C3.ai Sensor Health
Manage sensor health for smart meters
C3.ai Sensor Health
Manage sensor health for medical devices
C3.ai Sensor Health
Manage sensor health for pipelines
C3.ai Sensor Health
Manage sensor health for refineries
Ensure Optimal Deployment and Operational Health of IoT Sensor Devices
C3.ai Sensor Health™ ensures the operational effectiveness of IoT devices and network infrastructure during both the deployment and the operational life cycle of IoT devices.
Features
Executive dashboard
Visualize sensor status, deployment progress, and geographic regions of concern, and access a prioritized view of sensors with identified health issues.
Sensor deployment
Identify sensor deployment issues, diagnose the source of sensor malfunctions, optimize field service, and forecast future deployment progress.
Sensor device reconciliation
Ensure device installation information is correct, consistent, and current across source and cloud data systems.
Health and sensor exceptions
Monitor and analyze physical integrity, functionality, and communication of sensor devices to optimize field service and issue resolution.
Geospatial intelligence
Visualize planned sensor deployment, actual deployment and provisioning progress, device operational issues and trends, and service work priorities.
Reporting and ad hoc analyses
Present analyses and summarize results using preformatted and custom reports, including failure analysis, health analysis, identified and realized value, and financial performance against budget.
Testimonials
Dulce Borjas
VP and CIO, ENGIE North America
“ENGIE is looking to provide a zero-carbon future. The C3 AI Suite is important because it helps us build applications faster.”
Jeff Leonard
Systems Manager of Data Architecture
“We are currently ingesting a billion records a day. With that amount of data, I can’t imagine doing it on other technologies.”
Benefits
Analyze
Analyze sensor health data from multiple sources and systems, such as network communication, device data management, and customer systems.
Visualize
Visualize sensor deployment progress or health in an interactive, geospatial view of assets, device health metrics, and tool tips.
Access
Access network communication data to analyze, identify, and fix network problems and affected meters.
Identify
Identify root causes of failure and get recommendations to address them.
Create
Create a single, continuously updated, and prioritized work queue of installation and maintenance work orders to increase efficiency and effectiveness.
Locate
Locate sensors and remotely identify sensor configuration and location mismatches to ensure that the sensor is at the correct location and configured properly.
Assess
Assess device reconciliation issues to resolve errors related to provisioning errors and problems with customer, asset, or communications systems.
Prioritize
Generate a prioritized list of devices requiring field investigation or maintenance, with a health index score and supporting details to facilitate diagnosis or repair.
Track
Track performance reports of deployment and provisioning performance.
Reduce
Reduce operational expenses by reconciling installation and provisioning issues, improving office and field investigation efficiency, and isolating network problems.
Improve
Improve customer satisfaction through reduced device interruptions, rapid resolution of configuration issues, and improved service scheduling workflows.
Data Sources
C3.ai Sensor Health integrates and analyzes data from multiple disparate systems including IoT device data, head-end data from communication systems, asset management systems (AMS), global information systems (GIS), work order systems, customer relationship management systems (CRM), installation vendor data, and third-party data like weather information.
During sensor deployment, C3.ai Sensor Health identifies and reconciles problems, prioritizes remediation efforts, and enables the effective management of third-party vendors. During the ongoing operation of the sensor network, C3.ai Sensor Health uses advanced machine learning algorithms that continuously improve over time to identify sensor issues with increasing precision, predict sensor failures, and ensure the efficient operation of the sensor network.
Proven results in weeks, not years
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