How big data and IoT connection has transformed the automotive industry
October 17, 2020 5:00 PM
Big data analytics has transformed driver experiences by capturing real-time data to improve driver safety, vehicle services and the driving experience as a whole
Left to right: Alex M and Ramesh Ayyakut.
By Alex M and Ramesh A
Internet of Things (IoT) makes it possible to track the performance of your car with something as simple as a mobile application. Internet of Things refers to a connection of multiple devices like electronics, sensors, gateways, actuators, and platform hubs. These devices connect and interact with each other over a wireless network. Connected devices share data with each other and operate without any intervention by humans. Wireless IoT allows us to monitor additional parameters using sensor-level technology and to gather data. Big data analytics has transformed driver experiences by capturing real-time data to improve driver safety, vehicle services and the driving experience as a whole.
Companies in the automotive sector today have built mobile applications that allow their customers to efficiently drive and maintain their cars. While buying a car, the customers can opt to attach wireless sensors in their car to capture the data which will be analyzed using predictive analytics. The sensors embedded in different parts of the car collect data and share it to a database. This data is then processed by a prediction algorithm that can analyze the future outcome of the component based on its performance. With that data, weekly reports can be sent with the performance metrics and instant push notifications that detect accidents and even bad driving.
Majority of car accidents across the world are due to human error, 93% to be precise. This can be reduced by leveraging IoT technology. This is because it can be used to monitor driving habits and send recommendations to the driver if there are any alarming signs. IoT in vehicles also makes the maintenance of running parts easier. IoT automotive maintenance systems help customers with preventive maintenance of parts and avoid sudden breakdowns on the freeway. The alerts are sent to the customer’s mobile, way before the problem even occurs. This helps the customer to make cost-effective and time-saving decisions to avoid component failure while driving. By using the automotive maintenance system, one can ensure optimum performance of the vehicle and maintenance can be ensured before part failure.
The working of the IoT sensors and analysis of the data
Collecting sensor data and storing it in a Data Lake
The sensors in the car are connected to a Process Information (PI) historian database. Each sensor has a unique tag id which gets stored along with the sensor value and the time-stamp information. A Python JDBC (The JayDeBeApi module allows you to connect from Python code to databases using Java JDBC) will incrementally read the data from the PI historian database and store it into an Hbase table (HBase is a relational database management system that provides a fault-tolerant way of storing sparse data sets).
Analyzing stored data
A PySpark program (a Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data) runs on top of the data in Hbase and calculates the performance metrics of the car. A prediction algorithm like Shapelet is used to predict the metrics. With the prediction algorithm in place, the below notifications will be sent to the customer:
Weekly report: A weekly report with the below metrics is sent to the customer.
Best route: If a customer uses his car to reach his workplace daily by three different routes in a week, then the best route is calculated by considering factors like fuel consumption, traffic, time taken, distance, tyre wear and tear etc.
Safety: Monitor the driver’s behavior like speed violation, driving speed and provides data that can be used to improve the driver’s safety. Speed monitoring applications are in place to inform the car owner if the vehicle is being driven faster than a preset threshold speed.
Efficiency: Monitor the operational performance of the car like fuel consumption, engine RPM and provides data which can be used to reduce the maintenance cost and wear and tear of the vehicle.
Alert messages: Instant push notifications will also be sent to the customer in the below cases:
Rash driving: Vehicle movement parameters such as speed, acceleration, rate of change in distance are analyzed. If those parameters go beyond the preset threshold then an alert will be sent with an accident warning.
Fuel warning: If the fuel in the car is less and the customer starts speeding, a warning message will be sent to the driver stating that the fuel is less and if the driver continues driving in the same speed then they can reach only a certain distance.
Internet of Things is reshaping almost all industries by enhancing the customer experience. IoT applications are increasing day by day in the automotive industry. For example, in the vehicle insurance space, precise data is gathered from IoT sensors to support the assessment of claims, reduce fraud, and drive down costs. In the vehicle service segment, customer loyalty can be enhanced through regular contact for timely service based on IoT data gathered regarding wear and tear of parts. In vehicle manufacturing, parts that wear out easily are tracked using IoT sensors and necessary changes can be made. We see companies calling back a large batch of cars for this particular reason. Better the engineering, better the quality of cars.
With the enhancement in the technology of Internet of Things, more automotive cases will pop up which will completely change the way we interact with our vehicles.
The authors work Indium Software. While Alex M is a Senior Architect, Big Data, Ramesh A is the Chief Solutions Architect.