The explosion in interest in the Industrial Internet of Things (IIoT), including in sectors such as manufacturing and agriculture, is forecast to result in tens of billions of connected devices by the year 2020. However, deploying devices is not sufficient to create integrated systems returning maximum value to the industry. A coordinated communications system, combined with appropriate analytical and graphical output, as well as mobile device integration for knowledge dissemination is necessary to realise the full potential of the installation.
Connected intelligent networking
At COMAND, we have experienced distributed systems researchers looking at ways to provide an intelligent network to allow interoperability and autonomy of connected devices – irrespective of manufacturer, communications protocol or data types. By moving the intelligence into the network itself, we provide the scaleability required to handle potentially millions of always-on connections without congestion or lost data.
Within a distributed intelligent system, data analysis can be done wherever it is most appropriate – whether that is in the centralised core, at the network edges closer to the devices, or on the device gateways themselves. This versatility improves scaleability, reduces latency in the system, and can enable peer-to-peer (P2P) communication between devices or sub-systems.
Data visualisation, analysis and feedback
In addition to the collection and analysis of IIoT data, we have developed real-time dashboard data visualisation systems that allow real time monitoring and interpretation by human operators of system state – enabling rapid manual intervention or system tuning.
Dissemination of data analysis results, notifications or alarms to mobile devices can provide the end-to-end solution required by industrial operators for effectively managing a facility. We have developed cross-platform mobile device applications to both display the necessary information and allow interaction by the operator; providing manual feedback control of the system.
Automatic feedback (or closed-loop) systems (where the system is directly controlled as a result of data-analysis, without human intervention) are also possible. However, factors such as health and safety requirements, as well as the possibility of damaging valuable equipment, restricts the scale of any such system that can be achieved within the scope of a proof-of-concept.
Some examples from COMAND
1) Industrial machine tool monitoring system
We are currently investigating a manufacturing device data visualisation system to monitor the performance of an industrial moulding process, which would provide feedback to operators of the performance and accuracy of machine tools and signal in real time any deviation from normal working parameters. The factory data for visualisation, collected from machine tools and PLCs, can ultimately be fed into an analysis system to monitor the long-term performance of the moulding process and equipment, as well as other benefits such as preventive maintenance programmes.
2) Agricultural cattle feed dispensing system
As part of a cattle feed dispensing apparatus, we have developed a closed-loop system combining volume sensors with dispensing actuators to provide appropriate levels of feed with reference to a pre-programmed schedule or calendar. The system is designed to run automatically, but with the ability of the farmer to monitor progress and intervene if necessary through use of a cross-platform mobile application which can override the automatic functionality.
Working with COMAND
The COMAND Technology Gateway offers a flexible team of researchers encompassing a broad range of applicable knowledge in the field of connected media applications in distributed environments. We provide clients with a professional and effective asset in the specification and development of innovative solutions to technical problems.
About the author
COMAND Technology Gateway Manager