Ambient Noise Cancellation: User and Developer Insights
“If you aren’t able to explain simply, then you haven’t understood completely” — Wise Words by someone I know whose name I can't remember ;)
Noise bothers us in daily life. It affects our focus, communication, and music. Many people use headphones or earbuds to block noise. But they are not always good. They may cut us off from important sounds.
Open-Air Active Noise Cancellation (OANC) can help. OANC uses intelligent methods to make “anti-noise.” It comes from a speaker and stops the noise in our ears.
But OANC is hard to do. There are many problems and challenges. In this article, we will talk about the technical parts of OANC, like the noise types, the methods, the devices, and the results. We will also discuss the uses and benefits of OANC for different situations and areas.
To know how it works, we should first know what noise is and how it hurts us.
Noise impacts us, and we don’t even realize it.
Noise is any sound that we don’t like or want. Noise can come from many things, like nature, people, or machines. Noise can differ in how fast, loud, long, or where it comes from.
Noise can harm our health, happiness, and work. The World Health Organization says noise can cause hearing loss, stress, high blood pressure, heart problems, sleep problems, memory problems, and low quality of life. Noise can also make it hard to talk or hear other sounds. Noise can make music or different sounds worse.
So we want to reduce or stop the noise. But typical ways of noise reduction are not always reasonable or possible. Sound insulation uses materials to block or take in sound waves. But sound insulation can be costly, big, or complicated to use. Sound masking uses another sound to cover or hide the noise. But sound masking can be bad or annoying itself. Or it may not be what we like.
Here are some stats about noise and its effects:
- 2.5 billion people are expected to have hearing loss due to noise pollution by 2050.
- 30 million Americans are exposed to noise pollution above healthy levels.
- 100 million or around 20% of Europeans are exposed to noise pollution.
- USA, UK, Italy, and India are among the loudest countries in the world.
- The annual cost of noise pollution to Europe is £30 billion.
- Workplace noise can cause a 66% decrease in productivity.
- Noise can lead to a 50% drop in concentration in mind-intensive tasks.
- Noise can cause a 20–30% increase in errors.
- Noise can reduce verbal communication effectiveness by 30–40%.
These stats show how serious and widespread the noise problem is. That is why we need OANC to solve it.
OANC can give a better answer. It does not need any walls or extra equipment or sound to reduce noise. It uses math and engineering to make a sound wave opposite the noise wave. When these two waves meet at our ear, they stop each other because of destructive interference. This makes a quiet area around us without changing the environment.
In the next part of this article, we will see how OANC works more clearly and how it can help in different cases and fields.
Types of Noise
(Classification done by me for my idea)
This idea currently works for 5 different types of Sounds/Noise —
Continuous Noise
Continuous noise comes from objects or machines that run without interruption. These noises are noticeable and happen all around us wherever we go. Ex: In a car, a continuous noise is audible from the engine.
Intermittent Noise
Intermittent noises are infrequent but regular in your daily life. Generally, they come from loud bursts you notice but are not surprised by. Ex: People living near an airport may hear planes taking off and landing constantly. It’s a loud noise, but they’re not surprised by it.
Impulsive Noise
An impulsive noise is not regularly scheduled or recognized. Instead, it is like a surprising burst or sound that causes people to look up to see what’s going on. Ex: A waiter dropping a plate. When this happens, the restaurant generally calms down a little as people look around for the noise source.
Low-Frequency Noise
A low-frequency noise comes from objects around us in everyday life. A seemingly silent room still registers around 30–40 decibels sound levels. Ex: This noise comes from a heating or ventilation system in an office setting. In your home, it comes from the ticking of a clock.
Hybrid Noise
Hybrid Noise could combine one or more of the above 4 types. It is also a new type of noise that will be classified later on using Artificial Intelligence Annotation and classification methods.
These are the 5 categories we classified noise types into, and it pretty much covers the entire sound base, so my idea works for any noise — even a new type of noise that gets classified in the future. How does it do that? Well, that’s because we keep updating it regularly, so when there is a breakthrough and a new sound type is discovered, we’ll be quick to update our idea so that it works with that as well.
How this Idea Works
When sound wave “a)” is generated, this noise cancellation software can comprehend that and identify which category of the sounds mentioned above it falls into and sends out/releases sound wave b). In this case, both the sound waves cancel out, leaving you with silence. This is a property called ‘Destructive Interference.’
But if you don’t want the sound to be canceled out totally, and you want it to reduce in volume, then we can convey that to the software through the Mobile App, which has the option to change the request so that we don’t cancel out the sound wave, we just reduce it. Then, this software sends out a relatively low amplitude opposite sound wave, so it cancels out only a tiny portion of the total noise, reducing the intensity. This can be controlled, adjusted, and changed through the Mobile App, which works seamlessly.
Artificial Intelligence is also incorporated into this software, so it can perform tasks like sensing a prolonged intermittent noise and adjusting that without us giving it a command to do so and to sense any different types of noise.
Since this device can recognize sounds and classify them, it can also identify important sounds like a smoke alarm, etc., so when you’re not at home, the device can send a notification to the mobile app saying that it has detected the sound of a smoke alarm.
