Fleet Performance Improvementby 6%
Improved Vehicle Maintenanceby 10%
Our state of-of-the art predictive algorithms can detect maintenance issues weeks in advance, thus reducing downtime, preventing road breakdowns and high operating expenses, and simultaneously improving driver safety. This predictive model provides real-time maintenance alerts and recommendations to mitigate
In order to perform analysis, we require telematics from your
If your vehicles are not yet connected to a telematics provider, you can get your fleet connected with our iotaSmart platform by mailing us at email@example.com or filling out the contact form
PredictEdge even allows seamless integration of other telematics platforms with no extra cost.
Register and create your iotaSmart account.
Later on, you can select if you want to use our telematics service or go through another platform via an API
With the data coming in, our AI makes use of data points such as driving behavior, terrain conditions, and emissions to generate any potential maintenance requirements and alerts. In addition, we also provide recommendations to mitigate such issues.
These alerts are organized in a convenient calendar format, ensuring on-time maintenance. With every new data point, the AI model gets smarter and more efficient at optimizing your fleet’s performance.
KPIs based analytics for informed and faster decision making.
Engine related issues based alarms on phone and email and predicting its failure.
Tracking the fuel efficiency by trip and providing recommendations for improvements.
Tracking driving behaviour by trip and trending for driver risk computations.
Tracking your vehicles by trip along with driving alarms and playing it back.
Real time monitoring, alarms, and trending for your vehicles.
• Loss due to improper dispatching and routing and unofficial vehicle use.
• Low vehicle utilization with unexpected breakdowns.
• Dispatching and routing optimization with real-time updates.
• Predictive maintenance calendar for on-time repairs and vehicle upkeep.
• Alert system in case of unofficial usage.
• Vehicle utilization improved by 65% leading to $275k per year.
• Advanced maintenance created $120k of savings each year.
• Improved staff productivity by 25%.
• Losing $90m per year due to low vehicle productivity and high fuel burn rate.
• High staff-to-bus ratio and low staff productivity.
• Past years' data compared with that of best in class.
• OBD devices connected to BS IV buses for real-time data collection.
• AI and Machine learning was applied to the operational and vehicle data for predictive maintenance and driving behaviour
• $6 mil savings I operating costs over two years.
• Improvements in vehicle productivity(10.9%), staff utilization(12%), fleet utilization(15.3%).
• Significant improvement in driving behavior.
Please fill the form below and we will call you to understand your requirements