What is automotive software and why does it matter?

 With the development of artificial intelligence, the Internet of Things, and cloud solutions, the amount of data we can retrieve from a vehicle is expanding every year. Manufacturers improve efficiency in converting this data into new services and enhance their own offerings based on the information received from connected car systems. Can software-defined vehicle solutions be successfully applied to enabling fleet management systems for hundreds or even thousands of models? Of course, it can, and even should! This is what today's market, which is becoming steadily more car-sharing and micro mobility-based, expects and needs.

Netflix, Spotify, Glovo, and Revolut have taught us that entertainment, ordering food, or banking is now literally at our fingertips, available here and now, whenever we need or want it. Contactless, mobile-first processes, that reduce queues and provide flexibility, are now entering every area of the economy, including  transportation and the automotive industry .

Three things: saving time, sparing money, and ecological trends dramatically change the attitude toward owning a car or choosing means of transport. Companies such as Uber, Lyft, or Bird cater to the needs of the younger generation, preferring renting over ownership.

The data-driven approach has become a cornerstone for automotive companies - both new, emerging startups and older, decades-old business models, such as car rental companies. None of the companies operating in this market can exist without a secure and well-thought-out IT platform for fleet management. At least if they want to stay relevant and compete.

It is the software - on an equal footing, or even first before the unique offer - that determines the success of such a company and allows it to  manage a fleet of vehicles , which sometimes includes hundreds, if not thousands of models.

Depending on the purpose of the vehicles, the business model, and the scale of operations, solutions based on software will obviously vary, but they will be beneficial to both the fleet manager and the vehicle renter. They allow you to have an overall view of the situation,  extract more useful information from received data and reasonably scale costs.

Among the potential entities that should be interested in improvements in this matter, the following types of fleets can be specifically mentioned:

•  city e-scooters, bicycles, and scooters;
•  car rentals;
•  city bus fleets;
•  tour operators;
•  transport and logistics companies;
•  cabs;
•  public utility vehicles (e.g., fire departments, ambulances, or police cars) and government limousines;
•  automobile mechanics;
•  small private fleets (e.g., construction or haulage companies)
•  insurers' fleets;
•  automobile manufacturers' fleets (e.g., replacement or test vehicles).

The benefits of managing your fleet with cloud software and the Internet of Things (IoT)

Real-time vehicle monitoring (GPS)

A sizeable fleet implies a lot of responsibility and potentially a ton of problems. That's why it's so important  to promptly locate each vehicle included and monitor it in real-time:

•  the distance along the route,
•  the place where the car was parked,
•  place of breakdown.

This is especially useful in the context of a bus fleet, but also in the  sharing-economy group of vehicles : city e-scooters, bicycles, and scooters. In doing so, the business owner can react quickly to problems.

Recovering lost or stolen vehicles

The real-time updated location, working due to  IoT and wireless connectivity , also enables operations in emergency cases. This is because it allows you to  recover a stolen or abandoned vehicle.

These benefits will be appreciated, for example, by people in charge of logistics transport fleets. After all, vehicles can be stolen in overnight parking lots. In turn, the fight against abandoned electric 2-wheelers will certainly be of interest to owners of the startups, which often receive complaints about scooters abandoned outside the zone, in unusual places, such as in fields or ditches in areas where there is no longer a sidewalk.

Predictive maintenance

We should also mention  advanced predictive analytics for parts and components such as brakes, tires, and engines. The strength of such solutions is that you receive a warning (vehicle health alerts) even before a failure occurs.

The result? Reduced downtime, better resource planning, and streamlined decision-making. According to estimates, these are savings of $2,000 per vehicle per year.

More convenient vehicle upgrades - comprehensive OTA (Over-the-Air)

Over-the-Air (OTA) car updates are vital for safety and usability. Interconnected and networked vehicles  can be updated in one go , simultaneously. This saves the time otherwise required to manually configure each system one by one. In addition, operations can also be performed on vehicles that happen to be out of the country.

Such a facility applies to virtually all industries relying on extensive fleets, especially in the logistics, transportation, and tourism sectors.

Intermediation in renting

A growing number of services are focusing on  service that is fast, simplified, and preferably remote. For instance, many rooms or apartment rentals on Airbnb rely on self-service check-in and check-out, using special lockups and codes.

Similar features are offered by  software-defined vehicles , which can now be rented "off the street", without the need for service staff. The customer simply selects a vehicle and, via a smartphone app, unlocks access to it. Quick, easy, and instant.

