Our client is a telematics service used for truck fleet management. Technically, their solution is a mix of sophisticated software and hardware for collecting and analyzing critical information about vehicle and driver parameters in real-time, allowing customers to manage their fleet with a high degree of efficiency and at the lower cost.
The client strove to augment driver's safety and security and enhance the driving experience by digitally transforming its obsolete software into a modern
platform powered by AI, able to track the large number of fleet vehicles in real-time.
Our team designed and implemented different parts of the final product, including APIs,
web-interfaces and mobile apps, with the main challenge to create the system which receives the data from hundreds of thousands of monitoring devices in real-time, working 24/7.
Tracking a large vehicle fleet requires integration of large amounts of sensor data into a single pipeline.
Making tracked data available to compliance units within seamless interface, at a
Data has to be processed and accessible in near real-time fashion.
All the data is stored in the scalable cluster in a fault-tolerant manner (Cassandra).
The mobile app has a real-time access to the information from each connected monitoring device.
System automatically produces reports for each fleet vehicle, via collecting data from
analytical indicators built by our team.
Huge amounts of data are processed fast due to Apache Spark cluster; micro-services were built as an isolated Docker containers.
Metrics gathered in real-time are numerous and detailed (i.e. number of stops, start and end time of the journey, mileage, speed, idle time, route history, geofences, fuel consumption, engine temperature, etc.) They are used to create automatic alerts about accidents, critical situations, theft and other situations.
We have developed a sophisticated platform for collecting and analyzing critical information about vehicle and driver parameters in real-time.
The final solution allowed customers to manage their fleet with a high degree of efficiency and at a lower cost.
The platform receives the data from hundreds of thousands of monitoring devices in real-time, working 24/7.
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Yuliya is a co-founder and COO of DataRoot Labs, where she oversees operations, sales, communication, and Startup Venture Services. She brings onboard business and venture capital experience that she gained at a leading tech investment company in CEE, where she oversaw numerous deals and managed a portfolio across various tech niches including AI and IT service companies.