Processing IoT data

Assetwolf performs immediate calculations on data as it arrives; for example, if your device sends Fahrenheit, and you want Celsius, the data is immediately converted to the format you need.

Calculations are written in our easy-to-learn, IoT-dedicated scripting language called Phi.

Phi is simple to write and understand, and has a handy dry-run feature for testing.

It can do anything from simple arithmetic, to foreach-loops and if statements, and it can look up historical data from the current device or other devices, in order to perform smart calculations.

You can define trigger conditions for alarms. A trigger can be as simple as a sensor's measurement exceeding a numerical threshold, or it can use more complex rules.

Each kind of alarm has a severity level, so that more serious events are prioritised.

You can set procedures to determine what happens when an alarm is raised. AssetWolf can send an email or SMS, send a command to the asset, or make an API call.

You can set up metrics, i.e. key performance indicators that are measured on a regular basis, down to a 10-minute level of granularity.

Metrics can then be displayed on graphs and pie charts.

You may envisage your devices as sitting in logical groups: devices may be in rooms, rooms may be within defined areas of a building.

For example, instead of viewing individual device measurements, you may want to compile an average for each room, or an area.

With the Data Pools feature, you can arrange devices by multiple levels, such as rooms, floors, zones and locations. Whenever data arrives in from devices, it "bubbles up" through the hierarchy, triggering new calculations at the various data pool levels.