Invented by Ibarra Von Borstel; Alejandro, Lopez Meyer; Paulo, Cordourier Maruri; Hector Alfonso, Zamora Esquivel; Julio, Macias Garcia; Edgar, Campos Macias; Leobardo

Welcome! Today, we are diving into a new way of making smart homes truly “smart.” We’ll talk about a patent that helps your smart home know what it can do, what it cannot, and even what it could do better. If you are curious about how your home can work more smoothly and even suggest new ways to help you, keep reading. We’ll keep things simple and easy to understand.

Background and Market Context

Smart homes are no longer just a dream. Many people already use devices like smart lights, door locks, cameras, and voice assistants such as Alexa, Google Home, or Siri. With a simple voice command, you can turn on the lights, lock the door, or check who is at the front door. These gadgets make life easier, safer, and more fun. The market for smart home devices keeps growing because people want more comfort, convenience, and control in their homes.

However, as more devices come out, things can get a bit tricky. Sometimes, different brands don’t “talk” well with each other. Sometimes, your voice assistant cannot do what you ask because it does not have the right device or skill. Maybe you ask, “Who is at the front door?” but your system cannot answer because it does not have a camera there, or the camera does not have face recognition software. Other times, you may not even know what your smart home can actually do or what it is missing.

People want their homes to understand them better, help them more, and even suggest ways to improve. For example, if your smart home cannot do something you ask, wouldn’t it be nice if it could tell you what you need to add or upgrade? This is where the idea of smart home “functionality awareness” comes in. It helps your home know about its skills and weaknesses and helps you as the homeowner make better choices.

Most current systems are limited. They follow fixed commands and often do not give feedback if they cannot handle a task. They rarely suggest improvements or let you know about missing skills. Users want more natural conversations with their homes, more useful suggestions, and fewer headaches when setting up or upgrading their devices.

With faster internet, better voice assistants, and more devices on the market, the time is right for a system that can not only manage lots of devices but can also think about what it can and cannot do, and explain those things to you in plain language. This patent aims to solve the problem by making your smart home self-aware and helpful.

Scientific Rationale and Prior Art

Let’s look at how the science behind this works and what has been done before. Most smart home systems today use voice assistants that know how to control connected devices. For example, you might say, “Turn on the lights,” and the system sends a simple command to the lights. The commands are usually mapped to a set of known skills or actions. If you ask for something new or more complex, the system may not understand or may just say, “Sorry, I can’t help with that.”

Some systems try to be more flexible by using software “skills” or “apps” that add new abilities. For example, a voice assistant can get a new skill that lets it control a vacuum robot. But the system still doesn’t really “know” what it has or what it needs. It just checks if the skill is present or not.

A few systems use device tables or lists to keep track of what is connected. But these lists are often simple and do not explain what the devices can actually do. They don’t connect user requests, device features, and possible upgrades in a smart way.

Some research has tried to use artificial intelligence (AI) to understand user requests better. This can help with more natural conversations, but most AI systems are used in big data centers, not in your home. This can cause delays and privacy concerns.

Another idea is to use “semantic search,” where the system tries to understand the meaning of your command, not just the words. But this can be slow and needs lots of computing power. Also, it often uses large language models (LLMs) that are hard to run at home.

What stands out in this patent is the use of something called Functional Semantic Identifiers (FSIDs). These are smart labels that connect user requests, device features, and possible improvements in a neat way. The system can “decode” what you say, match it to what is possible, and if it cannot do it, suggest what you need. All this can happen quickly, even on a small home computer or “edge” device, so your data stays safe and your commands are answered fast.

Unlike older systems, this one builds a richer picture of what your home can do. It creates a kind of “map” of devices, skills, and possible upgrades. When you ask for something, it can check this map, see if it can do the task, and suggest how to do it better. It keeps track of new devices you add or remove and learns over time.

This approach is new because it focuses on making the home system self-aware about its own abilities. It does this by breaking down requests into “semantic triplets” (simple parts like device, action, target) and matching them to what is possible. It also uses AI in a way that can run on local devices, not just in the cloud. This means less waiting, more privacy, and a better user experience.

