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Signals All Around Us

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Collection: Signal Processing

Signals are all around us, more so than we might realize. Almost any modern communication technology relies on signals. Signals are commonplace enough that many school-aged children will likely also recognize and understand what they are and how they affect our lives. 

According to IEEE Signal Processing Society (SPS), signal processing is a branch of electrical engineering that models and analyzes data representations of physical events as well as data generated across multiple disciplines. 

Much of the technology we use every day relies on signals. Let’s explore just some of the many applications of signal processing. 

Speech Recognition

According to SPS, speech recognition technology collects spoken data, interprets it, and generates an output in the form of words. Recorded soundwaves of spoken data is converted into an electrical signal which is generated into a word. Recent advancements in machine learning and AI have made speech to text a commonplace application such as on phones and digital watches.

One notable example of speech to text for school-aged children is the Speak and Spell.  In 1978, the Texas Instrument Speak and Spell launched as the industry’s first digital signal processing integrated processor, the TMS5100. An innovative digital game for children learning how to read and spell, the Speak and Spell was one of the earliest examples of speech to text.

You can read more about the Speak and Spell and how it was an IEEE milestone in this IEEE Spectrum article.

Hearing Aids

Signal processing is used in hearing aids by collecting sounds as input data and then amplifying what the user hears in the output. The functionality of hearing aids has increased significantly in recent years. Signal processing technology can determine which sounds should be amplified and which should be disregarded (such as background noise). 

Autonomous Driving

Signal processing is what makes the once dream of autonomous driving a reality. Technologies within these cards acquire data from the environment outside of the car and need to transfer it to usable information for the mechanisms of the car. The ability to collect, interpret, and transfer this data in the form of signals is what makes autonomous driving possible. 

Image Processing

Image processing and analysis are a huge part of our everyday life that rely on signal processing technology. Most photos today are digital. That means they have a unique fingerprint or blueprint. The process of collecting this data, analyzing it, and then creating output data that can be used to communicate information about the photo and then alter it is signal processing. Every smartphone has applications that use image processing. A common application is filters for pictures. 

Another example is applications within medical imaging such as computer aided diagnosis. Imaging technology using signal processing is able to capture data in the form of an image, transform it into a signal, and then provide an output in the form of another image after interpreting and analyzing the data in the form of a signal. Medical Resonance Imaging (MRI) uses radio frequency pulses to spin hydrogen atoms out of place. As they realign to their normal state, they emit a signal. Collecting a vast array of these signals over a given space is what creates the image produced from an MRI.

Machine Learning

Many applications of signal processing may contribute to machine learning. According to Geeks for Geeks, machine learning is a form of AI that improves itself as it collects data from usage. It allows computers the freedom to learn without being programmed. A computer may learn from collecting data as an input and using signal processing to transform it into another output. One example of machine learning is through the text message applications on smartphones that use speech recognition. Overtime, smartphones learn what words or spellings are most likely to be spoken by the user based on their history. As the user uses words or spellings of words more frequently, the speech recognition technology becomes more likely to recommend the most frequently used word as dictations are made. 

Signal Processing Resources for School-Aged Students

IEEE’s TryEngineering empowers educators and volunteers to foster the next generation of technology innovators. TryEngineering provides quality resources to inspire and engage pre-university students. Engineers and educators across various disciplines helped to create these resources.

TryEngineering and the IEEE Signal Processing Society (SPS) are proud to announce a strategic partnership with the goal of developing high quality pre-university content to inspire and educate the next generation of communications professionals. SPS’s experts in signal processing technology are working with the IEEE Pre-university team to create content for STEM outreach.

To better navigate all of the resources that SPS has to offer for pre-university STEM education, TryEngineering is launching the TryEngineering Signal Processing Webpage. This resource will help school-aged children find all of the TryEngineering signal processing-themed resources in a one stop shop. The page offers the ability to explore various functions and applications of signal processing such as speech recognition, video compression, computational imaging, and more. Some of the resources you’ll find include this lesson plan on adaptive design for devices such as hearing aids and this article about a student who developed a wearable tracking device to assist with social distancing during the COVID-19 pandemic. The page also offers information about how pre-university students can explore a future education or career path in signal processing. Be sure to check out the page today. 

You can also get started learning with this list of videos that cover a range of topics in signal processing.  

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