the nRF52832 this is 10,000 erase/write cycles. This is irrelevant for most beacons as they save very little data, irregularly, usually only when settings are changed. However, for applications such as mesh, the number of erase/write cycles needs to be minimised to prevent the device wearing out in a short period of time.
Tracking things and/or people makes organisations more efficient through enhanced productivity. Most organisations want to improve a specific problem in one of the following areas:
Stock Control – Knowing how much you have, where, without any human checking
Finding Items – Picking items without time-consuming manual searching
Safety & Security – Knowing when assets move, go missing, are dropped or crashed into
Process Efficiency – Preventing human error of manual audits, knowing an expensive asset is being fully utilised, providing real time workplace instructions
Having solved a problem, it’s often the case that the act of digitisation allows other problems to be identified and also solved.
There are many ways to track assets using beacons. Beacons can be put on assets and detected by smartphones, Bluetooth gateways, Bluetooth mesh, or other Bluetooth LE devices such as single board computers. Alternatively, beacons can be fixed and the detecting device(s) can move. Software can be in the detecting devices and/or at a server receiving data from the detecting devices. It’s also possible to use a real time locating system (RTLS) to map the positions of assets.
The optimum solution depends on your situation and requirements. Here are some aspects to think about that will determine the optimum solution:
What’s the size of area(s) and sub-areas (rooms, zones) you need to cover and is this outside?
What’s the physical makeup of the areas (walls, racking) and their composition?
What’s the electrical infrastructure (power, WiFi and Ethernet availability) and can this be upgraded?
What assets need to be tracked?
What attributes of assets need to be tracked (just location or sensor data as well?)
How many need to be tracked?
How many are in the same place, at the same time?
How often do the assets move?
How accurate do you need the locating?
How up to date do you need the tracking?
Who needs to do the tracking, from where?
How many people need to do the tracking simultaneously?
What kinds of information/report do you require and what’s the desired method of receiving?
This is part 1 of a 3 part series that explains what’s inside a beacon. In this part we take a look at the physical beacon.
All beacons are similar inside because they are based on standard circuit designs from Nordic Semiconductor, Dialog Semiconductor or Texas Instruments. These semiconductor manufacturers produce a complete system on a chip (SoC) that requires minimal external components. The SoC is a small computer with memory that runs software created by the manufacturer of the beacon. We will take a deeper look at the SoC in part 2 and the software in part 3.
For this series of articles we going to take a deeper look at Minew’s i7 beacon. It’s based on Nordic Semiconductor’s nRF52832 SoC.
Minew i7
Inside the case is a PCB with a CR2477 slide in battery at the rear.
Inside the i7
The main chip you can see is the mRF52832. At the top you can also see the antenna that’s created using a track in the printed circuit board. The holes at the bottom right are connections used to program the beacon.
To understand more, we need to look at the printed circuit board design and circuit schematic:
i7 design
Circuit diagram – click to see larger in new window
It can be seen that there aren’t many external components. Y1, the metal component at the top is the crystal used to maintain timing. The SoC has a number of programmable input/output (PIO) pins that are multi-purpose. In a beacon some are usually connected to LEDs and a switch as shown at the left hand side of the circuit diagram. There are also capacitors that need to be external to the SoC.
Prognostics is the determination of health of assets to diagnose anomalous behaviour and predict the remaining useful life. It’s used to:
Prevent catastrophic failures
Increase asset availability through less downtime and less time wasted through ‘no fault found’ tests
Extend maintenance cycles
Execute timely repair
The overall aim is to lower lifecycle costs via fewer inspections, repairs and manual inspections. It can be applied to all types of assets across all sectors but is particularly applicable to manufacturing, industry and infrastructure. Infrastructure includes roads and ports as well as utility industries such as water, power and gas.
Prognostics and in-situ testing isn’t new. However, what is new is substantially improved viability and economics. New sensors, such as beacons, are easier to use, can be attached to legacy equipment and have much lower costs. The cost of connectivity and cloud storage is also decreasing. This means more assets can be retro-actively connected and the sharing of data across assets and platforms enables a more complete operating picture. This opens up new business opportunities.
The paper explains the four main types of prognostic management strategies: corrective, fixed-interval preventative, failure-finding, and condition-based maintenance (CBM). It also explains a new fusion approach to prognostics:
The paper gives examples of use of prognostics in the manufacturing, heavy industry, energy generation, transport & logistics, infrastructure assets, automobile, medical, warranty and robotic industries.
It ends with the mention that, in the future, current research and work on energy harvesting will benefit sensors used for prognostics.
