AutoPi Big Data Project
Optimize your operations or projects by obtaining insightful telematics data
Capture terabytes of telematics data that streams into your organization and apply analytics to transform it into actionable insights.
Benefits and features
A configurable tool to gain a large amount of insightful telematics data
Capture every byte
Do not let even a single byte escape your analysis, regardless if it is for daily operations or research projects.
The solution has specifically been designed for a high amount of telematics data from a lot of devices at once and to retain the data for a long period.
Real-time data support
No matter the need and requirements, we can log, store, and support your data in real-time.
Using external storage volumes
Built on a time series database which gives advantages in hosting as there is a potential for using external storage volume.
The bigger the data, the greater the value
Seize the opportunity, improve efficiency, and stay competitive
Improve safety and behavior
Onboard telematics devices installed in vehicles can collect data on driver behavior ranging from harsh braking to excessive speed. The data is sent back to Autopi cloud or directly to your server, enabling you to examine all of the aggregated data to identify patterns and address any overarching issues.
Furthermore, by analyzing the data, you will acquire actionable insights to deploy data-driven decisions and help prevention of possible downtime of vehicles and potential accidents of drivers.
Increase overall performance
Access to vehicle data means you'll have a better-performing fleet overall. You can utilize the aggregated data to predict when a vehicle will require maintenance, in addition to receiving real-time alerts, e.g., problematic engines, low batteries, etc.
With the use of big data sets and connected devices, you will be able to fix the problem before it occurs, resulting in the increased lifetime value of vehicles. Predictive analytics improves fleet efficiency by limiting, if not eliminating, downtime, resulting in significant cost savings.
Huge cost savings
Fewer accidents result from predictive analytics and safety features. Accidents account for approximately 14% of fleet expenses, so this saves resources. Predictive maintenance also enables you to understand the lifetime value of parts and vehicles, allowing you to save money in that area as well. Late deliveries, vehicle replacement, overtime pay for drivers, and other costs can add up; however, by reducing downtime, you can avoid all of this.
Why AutoPi Big Data Project?
AutoPi Big Data Solution is a fully customizable tool for collecting, sorting, aggregating, and sending data. The AutoPi Big Data Solution is intended to support streaming up to the entire CAN bus in real-time, at configurable intervals, or on a local hard disk. Furthermore, Big Data Project allows you to tap into the massive amount of data generated by vehicles while managing the high frequency and quality data in real-time.
Frequently asked questions
Big Data is a term used to describe a massive amount of data and data sets. Big data is frequently defined by the big five Vs. - data with great Variety, increasing Volume, high Velocity, excellent Veracity, and useful value.
- Variety: Data is now gathered from a wide range of sources, including websites, applications, social media, audio and video, smart devices, sensor-based equipment, and more. These disparate bits of data are all part of enterprise business intelligence.
- Volume: "Big" is a relative term, the volume of data generated determines whether it is indeed big data. This metric can assist organizations in determining whether they require a big data solution to process their proprietary data.
- Velocity: The usefulness of data is determined by how quickly it is generated and moved across systems.
- Veracity: Data from disparate sources can be incomplete, inaccurate, and inconsistent. Only complete, accurate, and consistent data can contribute to the value of enterprise business intelligence and analytics.
- Value: The value of big data in business decisions determines how useful it is to the organization.
Because of the sheer volume and variety of big data, it requires a different approach than traditional methods. Before large, complex data sets can be ingested by business intelligence and analytics solutions, they must be cleaned, prepared, and transformed. To produce real-time data insight, big data requires smart storage solutions and extremely fast computing speeds.
Big Data has permeated many industries, altering the way we work. Big Data enables IoT platforms to operate, connecting devices and revolutionizing machines. While the fleet management industry is not usually associated with the term "innovation," Big Data has changed that. The infrastructure of the Big Data Solution from AutoPi has specifically been designed for a high amount of telematics data from a lot of devices at once and to retain the data for a long period.
The Big Data Solution is built on a time series database, which gives advantages in hosting, as there is a potential for using external storage volumes, which are cheaper and therefore, needed for extended retention of huge databases. Our solution is customizable, meaning that we can tailor a businesss solution exactly to your project needs. In other words, you will be able to gain very large datasets that can be analyzed computationally to reveal patterns, trends, and associations – especially in connection with human behavior and interactions.
Big Data analytics uses analytic techniques to examine data, thus obtaining and finding out information like hidden patterns, correlations, market trends, and consumer preferences. Therefore, analytics help businesses and organizations make informed business decisions that lead to efficient operations, happy consumers, and increased profits.
Big Data analytics entails processing large amounts of data in order to discover patterns and/or assign values to the data. E.g. Data storytelling. Businesses can improve their models to better meet the needs of their customers. Data collection is pointless if it cannot be used to its full potential. Organizations that have yet to leverage big data must begin taking steps to implement big data technologies.
Telematics is built on the technology of collecting, storing and transmitting information between end-users and vehicles via telecommunication devices. Big data use cases in telematics, increase the data's usefulness. So, what kinds of valuable services can big data bring to the world of telematics:
Optimization of Routing (use case #1): The number of possible routes for a truck is extremely large. Previously, logistics companies had to plan a delivery path manually, which took a long time. Furthermore, it was difficult to provide accurate ETAs and save driving time on the road without real-time traffic conditions.
Big data relies on several key types of data to evaluate the best route based on consuming time and fuel usage in a few seconds to make the driving oath more efficient and optimal: Telematics tracking devices collect real-time GPS and speed data. Instant traffic information, such as accidents and construction zones reported by other road users; Authorized institutions post road information such as the number of stop signs, road speed, school zone, and so on. The optimized route is then calculated and displayed to the driver.
Maintenance Reminders and Breakdown Alerts (use case #2): Engine data collected by telematics devices include engine RPM, oil level, transmission, mileage driven, tire pressure, and more. Big data predictive analysis could provide us with precautionary breakdown and maintenance notifications, as well as recommended solutions, based on all of the engine data and historical records of maintenance and repair. By gaining early insight into potential vehicle health issues, the fleet can balance downtime and work time for vehicles, reducing the likelihood of an unexpected breakdown on the road.
Analysis of Driving Behavior (use case #3): People are often referred to as a company's most valuable resource. Driving and road safety has always been and will always be the top priorities in the transportation industry. Running a large global fleet makes managing safety even more difficult. As a result, analyzing driver behavior is critical for both fleet management and the drivers themselves.
It is widely acknowledged that a better understanding of driving behavior aids in the development of more appropriate safety policies, more intelligent driving guiding systems or coaching systems, and, most importantly, in lowering the rate of accidents while protecting company property and reputation, as well as drivers' lives. More and more in-depth machine learning and artificial intelligence algorithms have been performed in recent years to investigate drivers' driving behaviors and styles. Telematics can detect speed-related, stop-related, turn-related, and other driving behaviors.
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