Loyalty scheme for large fleets

Vehicle and software providers are well aware that new technology comes with great benefits, but also with a degree of investment. In order to make such commitments easier to decide upon, attractive loyalty schemes are being rolled out for larger fleets.

So as a business owner you reap double benefits. And at the same time you test, on lucrative terms, which solutions work best for you.

Improved fleet utilization

Cloud and IoT software enables more practical use of the entire fleet of available vehicles and accurately pinpoints bottlenecks or areas where the most downtime occurs.

This is an invaluable asset in the context of productivity-driven businesses, where even a few hours of delay can result in significant losses.

By contrast,     artificial intelligence(AI)-based predictions   (for example, information about an impending failure)  offered to commercial fleets provide fleet managers with more anticipatory data , which can significantly cut business costs. Other benefits include improved emissions control or higher environmental standards.

Increasing safety

Minimized almost to zero danger of hacking into the system contributes to the security of the fleet-based business.

    Case study: Ford Pro™ Telematics  

Revenues based on software and digital services is not a bad deal for all informed participants in the business environment. Some big players like Ford have based their entire business model, on this idea.  With their Ford Pro™ series of solutions, they want to become an accelerator for highly efficient and sustainable business. Their offering is based on market-ready commercial vehicles to suit almost any business needs and on all-electric trucks and vans. They are developing telematics in particular.

 Ford Chief Executive Jim Farley puts it bluntly: We are the Tesla of this industry.

Bold assumptions? Yes, but also an equally bold implementation. Created in May 2021, a standalone Ford Pro™ unit is to focus exclusively on commercial and government customers. The new model also serves as a prelude to expanding digital service offers for retail customers.

The objective is to increase Ford Pro's annual revenue to $45 billion by 2025, up 67% from 2019.

Streamlined vehicle repairs

Managing a large group of vehicles also necessitates regular inspections and repairs, and at different times for different vehicles. This entails the need to control each unit individually.

The risk this poses is that information about the problem may not reach decision-makers in time, and besides, instead of the service and product, the executive is constantly focused on responding to anomalies. New technologies partially eliminate this problem.

As part of the Ford Pro Telematics Essentials package, vehicle owners receive real-time alerts on vehicle status in the form of engine diagnostic codes, vehicle recalls, and more. There's also a  scheduled service tracking feature and, in the near future, remote locking/unlocking, which will further enhance fleet management.

Driver behavior insights

Human-centered technology can help improve driver performance and road safety. Various sensors and detectors inside Ford vehicles provide a lot of interesting  information about the driver's behavior. They monitor the frequency and suddenness of actions such as braking or accelerating. Knowledge of this type of behavior allows for better fleet planning and improved driver safety.

Fuel efficiency analysis

Fuel is one of the major business costs for companies managing a large number of vehicles. Ford Pro™ Telematics, therefore, approaches customers with a solution to  monitor fuel consumption and engine idle time.

This functionality is designed to  optimize performance and reduce expenses. Better exhaust control also indirectly lowers operating costs.

Manage all-electric vehicle charging with E-Telematics

Telematics also provides an efficient way to manage a fleet consisting of electric vehicles. There are many indications that due to increasingly stringent environmental standards, they will form the backbone of various operations.

That's why Ford has developed its own E-Telematics software. It enables  comprehensive monitoring of the charging status of the electric vehicle fleet. In addition, it helps drivers find and pay for public charging points and facilitates reimbursement for charging at home.

The system also offers the ability to accurately compare the efficiency and economic benefits of electric vehicles versus gas-powered ones.

Better cooperation with insurers

Cloud-based advanced telematics software not only provides a better customer experience. What also counts is a streamlined collaboration with insurance providers and the delivery of vehicle rental services to clients of such companies.

This, of course, requires a special tool that enables:

•  remote processing of the case reported by the customer,
•  making the information available to the rental company,
•  allowing rental company personnel to provide a vehicle that meets the driver's needs.

The goal is to provide  replacement cars for the customers of partnering insurers .

Touchless and counter-less experience

It includes  verifying a customer and unlocking a car using a mobile app . This translates into greater customer satisfaction and the introduction of new business models. With the introduction of mobile apps in app stores,  queues can be shortened. This results in a simplified rental process. From now on, it is more intuitive and focused on user experience and benefits. Because nowadays customers expect mobile and contactless service.