Beacons are small computers with a complete System on a Chip (SoC). There are four main companies that manufacturer SoCs: TI, Dialog, NXP and Nordic. Nordic is the most popular SoC for use in beacons, mainly because of the lower (tool) license cost and ease for beacon manufacturers developing the software (actually called firmware) that runs in the beacons.
Nordic has a new free Wireless Quarter Magazine that showcases uses of Nordic SoCs in many types of device, not just beacons.
Learn about:
Gartner research showing sensor innovation fosters IoT growth
Beacons help U.S. shoppers find way
Bluetooth LE in Amazon FreeRTOS
Bluetooth LE smart textiles on the rise
Article combining Bluetooth Low Energy and LPWANs
Firmwave’s use of Bluetooth Low Energy beacons to build an inexpensive satellite broadcast system
The G1 gateway collects advertising data from iBeacon, Eddystone, Bluetooth LE sensor and other Bluetooth LE devices and sends it to your server by HTTP(S) or MQTT/ using WiFi or Ethernet.
The demise of Google Nearby prompted some commentators to declare the death of beacons. However, here at BeaconZone we are actually seeing a resurgence of the use of beacons in retail.
Gone are the unsolicited notifications and gone are the ‘get rich quick’ marketers. The scenarios that remain tend to use beacons as an adjunct to something else rather than being the main solution itself. For example, they are used to provide triggering in CloseComm‘s WiFi onboarding app used by Subway, McDonalds, BurgerKing and CircleK and NCR.
Beacons are being rolled out to many food retailers, particularly in the USA. They are also taking new physical forms as witnessed by Mr Beacon:
If you are looking for more innovative uses of beacons in retail, take a look at Alibaba’s Fashion AI concept store as mentioned in the latest Wired (UK):
RFID and Beacons are used to detect items picked up during shopping so that customers can collect what they have looked at, have accessories automatically selected and view what’s in stock. Once they are home, a virtual wardrobe allows customers to buy anything they saw in store.
Beacons can also be used to enable audit compliance. Eric West, Head of Strategy at IMS has a useful free pdf on takeaways from GroceryShop, the retail industry conference. The pdf also mentions the use of beacons in lighting to drive location-based messages and wayfinding. Also:
“Amazon’s 2017 acquisition of WholeFoods was a “tipping point” that ensured all grocery players were speeding up their digital plans.”
We mentioned Wiliot last March and since then their R&D team has created early engineering samples that prove it’s possible to create a battery-less Bluetooth LE beacon harvesting energy from radio frequencies (RF).
The Wiliot device looks more like a RFID tag than a traditional beacon in that it’s supplied as a very thin PVC inlay sheet containing the chip and wire antenna together. The thin form factor, no battery and the relatively low cost will allow it to be manufactured into or stuck onto clothing and packaging that will provide for many new usecases.
Producing such a device isn’t easy as it can’t use existing System On a Chip (SoC) devices as produced by Nordic, Dialog and Texas Instruments (TI) because they are too large and use too much power. Wiliot has had to create their own SoC from the ground up, including software tools to develop and program the devices. We have been told it will be a year before Wilot has all the components in place for commercial rollout. Meanwhile, selected organisations can join the Early Advantage Program (EAP). There’s a new a product overview (PDF below) that explains the EAP and the main usecases, connected packaging, connected apparel, logistics and asset tracking:
Wiliot already have Early Advantage Program (EAP) agreements in place with over a dozen brands including top fashion brands, a telco, appliance companies, a furniture brand and packaging companies.
AI machine learning is a great partner for sensor beacon data because it allows you to make sense of data that’s often complex and contains noise. Instead of difficult traditional filtering and algorithmic analysis of the data you train a model using existing data. The model is then used to detect, classify and predict. When training the model, machine learning can pick up on nuances of the data that a human programmer wouldn’t see by analysing the data.
One of the problems with the AI machine learning approach is that you use the resultant model but can’t look inside to see how it works. You can’t say why the model has classified something some way or why it has predicted something. This can make it difficult for us humans to trust the output or understand what the model was ‘thinking’ when the classifications or predictions end up being incorrect. It also makes it impossible to provide rationales in situations such as ‘right to know’ legislation or causation auditing.
A new way to solve this problem is use of what are known as counterfactuals. Every model has inputs, in our case sensor beacon data and perhaps additional contextual data. It’s possible to apply different values to inputs to find tipping points in the model. A simple example from acceleration xyz sensor data might be that a ‘falling’ indicator is based on z going over a certain value. Counterfactuals are generic statements that explain not how the model works but how it behaves. Recently, Google announced their What-If tool that can be used to derive such insights from TensorFlow models.
