Author: Support

Bluetooth AoA Direction Finding Antenna Design

We have previously mentioned that antenna design is a complex area that will slow the rollout of Bluetooth AoA direction finding solutions. What are the issues?

Theodoros Prokic of the KTH Royal Institute of Technology has a new paper on the Antenna Design for Angle of Arrival Measurement in Access Control Applications (pdf) that explores the antennas needed for two sides of an in an inside-outside scenario.

The paper provides an analysis of the challenges the antenna designer faces when creating an AoA solution. Issues include orientation and polarization, matching, coupling, reflections, phase center, and physical size. Designing and creating antennas can easily lead to inconsistent results due to the affects of hardware, cables and other testing equipment in the vicinity.

IoT Priority and Asset Tracking

Gartner has a new report Hype Cycle for the Internet of Things 2019, in which they say:

“The Priority Matrix shows that many IoT technologies are 5 years from mainstream adoption. However only one innovation profile will reach maturity in 2 years, indoor location for assets.

So why is ‘indoor location for assets’ more likely to achieve mainstream adoption sooner than other technologies? It’s because there are clear benefits for most companies and off-the-shelf software such as our BeaconRTLS™ is already available.

Our work with companies shows they are nevertheless cautious. Companies are taking time to understand the competing asset tracking technologies and are performing, sometimes lengthy, trials to determine how new systems will integrate with existing systems. They are considering the implications of SAAS vs on-premise solutions, the availability of second-sourced beacon hardware and the compromises of accuracy vs system complexity and cost.

New Interview with Quuppa

Mister Beacon has a new interview with Fabio Belloni of Quuppa. It clarifies that while Quuppa uses direction finding techniques and contributed to the Bluetooth 5.1 direction finding standard, their solution is based on Bluetooth 4 and is a proprietary, not standards based solution. Their solution will continue to be provided alongside their new products based on Bluetooth 5.1.

The interview mentions how the Bluetooth 5.1 direction finding standard might need to evolve to provide less ‘chatty’, shorter communication in order to be suitable for all usecases, particularly those that are battery powered or need to have very large numbers of assets being tracked.

It’s also mentioned that the Bluetooth direction finding standard doesn’t cover tools needed to setup and control direction finding systems. It also doesn’t specify antenna design that’s a complex area.

As we have also experienced, there’s mention how some Ultra Wideband (UWB) vendors and ISVs are moving to Bluetooth for reduced costs, reduced power requirements and compatibility with other devices (tablets, phones and single board computers) that also use Bluetooth LE.

There’s also a recent article by Quuppa on Quuppa’s Role Regarding the New Bluetooth SIG Direction Finding Feature. It explains how AoD will require work by software operating system providers, hardware ODMs, silicon vendors and direction finding product providers before products appear in the market.

Location Beacons

We sometimes get asked for location beacons or which beacons are best for determining location. All beacons can be used for locating. While there are physical aspects such as battery size/life and waterproofing that make some beacons more suitable for some scenarios, locating capability is determined more by the software used rather than the beacons themselves.

Our article on Determining Location Using Bluetooth Beacons gives an overview on locating while the article on Using Beacons, iBeacons for Real-time Locating Systems (RTLS) explains how RTLS work. If you wish to create your own locating software we have a large number of posts on RSSI.

If you have been attracted to Bluetooth by recent announcements on Bluetooth direction finding, be aware that no ready-made hardware or software solutions exist yet. It will take a while, perhaps years, before silicon vendors support Bluetooth 5.1 direction finding, silicon vendors create SDKs and hardware manufacturers create hardware.

The State of AI in 2019

Beacons provide a great way of providing new data for AI machine learning. They allow you to measure things that aren’t currently being quantified, create new data that isn’t silo’d by protectionist staff or departments and allow you to pre-process data in-place making it suitable for learning and inference.

There’s a new free State of AI Report 2019 in the form of a 136 page presentation. It covers aspects such as research, talent, industry and geopolitical areas such as China and Politics.

