MOXA Simplify Connectivity for Predictive Maintenance

In order to achieve optimized results for predictive maintenance, it is critical to leverage edge computing capabilities to preprocess data from a diverse set of data sources. This data is acquired through a variety of sensors added to key components. Managers can implement appropriate measures in good time, be prepared for any event, and autonomously perform maintenance before machine failure truly occurs. However, you will face connectivity challenges to perform diverse data acquisition and deploy edge intelligence. What if we can simplify connectivity for you to acquire and preprocess diverse data?

Connectivity Challenge #2.1 Diverse Data Acquisition Makes Connectivity Complex

Problems Arduous programming efforts to realize edge-to-cloud connectivity from scratch Legacy PLC may not has the capability to communicate in cloud protocols such as MQTT

Connectivity Challenge #2.1

Diverse Data Acquisition Makes Connectivity Complex

Problems

Arduous programming efforts to realize edge-to-cloud connectivity from scratch
Legacy PLC may not has the capability to communicate in cloud protocols such as MQTT

Connectivity Challenge #2.2 Deploying Edge Intelligence Is Hard to Start With

Problems Edge computing in large-scale deployments requires more people and time to integrate, deploy, and redeploy devices

Connectivity Challenge #2.2

Deploying Edge Intelligence Is Hard to Start With

Problems

Edge computing in large-scale deployments requires more people and time to integrate, deploy, and redeploy devices

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