Intel Case Studies Predictive Maintenance Drives Smarter Fleet Management
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Predictive Maintenance Drives Smarter Fleet Management

Predictive Maintenance Drives Smarter Fleet Management - Intel Industrial IoT Case Study
Functional Applications - Fleet Management Systems (FMS)
Functional Applications - Remote Monitoring & Control Systems
Networks & Connectivity - Gateways
Sensors - Pressure Sensors
Specialty Vehicles
Logistics & Transportation
Fleet Management

Fleet managers are turning to predictive analytics to stay on top of maintenance and mitigate part failures before they happen. However, managing the large amount of new data generated by vehicle sensors is challenging.

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Any organization that relies on vehicles in its daily operations understands how critical it is to keep them up and running. Whether it’s a delivery company, a school district, a telecommunications provider, or a municipality, productivity can come
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Predixion Insight* can analyze data either in the cloud or edge devices, reducing the volume of information that needs to be transmitted. Sensors on fleet vehicles collect data about tire pressure, hydraulics, and other parts. The data is sent to Intel®-based IoT gateways on the vehicle, which then process data at the edge for immediate alerts, or send it to the cloud for longer-term analysis. The integrated Wind River Helix* Device Cloud delivers centralized remote management with a cloud-based platform.

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Inventory Levels, Mileage, Parts Quality, Tire Pressure, Hydraulics
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[Cost Reduction - Maintenance]
Fleet managers can reduce the costs associated with maintenance, while gaining control of scheduling and inventory.
[Cost Reduction - Energy]
There are also smaller, but important, losses that can result from deferred maintenance—for example, reduced gas mileage
due to low tire pressure.
[Data Management - Data Analysis]
Data from these sources can be analyzed in real time on the
industrial gateway in the truck to alert drivers of imminent
failures, or pushed via the gateway to the cloud, for analysis
by corporate headquarters and operations.

Reducing data transmission costs

It processes and analyzes data in real time to provide immediate predictions as to pending failures.

Reduce downtime and slash maintenance costs

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