Different kind of motion sensors, like accelerometers and gyroscopes are available in wide varieties. They are usually very cheap, consuming little power, and are now embedded to our daily devices. These sensors have the capability of sensing our motion, but unfortunately not widely used.
We want to provide technology to make motion sensor data more usable and meaningful for further decision making. We strongly believe, that a business or benefit driven approach for any data analysis drives the digitalization in the most efficient way.
Our approach towards motion sensor analysis can be divided in three main areas:
- Data Cleaning: Raw motion sensor data is usually buried with noise, like gravity and spontaneous user or environment based interactions. Efficient data cleaning provides the basis for further data analysis
- Transport Mode Detection (TMD): Recognizing the mode of transport based on acceleration and deceleration profiles. Detection between different modalities, especially motorized and non-motorized, is fundamental for further analysis needs and requirements. Notable thing is also that new modalities can be added based on the market needs. For example detecting a car detection mode can be further divided by car models.
- Advanced Motion Analytics (AMA): After recognizing the mode of transport, dataset can be recorded and analyzed for example evaluating driving behaviour skills or performance in sports.
When combining large datasets, we are able to open new perspectives and insights from the data. This includes, for example, monitoring of road and vehicle conditions and improving their predictive maintenance, or how people are using different means of transport in the cities, and measuring driving behaviour and matching it with weather conditions
Welcome to the world of motion sensing!