    Case study: car rental  

The leading rental enterprise teamed up with Grape Up to  provide counter-less rental services and a touchless experience for their customers . By leveraging a powerful touchless platform and telematics system used by the rental enterprise, the company was able to build a more customer-friendly solution and tackle more business challenges, such as efficient stolen car recovery and car insurance replacement.

Software-defined vehicle solutions in vehicle fleets. How do implement them sensibly?

Technological changes that we are experiencing in the entertainment industry or e-commerce have also made their way into the automotive sector as well as micro-mobility and car rentals. There are many indications that there is no turning back.

Solutions such as real-time tracking, predictive maintenance, and driverless rental are the future. They help manufacturers execute their key processes more efficiently and track and manage their fleets effectively. In turn, the end customer receives an intuitive and convenient tool that fosters brand loyalty and makes life easier.

Of course, they need to be implemented properly. A large role is played by the quality of software. The key is the efficient flow of data and their cooperation with devices inside the vehicle. That is why it is worth choosing for business cooperation such a company that not only has the appropriate technological competence, but also the knowledge and experience gained during other such projects and implementations for the automotive industry.

 Automotive is transforming into a hyper-connected, software-driven industry that goes far beyond the driving experience. How to build applications in such an innovative environment? What are the main challenges of providing software for connected cars and how to deal with them? Let’s dive into the process of utilizing the capabilities of the cloud to move automotive forward.

People have always aimed for the clouds. From Icarus in Greek mythology, first airplanes and spaceships to dreams about flying cars – our culture and history of technology development express a strong desire to go beyond our limits. Although the vision from Back to the Future and other Sci-Fi movies didn’t come true and our cars cannot be used as flying vehicles, our cars actually are in the cloud.

Meanwhile, the idea of the Internet of Things came true; our  devices are connected to the Internet . We have smartphones, smartwatches, smart homes and, as it turns out, smart cars. We are able to communicate with them to gather data or even remotely control them. The possibilities are only limited by hardware, but even it is constantly improving to follow the pace of rapid changes triggered by software development.

Offerings on the automotive market are developing rapidly with numerous features and promised experiences to the end customer. By using cutting-edge technologies, utilizing cloud platforms, and working with innovative software developers,  automakers provide solutions to even the most demanding needs . And while our user experience is improving at an accelerated pace, there is still a broad list of challenges to tackle.

In this article, we dive into the technology behind the latest trends, take into account the most demanding areas of developing software in the cloud, and explain how proper solution empowers the change that affects us all.

Challenging determinants of the cloud revolution in automotive

Connecting with your car through a smartphone or utilizing information about traffic provided to your vehicle thanks to the platforms that accumulate data registered by other drivers is extremely useful.

Those innovative changes wouldn’t be possible without  cloud infrastructure . And as there is no way back from moving to the cloud, the transition creates challenges in various areas:  safety, security, responsiveness, integrity , and more.

Safety in the automotive sector

How to create a solution that doesn’t affect the safety of a driver? When developing new services, you cannot forget about the basics. Infotainment provided to vehicles is more advanced for every new release of a car and can be really engaging. The amount of delivered information combined with increasingly larger displays may lead to distraction and create dangerous situations. It’s worth mentioning that some of the colors may even impair the driver’s vision!

Integration with the cloud usually enables some of the remote commands. When implementing them, there are a lot of restrictions that need to be kept in mind. Some of them are obvious, such as you don’t want to disable the engine when a car is being driven 100km/h, but others may be much more complicated and unseen at first.

Providing security for car owners

Enabling services for your vehicle in the cloud, despite being extremely helpful to improve your experience, creates another way to break into your car. Everyone would like to open a car without using keys, but using a mobile phone, voice, or a fingerprint instead. And as these solutions seem modern and fancy, there is a big responsibility on the software side to do it securely.

Responsiveness enabling the seamless user experience

 Customer-facing services need to deliver a seamless experience to the end-user. The customer doesn’t want to wait a minute or even ten seconds for unlocking a car door. These services need to do it immediately or not at all, as an issue with opening the doors just because the system had a ‘lag’ is not acceptable behavior.

Data integrity is a must

Another very important concept associated with providing solutions utilizing cloud technologies is data integrity.  Information collected by your vehicle should be useful and up to date. You don’t want a situation when the mobile application says that the car has a range of 100km, but in the morning, it turns out that the tank is almost empty, and you need to refuel it before going to work.

How to integrate and utilize mobile devices to connect with your vehicle?

