![\"\"](\"https://wp.inventiv.org/wp-content/uploads/2025/07/generated_image_20250708_090651_e608ad41-768x768.png\")
Today, capturing and sharing moments while on the road has become an everyday part of owning a modern vehicle, especially electric vehicles (EVs). With cameras built into cars, drivers can record their journeys for memories, safety, and even fun video journals. But as more video is captured, there is a growing problem: how do you find the best parts, keep what matters, and maybe even add cool effects, when there is just too much footage to look through? A new patent application tackles this challenge by using artificial intelligence (AI) and smart data processing to automatically create special videos from EV journeys, saving the best moments and letting users add creative touches. In this article, we will explore the background of this invention, the science and earlier solutions it builds on, and explain the clever new ideas it introduces.\n
\n\nImagine you are on a long road trip in your electric vehicle with friends or family. Your car has cameras facing forward, back, and to the sides, all recording every second of your adventure. Maybe you take a drive through the mountains, a busy city, or along a sunny beach. When you get home and want to make a short video to remember your trip or share with others, you are faced with hours and hours of footage. Watching it all, picking the best scenes, and cutting them together is a huge job. Even if your car does this for you, its memory might run out and the best clips could get deleted before you even see them.\n
\n\nThis is not just a personal problem—it’s a growing issue as more people use cars with cameras for many reasons. Some want to relive family vacations. Others use cameras for safety, like recording accidents or strange events. Some car makers offer features where you can make a video journal of your trip or use special effects to add fun or helpful information, like showing your route or adding animated characters.\n
\n\nBut the more cameras a car has, and the more people drive, the bigger the pile of video gets. Car storage is limited. Sorting through video is boring and slow. Deciding what to keep and what to erase is hard, especially if you do not want to lose important or exciting moments.\n
\n\nCar companies, technology creators, and drivers all want a better way to handle this. They want to:\n
\n\nThis patent application is aimed right at these problems. It is about a system that uses smart computer programs (AI) and the data from the car to figure out which video pieces are worth keeping, which should be deleted, and how to put the good ones together into a new, easy-to-share video. It even lets you add effects or information that match what happened in the video, like an animated animal running alongside your car in a forest scene or a chart showing your speed during a race.\n
\n\nThe timing is perfect. As more EVs are sold and technology in cars gets better, more drivers will want these features. The invention helps car makers stand out, gives users a better experience, and saves time and storage space for everyone.\n
\n![\"\"](\"https://wp.inventiv.org/wp-content/uploads/2025/07/generated_image_20250708_090558_5f4c937a-768x768.png\")
\nTo understand what makes this invention special, let’s look at what has been possible before and the science that makes it work.\n
\n\nCars with cameras are not new. Many modern vehicles, especially electric cars, have several cameras that record what happens in front, behind, and on the sides. Some systems even let you record your drive and save it to a memory stick or upload it to the cloud. There are “dash cams” that record everything for safety or insurance. Some cars can even make short highlight videos if you press a button.\n
\n\nBut these older systems have some big limits. Usually, they just record everything and save it. If the memory fills up, the oldest videos are deleted, even if they contain something special. If you want to make a video journal or a highlight reel, you have to watch all the footage yourself and use video editing software. This takes a lot of time and patience. Some solutions let you press a button to save a clip, but you need to know exactly when something interesting is happening.\n
\n\nPeople have tried to make this easier. Some apps and programs use simple rules to pick out video clips, like “save 30 seconds before and after a crash,” or “keep video when the car is moving fast.” Others let you mark favorite spots during your drive. Few systems try to use smart technology to look at the video and decide what is interesting, fun, or important.\n
\n\nThere has also been work on adding effects or information to videos. For example, some apps let you overlay a map, speed, or other driving data. A few apps let you add simple graphics or stickers. But these usually need you to do the work yourself, picking where to put things and what to add. They do not automatically match the effect to what is happening in the video.\n
\n\nArtificial intelligence (AI) and machine learning (ML) have started to change this. AI can look at pictures and videos and figure out what is in them—like cars, people, animals, road signs, or even the type of place (such as city, mountains, or beach). AI can also learn from many examples what kinds of scenes people like, what makes a video exciting, or when something special happens.\n
\n\nSome recent research uses AI to find the best scenes in a long video or to summarize a trip. These systems often use computer vision to look at each frame, recognize objects or places, and score how interesting each part is. Some can even use data from the car—like speed, GPS location, or sensor readings—to help decide what to keep.\n
\n\nBut even with these tools, there are still big challenges:\n
\n![\"\"](\"https://wp.inventiv.org/wp-content/uploads/2025/07/5e6be87934a5734c02c44ae2b368a057-794x1024.png\")
\nPrevious work often focused on one or two of these problems, but not all at once. There were no simple systems that could do everything: pick the best moments, use data from the car, avoid sudden scene changes, add matching effects, and manage storage all at the same time.\n
\n\nThis patent application takes all these ideas and brings them together in a system designed for modern electric vehicles. It uses AI trained on lots of driving video to understand what is happening in each scene, uses car data to add context, picks the best video fragments from all the cameras, puts them together smoothly, and lets you add custom effects that actually match the moment. It even keeps track of storage space and makes sure the best parts are never lost.\n
