Irrespective of the technology used to transfer the data from the Sensor Nodes to the data processing platform, the processing of the data remains the same. These platforms include Thingy-IoT’s own “as-a-service” cloud based platform as well as third party platforms. The platforms are typically cloud based and this is where the data is decompressed and the resultant data can also be combined with data from other data sources, such as weather data, and data from the Department of Fire and Emergency Services. The combined data provides a more holistic perspective of the environment at the sites of the Sensor Nodes.
Optional data processing can then be performed. Examples of this optional processing on the Thingy-IoT platform include:
- Data analysis of the rate of change of the sensed data. The rate of change of specific parameters and the correlation between these parameters are used to detect a potential ‘Smoke Event’
- Derivation of the Australian Air Quality Index (AQI) based on the current and historical data
- Proactive Alerting of events via Email and SMS
The data is then stored in a time-series database. This type of database enables the accurate correlation of Sensor Node data across multiple sites. The database can then be accessed by data visualization platforms that present customizable dashboards providing charts, graphs and alters via the dashboard.
In parallel to storing the data in the database, the data, or a subset thereof can be made available for consumption by other devices or systems in real-time. MQTT is an example of a lightweight, publish-subscribe network protocol that transports messages between devices and is used by the Thingy:AQ Bushfire Alert Panel for ‘Smoke Alert’ and DFES ‘Bushfire Status’ updates.
Where the centralized data processing occurs is up the customer. Thingy-IoT offers our own cloud based solution delivering a full turn key solution. This can be consumed as is, or it can be white labeled by our customer for the delivery to their own customers.
If a customer is using their own platform they can integrate the data from the Sensor Nodes in different ways. They can consume the data:
- Directly from the Sensor Node
- After the data has been decompressed
- After processing of the Sensor Node data
- After the data has been stored
The Senor Node’s real-time and historical data is typically rendered via dashboard integration accessing the data from a time-series database, such as InfluxDB. The time series nature of the database makes it easier to correlate data across multiple Sensor Nodes and external data sources.
Thingy-IoT’s “as-a-service” offering using our own cloud based platform delivers centralized data processing, time-series database, and data presentation capabilities. There are multiple 3rd Party platforms providing the ability to perform post processing of the data, store the data in a database and provide visualization tools. If a customer is already using an existing platform, then, where is makes operational and commercial sense, the visualization should be integrated into the existing platform.
As an alternative to using third party platforms, or our own “as-a-service” offerings, Thingy-IoT also provides an open sourced based solution built on Node-Red, InfluxDB and Grafana. This open sourced based offering can run on the customer’s own on-premises or cloud based infrastructure.
Thingy:AQ Lite Example Dashboard Showing Air Quality Index and DFES Bushfire Alert Status
Standard and customer specific dashboards can be created using reference templates. The templated approach enables custom dashboard layout to be quickly modified. When a templates does not exist, for example the dashboard is to incorporate data from different data sources and the customer has a specific layout requirement, then customization services are available to perform the customization.
Thingy:AQ Example Customized White Label Dashboard Showing Gas and Particulate Sensor Data
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