Internet of Things is a popular concept that provides connectivity between sensors or devices and everyday objects. It enables them to communicate with each other or with higher layers by sending and receiving data. We used machine learning algorithms on top of the large sets of data, that are produced by the sensors, to create an algorithm for our client’s IoT solution. The specific data aggregation, analytics, and data clustering solved the problem and helped our client to improve their product. Implementation of the algorithm is delivered as a smart component and can be used in many of our client’s use cases.
Info
Machine learning algorithm for an IoT solution
- Services: Smart component for an IoT solution based on a machine learning algorithm.
Technologies we used
Python & Numpy
In combination with its library NumPy, specialised for scientific computing, Python is a very common solution for solving data problems end-to-end. Also, since it's very easy to use, the community is growing fast.
Spring Framework
The backend component of the application was developed using the Spring Framework.
MongoDB
NoSQL document-oriented database is a very suitable solution for aggregating lots of unstructured sensor data.