With IoT sensors and connectivity becoming more mainstream, more and more data is being captured. The questions is: what are you going to do with all this data?
Our IoT platform is where it all started for TimeSeries. Our IoT platform is able to process billions of measurements from IoT devices. With IoT sensors and connectivity becoming mainstream, we capture more and more data from an unlimited number of devices. With connected cars, machines, watches and even toasters, the amount of data is ever increasing. The question is: how can you create valuable information from all this data?
Different types of data
We can process any amount and type of data with our IoT Platform. Whether it is data from consumer devices, machines or valuable equipment from inside a factory; TimeSeries has a solution to receive, process and analyze this data. Our IoT Platform can process in real time with configurable boundaries or other settings that alert you or your system only if necessary. With Machine Learning, patterns in data can be recognized and you can become smarter and more effective in your work.
The true power of our IoT Platform is that we can develop custom solutions that fit your specific needs. If you are currently working with a Commercial Of The Shelf (COTS) solution think about what it would mean if all your requirements could be met. If you could add a sequence to your planning tickets, certain movements of machines, a different measurement type like air pressure or a whole different information source like weather data to your current dataset. Your uniqueness as an organization is what made you successful and this requires different data insights.
Some of the standard features of this solution include:
- Scalable ingestion: horizontally scalable ingestion mechanism
- Scalable storage: horizontally scalable timeseries storage
- Multi source: adding and combining different data sources to generate insights
- Validation: pluggable validation process
- Interpolation: fill in the gaps when data is missing
- Consolidation: drill up and down in time, i.e. from 15 minute values to hourly, daily, etc.
- Aggregation: benchmark data from consumers within their peer groups
- Multi site benchmarking: comparing energy usage of different locations for companies
- Analytics: analyze incoming timeseries in real-time