When discussing how to use mobile phones to control cars, a very important question occurs; how to communicate with the car? There is no simple answer, as it all depends on what model and version of a car it is, as depending on a provider, the vehicles are equipped with various technologies. Some of them are equipped with BLE, Wi-Fi Hotspots, or RFID tags, while others don’t offer a direct connection to the car, and the only way is to go through the backend side. Most of the manufacturers will expose some API over the Internet without providing a direct connection from mobile to the car. In such cases, usually, it’s a good practice to create your own backend which handles all API flaws. To do so, your system will need a platform to have a reliable solution.

When the limitation of hardware is met, there is always an option to equip the car with a custom device, which will expose a proper communication channel and will be integrated with the vehicle. To do so, it may use the OBD protocol. It gives us full control over the communication part, however, it’s expensive and hard to maintain the solution.

Building a platform to solve the challenges

There is no simple answer on how to solve the mentioned challenges and implement a resilient system that will deliver all necessary functionalities with the highest quality. However, it’s very important to remember that such a solution should be scalable and utilize cloud-native patterns. When designing a system for connected cars, the natural choice is to go with the microservice architecture. The implementation of the system is one thing, and partly this topic was covered in the     previous article   , but on the other hand, the very important aspect is a runtime, the platform. Choosing the wrong setup of virtual machines or having to deploy everything manually can lead to downtime of the system. Having a system that isn’t available for the customer constantly can damage your business.

Kubernetes to the rescue! As probably you know, Kubernetes is a container orchestration platform, which allows running workload in pods. The platform itself helped us to deliver many features faster and with ease to our clients. Nowadays, Kubernetes is so easily accessible that you can spin up a cluster in minutes using existing service providers like AWS or Azure. It allows you to increase the speed of delivery of new features, as they may be deployed immediately! What’s very important with Kubernetes, is its abstraction from infrastructure. The development team with expertise in Kubernetes is able to work on any cloud provider. Furthermore,     mission-critical systems can successfully implement Kubernetes   for their use cases as well.

Automotive cloud beyond car manufacturers

 Automotive cloud is not only a domain of car manufacturers. As mentioned earlier, they offer digital services to integrate with their cars, but numerous mobility service providers integrate with these APIs to implement their own use cases.

•  Live notifications
•  Online diagnostics
•  Fleet management
•  Vehicle recovery
•  Remote access
•  Car sharing
•  Car rental

The best practices of providing cloud-native software for the automotive industry

Working with  the leading auto motive brands and being engaged in numerous projects meant to deliver innovative applications. Our team have collected a group of helpful practices which make development easier and improve user experience. There are some must-have practices when it comes to delivering high-quality software, such as CI/CD, Agile, DevOps, etc., – they are crucial yet well-known for the experienced development team and we don’t focus on them in this article. Here we share tips dedicated for teams working with app delivery for automotive.

Containerize your vehicle

One of the things we’ve learned     collaborating with Porsche   is that vehicles are equipped with ECUs and installing software on them isn’t easy. However, Kubernetes helps to mitigate that challenge, as we can mock the target ECU by docker image with specialized operating systems and install software directly in it. That’s a good approach to create an integration environment that shortens the feedback loop and helps deliver software faster and better.

Asynchronous API

In the IoT ecosystem, you can’t rely too much on your connection with edge devices. There are a lot of connectivity challenges, for example, a weak cellular range. You can’t guarantee when your command to the car will be delivered and if the car will respond in milliseconds or even at all. One of the best patterns here is to provide the asynchronous API. It doesn’t matter on which layer you’re building your software if it’s a connector between vehicle and cloud or a system communicating with the vehicle’s API provider. Asynchronous API allows you to limit your resource consumption and avoid timeouts that leave systems in an unknown state.

Let’s take a very simple example of a mobile application for locking the car remotely.

 Synchronous API scenario

1.  A customer presses a button on the application to lock the car.
2.  The request is sent and is waiting for a response.
3.  The request needs to be delegated to the car which may take some time.
4.  The backend component crashes and starts without any knowledge about the previous request.
5.     The application gets a timeout.  
6.  What now? Is the car locked? What should be displayed to the end-user?

 Asynchronous API scenario

1.  The customer presses a button on the application to lock the car.
2.     The request is sent and ended immediately.  
3.  The request needs to be delegated to the car which may take some time.
4.  The backend component crashes and starts without any knowledge about the previous request.
5.  The car sends a request with the command result through the backend to the application.
6.     Application displays: “Car is locked.”  

With asynchronous API, there’s always a way to resend the response. With synchronous API, after you lose connection, the system doesn’t know where to resend response out of the box. As you may see, the asynchronous pattern handles this case perfectly.

