Industrial

Industrial Use Case

Key Terms

Ultrasound

Direct to Consumer

Monitoring

Smartphone App

Bluetooth

WiFi

Preventative Maintenance

Predictive Maintenance

Low Cost, Distributed Sensors

Data security

This industrial device company has developed a networked ultrasound fluid level monitoring system designed for vehicles that use hydraulic fluid for accessory operations.  A typical vehicle is a farm tractor with multiple hydraulic lifts and compression systems.

Hydraulic fluid tank level can be measured using a conventional float arm which is linked to a dashboard gage.  Low fluid level must be realized by the driver who may not notice the level because they are operating the vehicle and needing to operate various accessories.

By placing a low cost ultrasound sensor with a wifi chip set on the tank filler cap, the fluid level can be monitored with the data sent to the smartphone of the operator via Bluetooth.  The data received by the smartphone would be held for initial analysis by a CAID© app with the option to immediately sound an audio, visual and vibrating alerts to the operator if a low fluid condition occurs.  Periodically the data would be uploaded via WiFi or cellular data to the cloud for identification prior to admission to the Certified AI database.

A similar sensor and transmission method can also be used with coolant and fuel systems.

The accumulated data can then be used to analyze the use and stress patterns and issue maintenance recommendations to the operator via the smartphone.  The goal of the AI system is to monitor key systems for symptoms that indicate a pending failure so it can be address as scheduled maintenance rather than an expensive in field repair.  

It is important to note that farm tractors have very high demand during certain time periods such as harvest.  These time periods are often a function of weather and cannot be precisely determined.  An additional function of the AI system is to evaluate location specific weather and weather patterns to determine potential high use periods and schedule maintenance prior to a probable critical use period.  This calculation would include anticipated use and not just the current maintenance need.

Additional factors would include estimated time for harvest over the known area, historical time necessary for the harvest and the probability of the existing equipment suitability for the time and capability for the estimated tasks.

The accumulated data as well as new data provides detailed information on planned harvest which has an economic value to both the buyer and seller.  That information is intended to benefit the seller or producer of the crop.  Conversely, making the data available to the buyer would be detrimental to the seller.  Therefore the benefit of having the AI insights into the harvest should be protected which would be a primary function of holding that data in a Certified AI Database©.

Summary

Combining equipment use history via consumable fluids is an opportunity for predictive maintenance which would lower the cost of crop production in farming.   This cost reduction would benefit food supply by eventually lowering food costs.  This can be accomplished using low cost distributed sensors that are easily attached to the farm tractor by the operator.

Data is collected via the operators smartphone using an app.  This data would be Certified for use in an AI system.