Scaling Industrial IoT and AI apps – What is the biggest challenge faced?

Most of the industrial enterprises deployed with Internet of Things (IoT) continue to see radical improvements within manufacturing and logistics operations. Industrial Internet of Things (IIoT) being elemental in data journey from edge to Artificial Intelligence (AI) acts as a core of digital transformation. However, the transformation is critical with broad sets of data required to create AI/Machine Learning (ML) capabilities with clear and measurable benefits. With different assets and numerous devices from various manufacturers within an industry, collecting the data; integrating the data and then normalizing it for applications can be an alarming task. Some of the successful IIoT applications in production industries includes: asset monitoring, energy management and predictive maintenance. Today, let us check out on how to address the biggest challenge faced in scaling industrial IoT and AI applications – data acquisition and integration.
Automated data acquisition improves Return on Investment (ROI):
Data acquisition being a tedious task, many industries go for third-party solutions on data integration support. While choosing the support solutions it is essential to consider some features which includes:
1. Regardless to complex asset integration, the solution should scale up on time
2. Should offer a consolidated data layer between Operational Technology (OT) assets and IT applications to make the asset data usable for all applications
3. Should provide an instant and user-friendly interface for the users to integrate assets into their applications in a few steps
4. Should be able to merge data assets to a specific model with data labels, units and scaling so the data can be used by IoT applications immediately
Scaling more data per day:
The main reason why scaling AI is so challenging is often associated with customization and data. A manufacturing company aims to increase the uptime in production with low running cost. This can be achieved with the collection of large data from various machineries within the asset. Scaling AI entails tools and workflows, for a wide collaboration between between development, data science, and data capabilities such as CloudOps, DevOps. Essentially it becomes important for an industrial enterprise to look out for a third party solution that can customize their solution according to needs with optimal performance.
Sterison – Data acquisition; integration & AI scaling and IIoT applications:
Looking for perfect third party solution for data acquisition and integration? No matter how large your data is, Sterison Technology Pvt. Ltd., with complete package of data engineering services offers reliable output of data collection and integration which may be structured, unstructured or semi-structured. As a result industrial enterprises can collect real time data without any downtime from installing a new solution.
Sterison pipelines the data from various sources like conveyors, variable frequency drives and air handling units and finally serves to enterprise level with AI-powered remote asset monitoring application which allows the maintenance teams to predict and prevent any issues without downtime. It significantly becomes more important as the data can be monitored on a fast pace and with the inclusion of all enterprise assets.
The challenge faced in scaling Industrial IoT and AI applications on data acquisition and integration can be addressed with the data engineering technology from Sterison Technology Pvt. Ltd. With complete knowledge in AI development and IIoT applications, Sterison can customize your need boosting your business in terms of cost and time effectiveness, productivity & profitability.