Understanding Sensor Beacon Accelerometer Data

In this post we will take a look at data from the INGICS iGS01RG beacon.

The x axis is time. You can see the x, y and z values, every 100ms, over time. The y axis is normalised between -1 and -1 for use in our SensorCognition Edge device. The chart is for when the beacon has been moving, followed by a stationary period. Notice how the orange line continues to show acceleration even though the beacon isn’t moving. This is caused by gravity.

In this chart the beacon has been flipped over and the orange line now shows a constant negative acceleration.

A good thing about the presence of a constant offset in one of the x y z inputs is that it can be used to help determine the orientation of the beacon. The less desirable aspect is that the offset significantly complicates using the x y z to determine types of movement such as human gestures.

Such complex data problems are more easily solved using AI machine learning than trying to write a traditional algorithm to make sense of the data.

Here’s an example of output from a SensorCognition Edge device trained with up and down movement and left and right movement. In this case, the output 227 is showing the beacon is moving left and right.

Read about SensorCognition

New Kaipule Bluetooth Sensors

We have a new range of Kaipule Bluetooth sensors that while intended for OEM alarm systems are stand-alone as regards Bluetooth. They are sensor beacons, sending out Bluetooth LE advertising when events occur.

There’s a gas detector, smoke detector, temperature/humidity sensor, water leak sensor, door sensor, PIR movement sensor and remote control.

Bluetooth Temperature/Humidity Sensor
Bluetooth PIR Sensor

All, apart from the remote control, have a low battery report when the battery is low and a heartbeat every 10 minutes.

The style and functionality of the Kaipule products make them particularly suited to smart building applications.