New M52 Variants in Stock

We have some new variants of the Meeblue M52 available.

  • The M52-PIR is a sensor beacon with built in passive infrared (PIR) sensor. It can be used to detect room occupancy.
  • The M52-PA is a long range version of the M52 Plus. It uses an extra Bluetooth output amplifier to achieve a range up up to 170m.
  • The M52-SA Plus Waterproof is an IP68 version of the M52-SA Plus sensor beacon providing temperature, humidity (SHT20) and acceleration (LIS3DHTR) sensors. The humidity sensor obviously isn’t useful when the beacon is waterproof.

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New Meeblue Platform

Meeblue has a new platform for users of the W1 Bluetooth WiFi gateway. It’s designed to work with Meeblue sensor beacons to easily capture and view sensor data.

The platform is free to use and is publicly available. However, devices need be registered with the platform in advance. Requests can be made no more than once per second and you must use https.

Steps to set up the W1 gateway with the Meeblue platform

The API allows you to GET a gateway’s status, POST data from a gateway, GET a sensor device status, POST a sensor’s status, POST and GET sensor storage data.

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Using Bluetooth Sensor Beacons for AI Machine Learning

Sensor beacons provide a quick and easy way to obtain data for AI machine learning. They provide a way of measuring physical processes to provide for detection and prediction.

Beacon Temperature Sensor

Beacons detect movement (accelerometer), movement (started/stopped moving), button press, temperature, humidity, air pressure, light level, open/closed (magnetic hall effect), proximity (PIR), proximity (cm range), fall detection, smoke and natural gas. The open/closed (magnetic hall effect) is particularly useful as it can be used on a multitude of physical things for scenarios that require digitising counts, presence and physical status.

The data is sent via Bluetooth rather than via cables which means there’s no soldering or physical construction. The Bluetooth data can be read by smartphones, gateways or any devices that have Bluetooth LE. From there it can be stored in files for reading into machine learning.

Such data is often complex and it’s difficult for a human to devise a conventional programming algorithm to extract insights. This is where AI machine learning excels. In simple terms, it reads in recorded data to find patterns in the data. The result of this learning is a model. The model is then used during inference to classify or predict situations based on new incoming data.

The above shows some output from accelerometer data fed into one of our models. The numbers are distinct features found over the time series as opposed to a single x,y,z sample. For example ’54’ might be a peak and ’61’ a trough. More complex features are also detectable such as ‘120’ being the movement of the acceleration sensor in a circle. This is the basis for machine learning classification and detection.

It’s also possible to perform prediction. Performing additional machine learning (yes, machine learning on machine learning!) on the features to produce a new model tells us what usually happens after what. When we feed in new data to this model we can predict what is about to happen.

The problem with sensor data is there can be a lot of it. It’s inefficient and slow to detect events when this processing at the server. We create so called Edge solutions that do this processing closer to the place of detection.

Read more about SensorCognition

Easy IoT with Bluetooth Beacons

When people think about IoT sensors they tend to envisage, for experimenters, discrete electronic components connected to single board computers (SBC) or for industrial, custom sensors connected to microcontrollers.

The problem for experimenters is the solution is fragile and needs to be evolved into a custom electronic design before it can be used in production. For industrial solutions, they tend to be proprietary, require deeply invasive installation and very expensive.

Example IoT Dashboard Using Sensor Beacons

Sensor beacons provide an easy, ready-made solution that have the following advantages:

  • They provide a solution that’s equally as good for experimentation as it is for the final production
  • They require no soldering or electronics skills.
  • They can be placed in remote areas where there’s no power or network connectivity.
  • They can be self powered and last for 5+ years.
  • They can detect quantities such as position, movement, temperature, humidity, air pressure, light and magnetism (hall effect), proximity and heart rate.
  • They can be easily attached to existing to exiting assets to make them IoT enabled.
  • Being Bluetooth standards-based, the sensor data can be easily read via gateways, smartphone apps or single board computers and sent on, as necessary, to servers.
Bluetooth-WiFi Gateway

Using beacons sensors in this way also provides for the ‘big data’ required for AI machine learning.

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

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FedEx SenseAware Beacon

FedEx has started to use Bluetooth sensor beacons to track packages. The SenseAware ID device provides more frequent location updates and temperature, humidity and vibration data for premium packages.

SenseAware ID is part of the FedEx SenseAware offering that has previously used devices with cellular technologies. SenseAware ID devices are instead detected by gateways at UPS sites.

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Using iBeacon for Sensing in Viticulture

There’s new research by Sotirios Kontogiannis and Christodoulos Asiminidis of University of Ioannina, Greece on A Proposed Low-Cost Viticulture Stress Framework for Table Grape Varieties.

The system automatically monitors vine stress to provide real-time surveillance and alerts. It identifies specific areas for irrigation, thereby saving water, energy and time.

The Bluetooth iBeacon protocol is used to relay temperature, humidity, UV levels and soil moisture levels. The authors modified the standard iBeacon protocol, using the existing iBeacon minor and major fields to encode the telemetry data.

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Can Beacons Store Data?

Beacons don’t generally need to store data because they are just sending out their unique id. However, sensor beacons do sense values over time that you might want to collect later via, for example, an app coming close to the beacon. Specialist devices such as social distancing beacons need to store close contacts for later collection.

Beacons use a System on a Chip (SoC), such as the Nordic nRF51, that includes memory. Most of the memory is used for the internal functioning of the beacon. Newer versions of SoC, for example the Nordic nRF52, have more memory that allows data to be stored.

Temperature Logger Sensor
M52-SA Plus Temperature Logger Beacon

There are some sensor logger beacons that store sensor values but this tends to be restricted to temperature logging.