Since the software will be used in intense situations such as a fire, it's’ training also would be with utmost quality, and there won’t be any compromise in the quality of either the training data or the testing data to ensure that the software doesn’t send out a false alarm notification.
This Software is part of a device that has the following components —
The Entire System
Consists of 11 Separate Components
- Noise Listener
- AI Noise Type Classifier
- AI Noise Math Equation Formulator
- AI Emitting Wave Modeler
- Noise Counter Wave Emitter
- Resident Noise Definition Database
- Central Noise Definition Database (Cloud)
- Central AI Noise Model Builder (Cloud)
- AI Continuous New Noise Learner
- Mobile App Communicator
- Mobile App
AI Noise Type Classifier, AI Noise Math Equation Formulator, AI Emitting Wave Modeler, Resident Noise Def. Database, AI Continuous New Noise Learner, and Mobile App Communicator are all components of the home device (Fig.1.3).
The AI Noise Type Classifier is an AI model that classifies the noise listened to using Artificial Intelligence into one of the types of noises identified as per the knowledge of the Central Noise-Model database.
The AI Noise Math Equation Formulator processes and creates math equations using the sound wave data from the AI Noise Type Classifier.
The AI Emitting Wave Modeler inverses the math equation created by the AI Noise Math Equation to produce the sound wave inverse to the original noise wave (Fig.1.1)
The Noise Counter Wave Emitter converts is primarily a sound emitter of the inversed math equation created by The AI Emitting Wave Modeler back into an Inversed Sound Wave and emits that sound wave back into the surroundings to cancel the sound wave in the environment.
The Resident Noise Definition Database is a database of the most frequent noise recordings (5 or 10) stored locally on the home device.
The Central Noise Definition Database is a database in the cloud that stores every single observation recorded from all the individual devices.
Periodically, the Central AI Noise Model Builder creates different AI Models based on the noise data definitions available at the Central Noise Definition Database and stores the models back in the model repository available in the Central Noise Definition Database. These models are eventually pushed to the home devices through Edge AI Deployment for noise classification.
The AI Continuous New Noise Learner stands as an observer and records new noises it identifies (if any). This could also be used if the human wants to annotate any of his surrounding sounds as noises manually. This could act as a mechanism to learn new noises using Human-in-loop.
The Mobile App Communicator is the interface of communication between the home device and the mobile app, where the mobile app itself is the interface that the end user uses to customize his requests to the device, such as changing the intensity of the cancellation, changing settings, etc.
What makes this different from traditional Noise Cancelling
Traditional Noise Cancelling is flawed. You have to arm yourself with plastic, metal, and other materials called “earwear.” Assuming you want to disconnect from the entire real world while your mom keeps shouting at you in the back, NC earwear is great! But for us folks who want to stay here on earth, and still jam to music, or attend a meeting in peace, earphones aren’t the best solution.
Introducing an Advanced Noise-Canceling Software and Device that is unique to traditional ear-based solutions. Place it anywhere, like a speaker, to minimize external noise. By emitting imperceptible high or low-frequency sound waves, our invention effectively distorts the path of noise particles, and therefore we reshape their path, creating a peaceful, quiet environment.
This breakthrough technology enhances productivity, focus, and well-being in various settings, from offices to public spaces and transportation. Say goodbye to distractions and hello to a quieter, more serene world.
Sounds awesome? Well it is! It took me about a year to finalise the Idea and method, and about 8 months to complete the patenting process, so you’re looking at almost 2 year’s worth of hardwork! :)
What People Are Saying
“If and when this product becomes available to the general public, I will be the first to purchase this; this is a revolutionary product idea, and I think it has loads of potential.”
“Wow, this is amazing! I can finally enjoy some peace and quiet without blocking out the world.”
“This is a game-changer for noise reduction. I love how it can adapt to different types of noise and cancel them out effectively.”
“This is a brilliant invention. I can see how it can improve my health and well-being by reducing stress and enhancing concentration.”
“This is a very clever idea. I am curious about how it works and how I can use it in various situations and environments. How are you working on scaling it up and mass-production?”
“I love this idea, especially because I’ve got 2 kids at home, and they’re incredibly noisy, and my meetings tend to be turbulent. I’m wondering, are you working on large-scale implementation? Is your idea fit for working in public spaces, or is it only for closed spaces for now?”
“Bro, this is the solution we’ve all been waiting for. This is the end of noise as we know it; a world with less noise pollution is a world with one less problem.”
“Innovation at its finest is what this looks like. OANC is a very complex concept, and to have cracked it at 16 is very impressive! Keep it up!”
“I schedule my meetings and calls very late into the night just because of extreme background noise, but with this solution, I can finally have a night’s sleep without worrying!”
P.S. These are all impressions from the Shell Changemakers of Tomorrow Conference and other personal interactions around which the actual quotations revolved. Multiple people said similar things, so I clubbed them.
So, what’s next? Well, right now, I’m working with different companies to build my own prototype, so we’ll have to see where that goes!
Thanks so much! I really appreciate your time, I hope you you found value in this article!
