Category: Sensor Beacons

Detecting Movement With Beacons

There are various types of movement that can be detected by beacons:

Movement between zones – This is large scale movement between, for example, rooms. This relies on devices detecting the beacons and relaying the information to software that, stores historical location, plots positions and creates alerts. This is the basis for Real Time Locating Systems (RTLS).

Movement from stationary – This is when something goes from being stationary to moving. There are two ways to do this. You can look at the xyz from a beacon accelerometer to determine it has started moving. Alternatively, some beacons such as the iB003 have motion triggered advertising so you will only see the beacon when it moves.

Falling – Again you can look at the xyz from a beacon accelerometer to determine a beacon is falling. Alternatively, you can use a more intelligent beacon such as the iBS01G that does this for you and just gives indications of a start/during/end of a fall as values in the advertising data.

Vibration – The xyz can be used to determine the degree of the movement and hence vibration.

Posture detection – This is more advanced analysis of the xyz that works out, for example, if someone is walking, running, sitting or standing. Another use is the analysis of sports (e.g. golf, squash, tennis, badminton) swings to determine the type of movement and score the movement.

There also scenarios outside the above that are also possible. For example, we had a customer wanting to know if their forklift truck hadn’t been moving for 2 minutes so as to make best use of it.

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Prognostics, Predictive Maintainance Using Sensor Beacons

A growing use of sensor beacons is in prognostics. Prognostics replaces human inspection with continuously automated monitoring. This cuts costs and potentially detects when things are about to fail rather than when they have failed. This makes processes proactive rather than reactive thus providing for smoother process planning and reducing the knock-on affects of failures. It can also reduce the need for over excessive and costly component replacement that’s sometimes used to reduce in-process failure.

Prognostics is implemented by examining the time series data from sensors, such as those monitoring temperature or vibration, in order to detect anomalies and make forecasts on the remaining useful life of components. The problems with analysing such data values are that they are usually complex and noisy.

Machine learning’s capacity to analyse very large amounts of high dimensional data can take prognostics to a new level. In some circumstances, adding in additional data such as audio and image data can enhance the capabilities and provide for continuously self-learning systems.

A downside of using machine learning is that it requires lots of data. This usually requires a gateway, smartphone, tablet or IoT Edge device to collect initial data. Once the data has been obtained, it need to be categorised, filtered and converted into a form suitable for machine learning. The machine learning results in a ‘model’ that can be used in production systems to provide for classification and prediction.

IoT Sensing Without Soldering

There are a lot of ways of doing sensing that mostly include development boards, wires and soldering. Even if you use prototyping or breadboards, your final solution is rarely ready for real use or production without then creating a custom electronics solution.

Sensor beacons provide for IoT sensing where all of the developed solution can be in software. The beacons send data via Bluetooth preventing the need for wires and soldering, even in production solutions. All you need is the receiving software in an app, laptop, desktop or other computer where you can receive data and if necessary send it on to servers.

What’s more, the use of low power Bluetooth allows you to place the sensors in locations where there’s no mains power. Batteries in the beacons can last 5 years or more depending on the sensor sampling frequency.

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Beacon Proximity and Sensing for the Internet of Things (IoT)

Machine Learning Sensor Data

Mobile World Live, the media arm of the GSMA, has a new article titled IoT data impossible to use without AI.

The article title is over-dramatic because IoT data can be used without AI. However, as the article goes on to say, AI is …

‘vital to unlocking the “true potential” of IoT’

… that has more truth.

As usual, these things are said with no example or context. Let’s look at a simple example.

Let’s say we want to use x y z accelerometer data from one of our sensor beacons to measure a person’s movement. If we wanted to know if the person is falling we could test for limits on the x y z. This doesn’t use AI. Now consider if we want to know if person is walking, standing, running, lying down (their ‘posture’). You can look at the data forever looking for right patterns of data. Even if you found a pattern, it probably wouldn’t work with a different person. AI machine learning provides a solution. A simplistic explanation is that it can take recordings of x y z of these postures from multiple people and create a model. This model can then be used with new data to classify the posture.

AI solves problems that previously seemed too complex and impossible to solve by humans. Solving such problems often improves efficiency, saves costs, increases competitiveness and can even create new intellectual property for your organisation.

However, don’t automatically turn to AI to make sense of sensor data. Don’t over-complicate things if the data can be analysed using conventional programming.

Machine Learning with Beacons

Advanced BlueUp BlueBeacon Sensor in Stock

We now stock the BlueUp BlueBeacon Sensor. This is one of the most capable sensor beacons we know of with up to 8 advertising slots. It detects temperature, humidity and air pressure. It also supports Quuppa and Eddystone GATT Service.

The two AA batteries (included) last 3.5 years with default settings.

