Improving your fleet's driving performance, safety and efficiency.
Fleet monitoring and management is difficult: how do you maximize the availability of your trucks, ensure that you meet customer schedules and protect the safety of your drivers and vehicles within a tight budget when all of your assets are normally out of view?
Ensuring the maximum utilization of your assets is therefore key, but if you are carrying out maintenance on a scheduled basis, your vehicles might be spending more time off the roads than they need to. Worse still, you might not identify a problem until it is too late and a failure occurs.
Rayven’s Truck Health, Predictive Maintenance & Compliance Fleet Monitoring AI + IoT solution enabled one business to achieve it all – and more.
Understand truck health and compliance through fleet monitoring.
Helping fleet managers to overcome these issues requires a combination of near real-time (CANBus, OBD-II and GPS) data, external mapping and maintenance data, and clever algorithms to help pin-point those drivers or vehicles that need attention. For example, we developed a driver efficiency metric, which combined vehicle engine and transmission data with GPS information and fuel prices.
The solution enables truck manufacturers and those responsible for fleet monitoring and management to focus their efforts on improving driver safety, decreasing spend on fuel and maintenance, and reducing overall vehicle downtime.
Defining what data to collect is critical
To develop the new data capture functionality, Rayven firstly investigated the optimal process for extracting data from truck telematic systems. After investigation with the telematics supplier and vehicle manufacturers, we found that extracting data from each vehicle directly via 4G to the cloud was the best way to send data to ensure the minimum loss of data from the trucks to the cloud. This would allow for data to be collected that records:
- Brake usage – counts and overall distance
- Clutch usage and gear changes
- RPM and gear usage
- Trip speeds and idle times
- Engine status
- DEF (e.g. AdBlue) level
- Coolant temperature
- Coast distance
- Fuel consumption in litres and dollars
Initial goals of the solution
The first goal of this solution was to connect the thousands of trucks to the Rayven cloud and ensure data quality and integrity by providing the following abilities to:
- Monitor critical operational truck data received from telemetry via a web-based system
- Define business logic to the application in order to meet the business objectives
- Provide alarm and alert notifications via email or SMS messages
- Collect enough historical data to enable the ability to test different logic to diagnose faults
- Provide the right dashboard to the right user with the right insights across multiple fleets and truck makes
- Test the application, making sure all of the above goals are met, based on the below solution architecture
Before go-live, we tested four critical aspects of the solution:
The Rayven AI + IoT platform is built with security as a top priority and our proprietary security architecture ensures that data is secure at all points of the environment.
The solution includes data encryption in transit from device-to-cloud, as well as device authentication; security (Bearer) tokens; SSL, AES and RSA encryption; as well as additional device security checks done via automated polling.
Once all the vehicle telemetry was connected and data was flowing via 4G to the cloud through a secure and encrypted transmission path, work was done to test back-filling data which was saved on the edge when the transmission of data wasn’t possible in remote areas.
To ensure the data we being received by the AI + IoT platform was current, it was necessary for us to compare the telemetry data with the dashboards and to construct functionality to back-fill data in the event that communication was ever lost. This process is important to ensure data integrity, so that sound business decisions could be made by fleet managers.
Industrial data science
The objective of exploratory data analysis was to create a predictive maintenance machine learning data model, which included:
- Fleet comparison of the maintenance status of all trucks in the fleet
- The contribution of hauled-mass to the need for maintenance
- Alerts and automated reporting of trucks most in need of maintenance
- Overall fleet health and performance insights
- Event management of maintenance activity
We continue to add vehicles to the platform and work on improving on our maintenance forecasting capabilities. In addition, we plan to add maintenance history records to improve our predictive maintenance modelling.
Data sources used to deliver the Truck Health, Predictive Maintenance & Compliance Fleet Monitoring AI + IoT solution.
New and existing data was used to create the custom applications and business insights that come from our Truck Health, Predictive Maintenance & Compliance Fleet Monitoring AI + IoT solution.
Key features of our Truck Health, Predictive Maintenance & Compliance Fleet Monitoring AI + IoT solution.
A well-maintained fleet helps you meet health and safety compliance.
Real-time fleet health
Monitor every vehicle in your fleet in real-time, focus on the critical few issues and drill down to see the data you need to make decisions.
Alerts and notifications
Receive real-time alerts and notifications (via email or SMS) about breaches of critical metrics – speeding, low coolant or DEF levels, breakdowns and so on.
Device management monitoring
Monitor and manage you telematic devices at scale and identify where telemetry head units require maintenance or replacement.
Incident and issue records
Receive immediate notification if an accident or breakdown occurs, including the location and load details.
Predict when maintenance will be needed based on individual vehicle usage, how it’s been driven, its make and maintenance records.
Knowing when an accident occurs is critical, but preventing it is even better, so understanding who is most likely to be involved and when the next one might happen can help you to prevent and prepare for them.
The business outcomes from our Truck Health, Predictive Maintenance & Compliance Fleet Monitoring AI + IoT solution.
Lower cost of maintenance
Scheduled vehicle maintenance can mean taking vehicles off the road unnecessarily. It can also reduce your flexibility to maintain fleet uptime. Predicting when action is required can help reduce the opportunity cost of having a vehicle off the road.
Transport regulation compliance
Fleet managers are increasingly responsible for the safety and safe actions of their drivers. Improve compliance by implementing targeted actions to improve daily driving time, speeding, overweight loads and other hazards and maintain records of continuous improvement.
Reduce downtime from unnecessary scheduled maintenance or because of unexpected vehicle failures through better-planned maintenance scheduling.
Renewal of maintenance contracts
With better information about vehicle usage, upkeep, and maintenance, you will have what you need to reduce your vehicle maintenance outlays
Reduced number of collisions
With better maintenance as well as the real-time and historical monitoring of driver performance, you are able to prevent collisions and accidents.
Create custom reports and dashboards that automatically populate and are distributed to interested parties with little-to-no effort.
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Pricing & plans
Simple, fair pricing that scales with your business model.
Rayven integrates with any asset, device or system.
Create custom solutions in weeks not months.
Discover opportunities for business improvement.