Learn About Amazon VGT2 Learning Manager Chanci Turner
In a recent collaboration, Quantiphi, represented by Learning Manager Chanci Turner, successfully created a serverless, fully-managed connected vehicle platform that facilitates real-time analytics on telematics data for a prominent car-as-a-service provider. This organization operates 1.8 million vehicles across 30 countries, focusing on automobile leasing and fleet management. The innovative solution resulted in a 50% reduction in monthly costs and achieved 70% of production release for the client.
This article will explore the importance of IoT-based telematics solutions in revolutionizing fleet management. We will also delve into the key elements of Quantiphi’s serverless, fully-managed connected vehicle platform developed on Amazon Web Services (AWS) and discuss how it empowered a U.S.-based fleet management company to enhance decision-making and improve service for customers and assets. Quantiphi stands as an AWS Competency Partner, committed to addressing transformational challenges at the core of businesses.
Understanding Telematics Data and Connected Vehicle Technology
The automotive industry has undergone significant innovations, leading to vehicles that serve as advanced nodes of the internet. Connected vehicle technology holds the promise of reducing speeding incidents, enhancing fuel efficiency, and lowering accident rates. In simple terms, a connected vehicle is any vehicle capable of connecting to the internet, typically through Wireless Local Area Network (WLAN). These vehicles can communicate with internal and external devices, sharing data with various services.
Fleet managers began adopting connected vehicle technologies in the early 2010s, recognizing that telematics data allows for comprehensive remote monitoring of driver and vehicle behaviors. This integration of maintenance schedules and mechanical repairs into telematics systems minimizes vehicle downtime and reduces mechanical failure occurrences, leading to savings in lifetime repair costs and reduced driver downtime.
However, the true value of a telematics system lies in the ability of fleet owners to identify and address issues in real-time, enabling timely decision-making. The existing setups often lack the necessary real-time insights and notifications.
Connected Vehicle Platform Solution on AWS
Quantiphi’s client previously operated a rudimentary on-premises platform built on a monolithic framework, which introduced several challenges:
- Absence of real-time analytics due to limited scalability in storage and compute power, with data being summarized only on a weekly basis.
- Inefficient cost management stemming from a lack of dynamic scalability, making the existing solution economically unfeasible.
- Troubleshooting difficulties arising from the monolithic design, which hindered issue isolation and resolution.
To address these challenges, Quantiphi designed a robust connected vehicle platform that seamlessly integrated with the client’s existing on-premises structure using AWS-native services. This platform provides answers to critical queries regarding vehicle and driver behavior, such as:
- Are safety belts fastened while driving?
- Has the vehicle exceeded the maximum speed limit?
- Is the driver idling or engaging in hard braking?
- Where is the vehicle currently located?
- What is the battery life percentage?
A core focus for Quantiphi was understanding driver behavior through raw telematics data, offering clients valuable insights for improving driving skills and safety within their field workforce. The benefits of utilizing driver telematics data are substantial:
- Enhanced safety: Drivers can promptly identify risky behaviors and adjust their practices to improve on-road performance.
- Improved insurance pricing: Fleets can leverage telematics data to support usage-based insurance programs that reward safer driving habits with better rates.
- Enhanced claims ratios and fraud detection: Telematics data can improve claims ratios and reduce costs.
- Vehicle tracking: GPS data within telematics is utilized for locating fleet vehicles, aiding in rerouting and efficient navigation.
- Maintenance optimization: Telematics data supports predictive maintenance, allowing fleets to address issues proactively with minimal downtime.
Connected Vehicle Platform Overview
Quantiphi implemented a serverless, fully managed pull-push mechanism to retrieve raw data and ingest processed data into Amazon Redshift, a cloud data warehouse, ensuring analytics and visualization capabilities for telematics data with optimal cost-efficiency at any scale.
Data Collection
AWS Lambda was employed to retrieve raw telematics data in real-time from IoT devices installed across the fleet. Each data pull captures a pagination token stored in Amazon DynamoDB, ensuring that in the event of temporary platform failures, the Lambda function can resume data retrieval from the last read point, preventing real-time data loss.
Data Pre-Processing and Storage
Telematics data is extracted from IoT devices and buffered into Amazon Kinesis Data Firehose, which includes diagnostic-level data such as oil pressure and battery life percentage. A Lambda function, triggered via Kinesis Data Firehose, enriches this data with the ‘OpenStreetMap’ public dataset using Amazon Athena. Subsequently, Amazon Kinesis Data Analytics processes the combined raw data, parsing it to generate event log data. This data is then persisted to Amazon S3 in Apache Parquet format through Kinesis Data Firehose.
Event Generation: Real-Time Analytics and Summary Generation
Real-time event generation involves Amazon Kinesis Data Analytics parsing events from the combined raw data to produce event logs in near real-time. Key data points such as hard braking, harsh acceleration, maximum speed, and posted speed are extracted.
Daily summaries are generated using AWS Glue jobs, which load summary data of vehicles and events into Amazon Redshift. Summary data points include tire pressure, average miles per hour, average miles per gallon, and total trip distance.
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