When the data from the selected points has been collected and forwarded via data communication connections, the following technology layer of the industrial IoT is a combination of centralised data collection, storage and situational awareness.
The nature of the information on the internet has changed radically during the course of the 2000s. As recently as in the 1990s, all of the information on the internet was, in essence, produced by humans alone. Now, automatic data collection processes generate data for the use of situational awareness and analysis software. Data is collected on companies’ business processes, environmental conditions, the operations of devices and machines, and on customer, competitor and consumer behaviour, for example.
Data collection software gathers data into enormous data repositories (big data), which compile a centralised view – or a real-time situational awareness – of the data. The situational picture can be viewed by people, but increasingly often, the collected data and the situational awareness formed from it are used for the purposes of yet again new software, which responds to changes taking place in the situational awareness. Furthermore, new software can produce forecasts on future events with the help of anticipatory algorithms and, when necessary, automatically intervene in measurable processes or produce information for decision-making purposes.
At the start of the millennium, practically all of the information on the internet was produced by humans. Now, the majority of all new information is generated by sensors and devices.
CENTRALISED SITUATIONAL AWARENESS IS NEARLY ALWAYS A PART OF NODEON’S SCOPE OF DELIVERY
The data gathering, control and management systems delivered by Nodeon nearly always include a layer of centralised data collection and a situational awareness system. Critical infrastructure systems are very often about the creation of real-time situational pictures that are as accurate as possible and about responding to abnormal events.
Nodeon has the extensive experience necessary to implement centralised situational awareness systems with diverse methods and technologies. We are used to implementing systems within traditional server environments and on cloud platforms or with SCADA (Supervisory Control and Data Acquisition) systems based on automation technologies. The list below describes tasks and properties related to the creation of situational awareness systems we are familiar with:
- Centralised data collection
- Database architectures
- Real-time situational awareness
- Visualisation of situational awareness
- Map-based presentation of data
- Extensive reporting features
- Data analytics