Digital Twin

DigDigital Twin is a virtual model of a process, a product or a service, in case of automotive – a digital cockpit of a car. This pattern helps to ensure the integrity of data and simplify the development of new systems by its abstraction over the vehicle. The concept is based on the fact that it stores the actual state of the vehicle in the cloud and constantly updates it based on data sent from a car. Every feature requiring some property of vehicle should be integrated with Digital Twin to limit direct integrations with a car and improve the execution time of operations.

Implementation of Digital Twin may be tricky though, as it all depends on the vehicle manufacturer and API it provides. Sometimes it doesn’t expose enough properties or doesn’t provide real-time updates. In such cases, it’s even impossible to implement this pattern.

Software for Connected Cars - Summary

We believe that the future will look more futuristic than we could have ever imagined. Autonomous cars, smart cars, smart homes, every device tries to make our lives easier. It’s not known when and how these solutions will fully utilize Artificial Intelligence to make this experience even better. Everything connects as numerous IoT devices are connected which provides us with unlimited possibilities.

T  he automotive industry is currently transforming, and it isn’t only focusing on the driving experience anymore. There is a serious focus on connected mobility and other customer-oriented services to enhance our daily routines and habits. However, as software providers, we should keep in mind that automotive is a mature industry. The first connected car solutions were built years ago, and it’s challenging to integrate with them. These best practices should help focus on customer experience. Unreliable systems won’t encourage anyone to use it, and bad reviews can easily destroy a brilliant idea.

The automotive industry is experiencing a challenging transformation. We can notice these changes with every new model of a car and with every new service released. However, to keep up with the pace of the changing world, the industry needs modern technologies and reliable solutions, such as Kubernetes. And on top of that cloud-native application,     software created with the best practices by experienced engineers   who use the customer-first approach.

In the modern world, tech companies strive to collect as much information as possible about the status of owned cars to enable proactive maintenance and rapid responses to any incidents that may occur. These incidents could involve theft, damage, or the cars simply getting lost. The only way to remotely monitor their status is by obtaining telemetry data sent by the vehicles and storing it on a server or in the cloud. There are numerous methods for gathering this data, but is there an optimal approach? Is there a blueprint for designing an architecture for such a system? Let's explore.

What does “telemetry” mean in a car?

This article is about gathering telemetry data, so let's begin with a quick reminder of what it is. Telemetry in cars refers to the technology that enables the remote collection and transmission of real-time data from various components of a vehicle to a central monitoring system. This data encompasses a wide range of parameters, including, for example:

• engine performance,
• fuel consumption,
• tire pressure,
• vehicle speed,
• percentage of electric vehicle battery,
• braking activity,
• acceleration,
• GPS position,
• odometer

Collecting vehicle details is valuable, but what is the real purpose of this information?

Why collect telemetry data from a car?

The primary use of telemetry data is to monitor a car's status from anywhere in the world, and it's especially crucial for companies like car rental firms such as Hertz or Europcar, as well as transportation companies like Uber. Here are some examples:

• Tracking Stolen Cars : Companies can quickly track a stolen vehicle if they store its GPS position.
• Accident Analysis : If a car is involved in an accident, the company can assess the likelihood of the event by analyzing data such as a sudden drop in speed to zero and high acceleration. This allows companies to provide replacement cars promptly.
• Fuel or Charging Management : In cases where a rental car is returned without a full tank of fuel or not fully charged, the company can respond quickly to make the car available for the next rental.

These are just a few examples of how telemetry data can be utilized, with many more possibilities. Understanding the value of telemetry data, let's delve into the technical aspects of acquiring and using this data in the next part of the article.

To begin planning the architecture, we need answers to some fundamental questions

How will the telemetry data be used?

Architectural planning should commence with an understanding of the use cases for the collected telemetry data. This includes considering what the end user intends to do with the data and how they will access it. Common uses for this data include:

1. Sharing data on a dashboard : To enable this, an architecture should be designed to support an API that retrieves data from databases and displays it on a dashboard,
2. Data analytics : Depending on the specific needs, appropriate analytic tools should be planned. This can vary from real-time analysis (e.g. AWS Kinesis Data Analytics) to near real-time analysis (e.g. Kafka) or historical data analysis (e.g. AWS Athena),
3. Sharing data with external clients : If external clients require real-time data, it's essential to incorporate a streaming mechanism into your architecture. If real-time access is not needed, a REST API should be part of the plan.

Can we collect the data from cars?