Invention Description and Key Innovations

Now let’s explore how this new smart home system works and what makes it special.

Imagine you are at home and you say, “Who is at the front door?” Your voice is picked up by a device, like a smart speaker or microphone. The system uses a smart language model, like a mini-AI, to understand what you want. It turns your words into a special code called an FSID. This FSID is like a tag that says, “user wants to identify the person at the front door using a camera.”

The system then checks its “system status table.” This is a record of all devices and skills your smart home has. It looks for a match: “Do I have a camera at the front door? Do I have face recognition software?” If the answer is yes, it uses these to answer your question. If not, it checks for “compatible” devices, like maybe a camera without face recognition, or a different camera in another location.

If it finds a way to help, but not perfectly, it does the best it can and lets you know. For example, it might say, “Sorry, I don’t have a camera at the front door, but I see someone on the side camera.” Or, “I can check, but my camera doesn’t have face recognition yet.”

If the system cannot do what you ask, it tells you what is missing. Even better, it can suggest what to add, like, “Add a smart doorbell camera with face recognition for better results.” If you have a compatible device that does the job but not as well, the system can say, “I can help, but adding this device would make it work better.”

What is really smart is how the system keeps learning. When you add a new gadget, the system records its features using FSIDs. It updates the “map” of what the home can do. If you install new software (like a face recognition skill), it adds that too.

The FSID system is flexible. Each device or skill gets a unique code, and these codes are grouped by type (like “vision,” “speech,” “door,” etc.). When you say something, the AI matches your request to the right group and device. It can even handle new requests by breaking them down into device, action, and target. For example, “mic-device; identify; speaking-user” means using a microphone to figure out who is talking.

If you ever ask, “What can you do?” the system uses its FSID map to tell you about all its skills. If you ask, “Can you do this?” it checks if it can, and if not, tells you what is missing or what you could add.

All of this happens with fast, local computing. The AI model that translates your speech into FSIDs can run on a small home server or even on some smart devices. This means your private voice commands do not have to go to the cloud, making things faster and safer.

Another big innovation is how the system manages connections. When you add a new device, it sends a special “hello” message with its unique ID and FSID. The smart home controller records this and knows right away what the device can do. If you remove a device, the system updates itself.

The system is also smart about software. If you want to add a new skill, like “speaker recognition,” you can request it. If it is not there, the system suggests installing it. When you do, it records the new skill and updates its abilities.

The natural language model is not just a simple keyword matcher; it is a “transformer-based neural network.” This kind of AI is trained on lots of examples to understand different ways people might ask for the same thing. As you use it, the system can keep learning and improve its responses.

All of this is made possible by a smart design that keeps track of devices, skills, and their relationships. The system uses tables and unique codes to manage everything. It can work with many brands and types of devices, making it open and flexible.

To sum up, the key innovations are:

– The use of FSIDs to connect user requests, devices, and skills in a smart, flexible way.
– A local AI model that understands natural language and matches it to what the home can do.
– Fast, private responses because most of the thinking happens at home, not in the cloud.
– Clear feedback to users about what the home can and cannot do, and helpful suggestions for upgrades.
– Easy, automatic updates when you add or remove devices or skills.
– Compatibility with many brands and types of devices.

With this system, your smart home becomes a helpful partner. It lets you know its strengths and weaknesses, helps you get more out of your devices, and guides you in making your home even smarter.

Conclusion

Smart homes are changing, and people want more than simple voice commands and basic automation. This new patent helps homes become aware of their own abilities, making them more helpful, friendly, and easy to use. By using functional semantic identifiers, smart language models, and smart device management, your home can now answer your questions, tell you what it can do, suggest improvements, and keep getting better as you add new devices or skills.

If you are thinking of upgrading your smart home, or building a new one, look for systems that offer this level of self-awareness and helpful feedback. It will make your daily life easier, safer, and a lot more enjoyable.

Ready to make your home smarter than ever? This breakthrough in smart home functionality awareness is the key to unlocking a truly connected, helpful, and future-proof living space.

Click here https://ppubs.uspto.gov/pubwebapp/ and search 20250216827.