Top Four Ways Fleets Can Benefit from Edge Analytics

Top Four Ways Fleets Can Benefit from Edge Analytics

In an earlier blog post, we detailed what edge analytics is and how it differs from traditional data analysis. To recap, unlike traditional methods that send data back to the cloud for processing, edge analytics enables data processing as close as possible to the data source.

 

As the amount of data generated by the transportation industry continues to increase — by way of smarter engines, more vehicle sensors and in-cab devices — fleets have started to turn to edge analytics as a way to better manage this vast amount of information and make smarter, data-driven decisions.

 

Here are a few of the ways edge analytics transforms how fleets operate:

 

1. Predicting breakdowns

 

Imagine if a truck was able to tell a driver immediately if a part was going to fail, not based on aggregate or average fleet data but based on individualized data from his or her truck, driving conditions and driver behavior. The driver could quickly plan for that repair and get it fixed before it becomes a problem.

In traditional computing methods, real-time maintenance information would first go to the back-office staff, who would then communicate the need for a repair to the driver. In a situation where delivery schedules are of utmost importance to maintain, edge analytics can inform drivers more quickly about impending maintenance events so that the right course of action can be taken faster.

 

2. Detecting driver fatigue and distracted driving

Video solutions are growing in popularity in the trucking industry – as is the amount of data collected from these videos. There is a growing need for the ability to quickly analyze and process videos – not just what the videos show, but what drivers should do in response.

Edge analytics can be used to detect driver fatigue or distracted driving by analyzing patterns in collected video data, such as drifting across lanes. In a scenario where major damage could be caused in just a matter of seconds, being able to analyze data in real time and provide actionable insights – such as alerting the driver to pull over to rest – is absolutely critical to the safety of everyone on the road.

 

3. Preventing collisions

Another video application could be the ability to detect and avoid potential collisions in real time, such as identifying if a driver is following too close to a vehicle and alerting them to reduce speed.

 

edge-analytics-truck

Edge analytics can alert a driver in real-time to adjust driving behavior to reduce the risk of a collision.

 

4. Managing data consumption

Just because data rates are becoming more affordable doesn’t mean you should collect data just for the sake of it. Data being transmitted for analysis can often be “noisy” – meaning that it contains irrelevant data points that obscure the important information. Edge computing can analyze this data at the source and make the determination if it is relevant or not and transmit only the important data, cutting down on the amount of this “noisy” data being transmitted.

Take for an example if a fleet has a video solution installed that captures a “ potential collision” that, in reality, only happens to be that the truck passed by a large billboard. By determining the relevance of this video on the edge, it not only cuts down on the data usage required to transmit this clip but also spares the time back office personnel would waste reviewing an irrelevant video.

 

As technologies evolve, the potential applications of edge computing will continue to expand. Download our free whitepaper on edge analytics to discover how it works and how to apply it to your organization.

 

At Trimble, we are building solutions with emerging technologies like edge analytics in mind. Contact us today to learn more about how our forward-facing view of technology can help your fleet operate more safely and efficiently, both today and in the future.

Top Four Ways Fleets Can Benefit from Edge Analytics

In an earlier blog post, we detailed what edge analytics is and how it differs from traditional data analysis. To recap, unlike traditional methods that send data back to the cloud for processing, edge analytics enables data processing as close as possible to the data source.

 

As the amount of data generated by the transportation industry continues to increase — by way of smarter engines, more vehicle sensors and in-cab devices — fleets have started to turn to edge analytics as a way to better manage this vast amount of information and make smarter, data-driven decisions.

 

Here are a few of the ways edge analytics transforms how fleets operate:

 

1. Predicting breakdowns

 

Imagine if a truck was able to tell a driver immediately if a part was going to fail, not based on aggregate or average fleet data but based on individualized data from his or her truck, driving conditions and driver behavior. The driver could quickly plan for that repair and get it fixed before it becomes a problem.

In traditional computing methods, real-time maintenance information would first go to the back-office staff, who would then communicate the need for a repair to the driver. In a situation where delivery schedules are of utmost importance to maintain, edge analytics can inform drivers more quickly about impending maintenance events so that the right course of action can be taken faster.

 

2. Detecting driver fatigue and distracted driving

Video solutions are growing in popularity in the trucking industry – as is the amount of data collected from these videos. There is a growing need for the ability to quickly analyze and process videos – not just what the videos show, but what drivers should do in response.

Edge analytics can be used to detect driver fatigue or distracted driving by analyzing patterns in collected video data, such as drifting across lanes. In a scenario where major damage could be caused in just a matter of seconds, being able to analyze data in real time and provide actionable insights – such as alerting the driver to pull over to rest – is absolutely critical to the safety of everyone on the road.

 

3. Preventing collisions

Another video application could be the ability to detect and avoid potential collisions in real time, such as identifying if a driver is following too close to a vehicle and alerting them to reduce speed.

 

edge-analytics-truck

Edge analytics can alert a driver in real-time to adjust driving behavior to reduce the risk of a collision.

 

4. Managing data consumption

Just because data rates are becoming more affordable doesn’t mean you should collect data just for the sake of it. Data being transmitted for analysis can often be “noisy” – meaning that it contains irrelevant data points that obscure the important information. Edge computing can analyze this data at the source and make the determination if it is relevant or not and transmit only the important data, cutting down on the amount of this “noisy” data being transmitted.

Take for an example if a fleet has a video solution installed that captures a “ potential collision” that, in reality, only happens to be that the truck passed by a large billboard. By determining the relevance of this video on the edge, it not only cuts down on the data usage required to transmit this clip but also spares the time back office personnel would waste reviewing an irrelevant video.

 

As technologies evolve, the potential applications of edge computing will continue to expand. Download our free whitepaper on edge analytics to discover how it works and how to apply it to your organization.

 

At Trimble, we are building solutions with emerging technologies like edge analytics in mind. Contact us today to learn more about how our forward-facing view of technology can help your fleet operate more safely and efficiently, both today and in the future.

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