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Motorq

Examples that make a difference for your business.

Dealing in theory is always harder to understand. For that reason, we put together several real-world use cases to let you see just how Motorq can help you.

Use Case:Vehicle pre-delivery tracking

Track your vehicle being shipped.

You can track just about any package, even a $2 pack of gum, but not your multi-thousand-dollar vehicle. Motorq is changing that. By working with OEMs, we can track your vehicle from the factory to your hands, so you know where it is and when it will arrive.

Our inputs let you know when it’s on the factory lot, in transit on rail, on car carrier, and more. Then, we’ll let you know based on historical data, and adjusted for any weather days, exactly when your vehicle will arrive.

Use Case:Trip Analysis

Are your vehicles and drivers getting where they need to go?

Before, your driver would start the day with five stops in eight hours. How long he or she took at each stop, or the route they took, was unknown. But today. you can you track their entire trip. Motorq gives you consistent trip information to enhance not only your operations, but the safety of your drivers and vehicles.

Complete Analysis

From Trip Start to Trip Stop, you can monitor your vehicles in real-time.

Behavior Events

Receive real-time behavior event information. Know when you your driver is braking hard, accelerating too fast, and more to be able to identify and react to any sort of patterns or events.

Trip Path

Receive time and location points along the trip, encoded for optimizing each route.

Use Case:Fueling misuse exception reporting

Don’t pay for what you don’t use.

In the past, fleets have paid millions in fuel that never even made it into a company vehicle. Without knowing where your vehicle was, and when the gas tank was filling up, employees could skirt the system. But now, just a couple dollars a month can let you track exactly what’s going on with your fueling, virtually eliminating fuel fraud.

Vehicle Location

Is your vehicle near a gas station? If it’s not, it’s highly unlikely the right vehicle is being fueled up.

Gas tank levels

We record the amount of fuel in each vehicle. So, we know exactly how much needs to get filled and when. So, if someone is fueling a full tank, but they only need a half, you can be notified and take swift action.

Tools and reports

Lastly, we look at all of the data over time, identify any anomalies and summarize everything for you. So, when you have to have those sometimes uncomfortable conversations, you have the data to back you up.

Use Case:EV charging and distance optimizing

Predict your battery range.

Motorq is running a long-term analyses of EV battery performance. This allows us to tell you how your battery should be performing using varied inputs.

Charting factors such as daily range vs. battery usage, battery efficiency vs. vehicle speed, and battery efficiency vs. ambient temperature allows us to determine the best range of your vehicle. We can then cross-reference that with charging locations, distance, charging locations, and charge frequency so you get the most out of your battery every day.

Use Case:Geofencing

Monitor where your vehicles are.

By placing a polygon around the location you want a vehicle to stay in, you can be notified when that vehicle leaves its designated area. You’ll get inputs such as time in, time out, and the amount of time spent outside of the geofence. Then, we’ll look at past history to identify patterns so you can take swift action in dealing with the situation.

Use Case:Insurance driver safety scoring

Monitor driver behavior to predict repairs.

Motorq sorts through multiple data inputs, giving you the most accurate summary of how safe your drivers are on the road. And, we go even further using our Machine Learning to monitor that behavior over time and even predict when that behavior will lead to repairs so you can plan ahead and eliminate downtime.

1

Receive varied inputs

We receive inputs like hard acceleration, harsh braking, speeding, seatbelt violations and more and aggregate them from a variety of inputs.

2

Let the algorithm do the work

Then our algorithm assesses each input, giving you a trip-level assessment, event-level assessment and weighted composite score on a rolling distance basis. It even lets you customize it to your needs by allowing you to configure the thresholds.

3

Summarize for you

We then create a summary, highlighting percentages of each event and giving that driver a specific score. And we continue tracking it over time, so you can see where things improve and where things might need to be addressed.

Use Case:Predictive battery failure detection

Predict when a battery may fail.

Downtime is a four-letter word in your business. That’s why we leverage our Machine Learning to help you predict when your battery may fail in order to reduce downtime as much as possible.

By observing a vehicle’s battery voltage, ignition, speed, utilization, ambient temperature, and more, our Machine Learning models have been able to predict battery failure of tens of thousands of batteries to within days of the actual event.

This allows you to plan ahead and schedule maintenance on your terms, instead of leaving your drivers and customers high and dry. It’s one thing when it’s one battery, but multiply that by the hundreds of thousands of batteries you may change each year and those predictions could save you millions.