\n\nNow let’s dive into how this invention works and what makes it stand out from anything before.\n
\n\nAt its core, this system is a set of computer programs (running on the car, a server, or the cloud) that work together to do several things:\n
\n\nLet’s walk through each part, using simple words and examples.\n
\n\nAs soon as you start your EV and begin a trip, the cameras start recording. Each camera (front, back, sides) makes its own video, all covering the same time period but from different views. These videos are chopped into small fragments—say, every three seconds. For each fragment, the system saves not just the pictures and sound, but also data from the car: how fast you were going, where you were, what mode the car was in (like off-road or city), and even sensor readings like G-force or sudden stops.\n
\n![\"\"](\"https://wp.inventiv.org/wp-content/uploads/2025/07/rotated_0a0b057eb3bfee3716bcb4ca703344f7-794x1024.png\")
\nOnce a drive is done, or even while you are still driving, the system uses AI programs trained to understand different types of scenes. Each fragment from every camera is fed into the AI, which decides what is shown (for example, “mountain view,” “city traffic,” “beach,” or “accident”). It also looks at the car data to spot moments that might be important—like a sudden stop, a change in speed, or a sharp turn.\n
\n\nThe system then gives each fragment a score. The score is higher if the scene is special (like a beautiful sunset or a family moment), or if the car data shows something interesting happened (like a near miss or exciting event). User preferences can also change the score—if you love mountain views, those get a higher score.\n
\n\nA big challenge in making videos from many cameras is that switching views too often makes the video hard to watch. To fix this, the system uses a clever “bias” when picking which fragment to use next. If the last chosen fragment came from the front camera, the system is more likely to stick with the front camera for the next fragment—unless something much better is happening in another view. The longer it stays with one camera, the less bias it gives, so it will eventually switch if there is a good reason. This keeps the video smooth and natural, not jumpy and confusing.\n
\n\nOnce the best fragments are picked, the system puts them together into a new video—a highlight reel or video journal of your trip. You can set how long you want the video to be, or what scenes to focus on. The system can also automatically speed up boring parts (like long straight roads) and slow down exciting moments (like a cool jump or sudden turn).\n
\n\nOne of the coolest features is how the system can add extra effects or information to the video. It uses more AI to look at the scene and decide what to add. For example, if you are driving through the woods, it might add an animated deer running alongside. If you are in a race, it might show your speed or a map of your route. The effects are chosen to match the actual scene, so they look natural and add to the story.\n
\n\nThese effects are not just dropped anywhere—they are placed carefully in the video, using AI to find the right spot in the frame, so they look like they belong. The system can even create new effects on the fly using advanced AI models, based on what is happening in the video.\n
\n\nWhat if your car’s memory is nearly full? The system has a solution for that too. Every video fragment gets a “priority score” based on how important it is (using the AI scene analysis, car data, and user preferences). When space runs low, the system deletes the fragments with the lowest scores first—like long stretches of empty road or when the car is parked. Fragments with high scores—meaning they show something special—are protected and never deleted until you say so.\n
\n\nThis way, you always have room for new footage, but you never lose the moments that matter. If there’s an accident or a funny family moment, the system saves those automatically.\n
\n\nSuppose you take your EV on a weekend trip. You drive through the city, then into the mountains, stopping at a lake for a picnic. Your car’s cameras record everything. When you get home, you want to make a three-minute video to share.\n
\n\nHere’s what happens:\n
\n\nThis invention brings together several key ideas in a way that has not been done before:\n
\n\nAll these pieces work together in a system designed for the real needs of EV drivers, using today’s best AI technology. The result is a system that saves time, makes video journals easy and fun, and ensures that your favorite moments are never lost.\n
\n\nThe world of electric vehicles is changing fast, and so is the way we capture and share our journeys. This patent application shows how smart computer programs and car data can work together to solve real problems—saving drivers time, making memories easier to keep and share, and protecting what matters most. By using AI to pick the best scenes, smoothly combine them, add creative effects, and manage storage, this invention offers a complete solution for anyone who wants more from their in-car cameras. Whether you’re an EV owner, a car company, or a tech fan, this technology points the way to a future where your car helps you remember, relive, and share every journey—without any hassle.\n
\nClick here https://ppubs.uspto.gov/pubwebapp/ and search 20250218178.
\n","id":"cG9zdDo0NjI1Mg==","uri":"/electric-vehicle-data-based-video-composition-and-content-augmentation-402336/","title":"ELECTRIC VEHICLE DATA BASED VIDEO COMPOSITION AND CONTENT AUGMENTATION","tags":{"nodes":[{"name":"Facebook/Meta"},{"name":"Patent Review"}]},"categories":{"nodes":[{"name":"Software"}]},"featuredImage":{"node":{"mediaItemUrl":"https://wp.inventiv.org/wp-content/uploads/2025/07/generated_image_20250708_090512_bf69cc35.png"}}}},"pageContext":{"slug":"electric-vehicle-data-based-video-composition-and-content-augmentation-402336","neId":"46252","categories":["3D Printing","Animal Health","Apple","Artificial Intelligence","Autonomous Vehicles","Biopharmaceuticals","Blockchain Fintech","Cannabis Patents and Trademarks","Chemical Products","Communications","Consumer Products","Digital Healthcare","Electronics","Food Science Packaging","Industrial Products","Infectious Diseases","Internet","Medical Device","Metaverse","Nanotechnology","Prescription & OTC Drugs","Software","Start Up","Therapeutic Antibodies","uncategorized"],"tags":["Alphabet","Amazon","Facebook/Meta","Microsoft","Patent Review","Samsung"],"siteUrl":"https://inventivs.net"}}, "staticQueryHashes": ["764694655"]}