Beacons and The 4th Industrial Revolution

We previously wrote about how beacons are part of Industry 4.0 and how implementations need to achieve a return on investment. Industry 4.0 is also being called ‘The 4th Industrial Revolution’ (4IR).

Oracle and the EEF have an excellent free, recent, paper (registration NOT required) on The 4th Industrial Revolution: A Primer for Manufacturers. It concludes 4IR isn’t hype and should be taken seriously. Here’s how manufacturers themselves see 4IR:

Manufacturing is undergoing a transformation. The report says it’s all about data connectivity. However, the report falls short on explaining how data can be sensed and captured. Sensor beacons, gateways and beacon platforms such as our BeaconRTLS are one such solution that helps fill that gap.

Read more about beacons and the IoT

Detecting Falling Using Beacons

Beacons can be used to detect when something is falling. The classic usecase is healthcare where patients can be monitored and an alert generated when they have fallen. However, fall detection can be used in other areas such as mountaineering and construction where human life is in jeopardy due to the high risk of a fall. It’s not just people that can be monitored. Fall detection can be used for valuable/fragile items in places such as warehouses, factories or even in transit.

Detecting falling uses an accelerometer in the beacon. Some sensor beacons generate x y z data that can be used to programatically detect the fall. The problem with this is you need relatively complex local processing such as a smartphone or single board computer to analyse the x y z data. A solution is the iBS01G that not only detects that the beacon is falling but also indicates when the beacon is moving, has gone from still to moving or moving back to still.

The advertising data event status shows the movement states:

The states can be logged or shown directly in an app or sent to a server via a WiFi gateway.

IoT Return on Investment for Industry

Mr Beacon has an interesting new interview with Sam Jha, Chief Business Officer of Alpha Ori. Alpha Ori work with the shipping industry that’s still lacking the productivity gains many other industries have experienced through the use of IT. While the interview talks about shipping, it’s equally applicable to all industries.

In the shipping industry, IoT can be used to measure ships’ systems. This can produce thousands of data points per second that can be analysed using ‘big data’ techniques. The key is to identify insights that have value in that they can impact the areas where there are large costs. An example is maintaining up time and using sensing to estimate the life remaining on machinery, detect when things are starting to fail and replace preventative maintenance with predictive and prescriptive maintenance. Better maintained ships can also have the side affect of reducing other costs. Smart ships have lower insurance risk profiles and can hence save insurance costs.

The key message is one of identifying areas where there are large costs and using IT to optimise those areas. In shipping or any industry this usually involves sensing on machinery and systems to maintain optimum up time. It also involves detecting when to perform in-time maintenance to get the maximum life from expensive machinery. Beacons, particularly sensor beacons, provide the sensing part and are especially suitable for areas that don’t have power, lack cabling or are difficult to monitor manually due to accessibility.

Read about beacons and the IoT

Bluetooth Beacons in Factories, IoT and Industry 4.0

McKinsey has a useful chart where they assess the potential impact of the IoT by segment:

It can be seen that ‘Factory’ has the greatest potential. This links with ‘Industry 4.0‘, the current trend for more automation and data exchange in manufacturing with the aim of significantly improving efficiency. But what does this mean in practice and what are challenges? Can these be solved with Bluetooth beacons?

We have learnt that while just about every industry client has different needs, all solutions involve context and location. Context is sensing, while location is where the sensing occurs.

Requirements we have experienced range from being able to pick up documents for particular machinery through to actual sensing such as detecting vibration is within (safety) bounds for ‘aggressive’ equipment. We have also seen the requirement for matching workers with workstations and jobs as well as the tracking of workers, tools, pallets, parts and fabrications. There’s also the need for real-time overviews for short term safety and efficiency management, the same longer term data also being used for process improvement and planning.

So why beacons?

  1. Low power. Sensors need to have a long life because replacing them or their batteries requires human effort and they are sometimes placed in normally inaccessible and dangerous areas. Beacons are ideal for this because some have up to 5+ years battery life and others can be permanently powered.
  2. Sensing. Various off the shelf sensor beacons are available. Custom variants are possible to sense industry specific metrics.
  3. Connectivity. Several gateways are available to connect to WiFi. Alternatively, it’s possible to use smartphones or small single board computers as gateways. There’s a trend for ‘Fog’ or ‘Edge’ gateways that only send pertinent data on to the cloud and can provide direct alerts quicker than being dependent on the latency of the cloud.
  4. Cloud management. Software such as our BeaconRTLS platform allows for the management and visualisation of sensors.
  5. Security. Beacon devices are password protected and the gateway to cloud communication is protected using standard Internet protocols.
  6. IoT needs to be made easy. This is BeaconZone’s role. As we mentioned, with the IoT every client has different needs. We bring together ready-made hardware and software components so that they can be dovetailed to create solutions.

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

Read about BluetoothLocationEngine™