We should not collect any data from cars unless we either own the car or have a specific legal agreement to do so. This requires not only planning the architecture for acquiring access to the car but also for disposing of it. For example, if we collect telemetry or location data from a car through websockets and the company decides to sell the car, we should immediately cease tracking the car. Storing data from it, especially location data, might be illegal as it could potentially allow tracking of the location of a person inside the car.

How do we manage permissions to the car?

If we have legal permission to collect data from the car, we must include correct permission management in our architecture. Some key considerations include:

• Credential and token encryption,
• Secure storage of secrets, such as using AWS Secret Manager,
• Regular rotation of credentials and tokens for security,
• Implementing minimum access levels for services and vehicles,
• Good management of certificates,
• Adhering to basic security best practices.

How do we collect the data?

Now that we have access to the data, it's time to consider how to collect it. There are several known methods to do this:

• Pull Through REST/GRPC API: In this scenario, you'll need to implement a data poller. This approach may introduce latency in data acquisition and is not the most scalable solution. Additionally, you may encounter request throttling issues due to hitting request limits.
• External Service Push Through REST/GRPC: Here, you should set up a listener, which is essentially a service exposed with an endpoint, such as an ECS task or a Lambda function on AWS. This method might incur some costs, and it's crucial to consider automatic scaling to ensure no data is lost. Keep in mind that the endpoint will be publicly exposed, so robust permission management is essential.
• Pulling From a Stream: This approach is often recommended as it's the most scalable and secure option. You can receive data in real-time or near real-time, making it highly efficient. The primary considerations are access to the stream and the service responsible for pulling data from it.
• Queues: Similar to streams, queues can be used for data collection, and they may offer better data ordering. However, streams are typically faster but might be more expensive. This is another viable option for collecting vehicle data from external services.
• Websockets: Websockets are a suitable solution when bidirectional data flow is required, and they can be superior to REST/GRPC APIs in such cases. For example, they are an appropriate choice when a client needs confirmation that data has been successfully acquired. Websockets also allow you to specify which telemetry data can be acquired and at what frequency. A notable example is the Tesla Websockets ( https://github.com/teslamotors/fleet-telemetry/blob/main/protos/vehicle_data.proto ).

Where to store the data?

After collecting the data, it's important to decide where to store it. There are various databases available, and the choice depends on your specific data use cases and access patterns. For instance:

• Commonly Used Data : For data that will be frequently accessed, you can opt for a traditional database like MongoDB or PostgreSQL.
• Low-Maintenance Database : If you prefer a database that requires minimal maintenance, AWS DynamoDB is a good choice.
• Infrequently Used Data for Analytics : When data won't be used frequently but will be utilized for occasional data analytics, you can consider using an AWS S3 bucket with the appropriate storage tier, coupled with AWS Athena for data analysis.
• Complex Data Analysis : If the data will be regularly analyzed with complex queries, AWS Redshift might be a suitable solution.

When planning your databases, don't forget to consider data retention. If historical data is no longer needed, it's advisable to remove it to avoid excessive storage costs.

Example

Here is an example of such an architecture on AWS in which:

1. An employee grants permissions to the car to stream the data.
2. The data is streamed using AWS Kinesis Stream and saved to an S3 bucket by AWS Kinesis Firehose for audit purposes.
3. The data is also normalized by the AWS Lambda function and stored in AWS DynamoDB.
4. The stored data is queried by another AWS Lambda function.
5. The query Lambda is triggered by an AWS API Gateway to enhance security, such as limiting requests per second.
6. The API is exposed via Route 53 to the end user, which can be, for example, a dashboard or an external API.

Conclusion

In the modern tech landscape, the quest for complete vehicle data is a paramount objective. Tech companies seek to collect critical information about the status of owned cars to enable proactive maintenance and rapid responses to a spectrum of incidents, from theft and damage to simple misplacement. This imperative relies on the remote monitoring of vehicles through the collection and storage of data on servers or in the cloud, offering the capability to monitor a vehicle's status from any corner of the globe. This is especially essential for companies like car rental firms and transportation services, with applications ranging from tracking stolen cars through GPS data to analyzing accident events and managing fuel or charging for rental vehicles.

The core of this mission is to strike a balance between data collection, security, and architectural planning. The process involves careful consideration of data collection methods, adherence to legal and security best practices, and informed choices for data storage solutions. The evolving landscape of vehicle data offers endless possibilities for tech companies to harness the power of telemetry and deliver an enhanced experience for their customers.