A road to sustainability via remote monitoring efficiency

Cloud Computing Infrastructure provides the means for scalable storage and processing of data from multiple IoT devices. As there is a need for processing sensor data close to the field because real-time detection of problems is required, edge and fog computing devices can be employed to enable data analysis close to the field.

Most remote monitoring extracts insights on the condition of the various assets and processes based on the analysis of large volumes of data by means of IoT analytics algorithms, which include machine learning and artificial intelligence techniques. Data Visualization Dashboards enable the visualisation of elements that present insights to end-users whilst for Augmented Reality (AR) and Mixed Reality (MR) remotely collected data can be used to build ergonomic cyber-representation of assets and processes based on these technologies.

The synergy of these data collecting, processing and visualising technologies allows for Telent to make asset monitoring a far more efficient, sustainable, and effective task.

Remote monitoring enables remote inspections. Remote inspections reduce the need for hands-on work. In many cases, data that would be otherwise gathered manually can be monitored and analysed off-site.

With a significant skills gap in qualified personnel for processes like inspections, maintenance, and engineering service, remote monitoring reduces the number of personnel that must be deployed in physical locations. It also provides more flexibility in planning hands-on processes.

Remote monitoring also enables organizations to integrate information about many assets and processes, regardless of time and the location of the assets. In this way, a customer gains a 360-degree view of their operations and optimizes their management. Thanks to remote management, an operator is no longer bound to a local view of their assets and processes. Rather, they can instantly consolidate information about the performance of the organization while calculating relevant KPIs (Key Performance Indicators) like Overall Equipment Efficiency (OEE) and total carbon (CO2) emissions.