Read more about AI Machine Learning with Beacons

Bluetooth MAC Randomization Can Be Defeated

The Register has an article Brilliant Boston boffins blow big borehole in Bluetooth’s ballyhooed barricades: MAC addy randomization broken.

Beneath the hyperbolic alliteration is some research (pdf) that Bluetooth MAC randomization isn’t foolproof. Researchers have found that similarities between the non-MAC information in advertising allows devices to be uniquely identified:

“What is perhaps even more concerning, say the Boston Uni trio, is the message Bluetooth vendors are putting out to the public when they advertise Bluetooth LE as being an untrackable standard.”

In actual fact, very few vendors do MAC randomization. The majority of beacon manufacturers don’t because the whole idea of a beacon is that it can be identified via MAC address or iBeacon id. For the same reason, most Bluetooth accessories don’t as they want to be identified via apps. Android smartphones don’t do MAC randomization but iOS and Windows 10 do to improve end-user privacy. It’s mainly iOS devices that will be moving around and possibly tracked in-store or on-site via the ‘vulnerability’ described in the paper.

The Crux of Machine Learning is Realistic Expectations

Venturebeat has an article, based on IDC research, titled For 1 in 4 companies, half of all AI projects fail.

“Firms blamed the cost of AI solutions, a lack of qualified workers, and biased data as the principal blockers impeding AI adoption internally. Respondents identified skills shortages and unrealistic expectations as the top two reasons for failure, in fact, with a full quarter reporting up to 50% failure rate.”

We believe a key part of this is ‘unrealistic expectations’. Half of all AI projects failing for 1 in 4 companies isn’t unreasonable. AI and machine learning should be viewed as a research rather than a development activity in that it’s often the case that it’s not known if the goal is achievable until you try.

Another unrealistic expectation of machine learning is often to have 100% accuracy. The use of an accuracy % in assessing machine learning models focuses stakeholders minds too much on the perceived need for a very high accuracy. In reality, human-assessed, non-machine learning, processes such as medical diagnosis tend to have much less than 100% accuracy and sometimes have undetermined accuracy but these are reasonably seen as being acceptable.

In summary, there has to be upfront realistic expectations of both the possible outcome and the accuracy of the outcome for projects to correctly determine if AI activities are an unexpected failure.

Read about AI Machine Learning with Beacons

Simple In Out Uses Beacons

Simple In Out is an employee in/out board that works across multiple platforms:

As well as providing a useful visual display of who’s in and out it’s also possible to use the system for employee timekeeping, notifications when people come in/out and integration with Slack or other systems via web hooks or the API.

Simple in/out uses the employees’ phone’s operating system to detect the geographical area using cell towers or local WiFi Networks. It’s possible to use beacons to improve the accuracy. Beacons are better when you need to use Simple In Out with smaller areas (10-20 metres), moving areas or areas with poor cellular reception or no WiFi.

Configuring iBeacon with Minew BeaconSET+

Minew have a new video showing how easy it is to set iBeacon parameters with their BeaconSET+ app:

BeaconSET+ is the newer app that works with MiniBeacon Plus beacons. These are Minew beacons supporting both iBeacon and Eddystone as opposed to those only supporting iBeacon for which the older BeaconSET app should be used.

This new video is one of many new tutorials that show how to use BeaconSET+.

View Minew Beacons

Using Beacons with iOS 13

iOS 13 has introduced changes to Location and Bluetooth permissions. Estimote has an excellent new post summarising the changes and their affect on apps using beacons.

The article differentiates between Core Location and Core Bluetooth. Core Location implies using the iBeacon APIs while Core Bluetooth is lower level and allows scanning and connection to any Bluetooth LE devices, not just beacons (but perversely can’t scan the iBeacon UUD, major and minor). If, as we recommend, you use the Apple Core Location APIs directly, only the Core Location permission changes will affect you.

There was time, during the release of iOS 10 when Core Location beacon detection was faulty. At that time, Estimote decided to create an alternative beacon detection API based on Core Bluetooth to circumvent the problems. This means that if you use their SDK, users of your apps will get both Location and Bluetooth prompts and both permissions are required for the Proximity SDK to function. The iOS 10 triggering problems have since been fixed.