Artificial intelligence (AI) is having an ever-increasing effect on the world as it becomes more and more digitally-focused.
We have already discussed how AI, automation and robots are all impacting the logistics sector, but this impact isn’t exhausted in the production process. In fact, we’re using AI features in our everyday lives without even giving it a second thought. From voice assistants that tell you whether it’s raining outside to wearable devices that tell you whether you’ve done enough steps today, we are surrounded by AI input, and that’s only going to increase.
A report by Markets and Markets claims that the global AI market is expected to be worth $1,345 billion by 2030, growing at a compound annual growth rate (CAGR) of 36.8% from the figure of $150.2 billion it’s valued at in 2023. With that exponential growth over the next seven years, AI will surely continue to have a significant influence over how humans live. Manufacturers will look to streamline the production process further with automation and designers will try to create innovative designs and impressive features with AI tools. In this article, we’ll explore the multifaceted role that AI plays in consumer electronics, highlighting five ways that AI has transformed the industry.
The Technology Behind AI in Consumer Electronics
There are many types of technology behind different features of AI in consumer electronics. For example, machine learning is a type of artificial intelligence that uses data and algorithms to notice patterns in human behaviour, and gradually improves its accuracy as a result. In wearable devices, sensors are key to gathering data about the body and feeding it back to the device. Other technologies like natural language processing (NLP) and speech recognition are also key to facilitating and improving AI features in consumer electronics. Read on to find out ways in which AI is influencing the consumer experience.
Personalised Experiences
User Preferences
AI algorithms are capable of learning from user interactions and gaining knowledge about their behaviours, interests, and consumption habits. Devices can change as a result and provide material, suggestions, and recommendations that are personalised for each user. As an illustration, streaming services like Netflix employ AI to analyse user viewing patterns and make tailored movie and TV programme suggestions that suit their preferences.
Tailored Content and Shopping
AI algorithms filter content for consumers to maximise their experience on social media and news apps. AI has been incorporated into e-commerce platforms to offer individualised buying experiences. These platforms examine user browsing and purchasing patterns to make recommendations for goods that match their preferences. By saving consumers’ time and exposing them to things they are likely to find appealing, conversion rates are increased.
Voice Assistants
For the purpose of comprehending and interpreting spoken language, voice assistants use NLP and AI algorithms. As a result, user interactions with gadgets become more conversational and user-friendly because they no longer require users to speak in accordance with predetermined orders. Voice assistants’ ability to operate hands-free is one of their most important benefits. It is possible for users to carry out tasks, view information, manage smart devices, and even make purchases without having to physically interact with a device like a smartphone or remote control.
Health Monitoring with Wearable Devices
Wearable devices which can track a range of valuable health metrics such as heart rate, blood pressure and oxygen saturation took the fitness industry by storm when they were introduced to the market. As they’ve developed over the years, they now offer multiple benefits, including:
Early Disease Detection
AI is able to spot early warning signs of health problems by analysing trends in health data across time. This data can be viewable via an app so the user can better understand patterns. If required, users may receive alerts about potential health risks, allowing them to seek medical care as soon as possible.
Sleep Monitoring
Wearables use sensors like accelerometers and heart rate monitors to track sleep patterns throughout the night. By analysing movements, heart rate variability, and other physiological signals, AI algorithms can differentiate between different sleep stages, such as deep sleep, REM (rapid eye movement) sleep, and light sleep. Some devices then give users a ‘sleep score’ out of 100, so they can better understand whether they are getting good sleep.
Stress and Mental Health Tracking
Stress-related physiological signs including heart rate variability, skin conductance, and even breathing patterns can be detected by wearables. These devices continuously track these signals and analyse them using AI to spot patterns that indicate different levels of stress. Some wearables offer guided breathing exercises to help the user combat these signs of stress too.
For more information on how wearables work and how they’ve developed into a key everyday gadget, read our article.
Security
Devices have become a lot more secure thanks to the introduction of AI. With fingerprint recognition and two-factor authentication, devices like mobile phones and tablets have an extra layer of protection, which doesn’t add too much time to the user experience either.
Fingerprint Recognition
As we all learnt at school, everyone has a unique DNA make-up, meaning fingerprints are exclusive to the beholder. Fingerprint recognition relies on these distinctive ridges on a person’s fingertip to gain access to a device. AI algorithms enhance accuracy by matching fingerprint images with stored templates, making it a popular biometric method in smartphones and access control systems.
Two-factor Authentication
Two-factor authentication or two-step verification is a process in which the user provides two pieces of evidence to verify themselves. It usually requires a user’s password, followed by a number of different methods to verify their identity. This extra step makes it much more difficult for a hacker to access a person’s account. Types of two-factor authentication include:
- SMS verification – When a user tries to login to their account via laptop, a one-time code is provided through SMS to the user’s registered mobile phone. To complete the login process, the user must enter this code via the original login method.
- Biometric authentication – Users identify using a distinctive biometric characteristic, using either a fingerprint, facial or iris scan. This method may need specialised technology but is very safe because biometric data is hard to copy.
- Push notifications – When attempting to log in, users receive a push notification on the registered mobile device. From the notification, they can choose to accept or reject the login request. This method may also use either biometric or PIN/password authentication to finalise the login process.
- Time-based one-time password (TOTP) – Users install a TOTP app on their mobile devices. A shared secret key is provided by the service during setup and the app generates a new one-time password which changes every 30 seconds. This code needs to be entered by the user in the time frame when prompted.
Find out here why industrial network security and cybersecurity are important.
Conclusion
AI has had a major impact on consumer electronics in various ways over the last decade or so. Devices can adapt to individual preferences, delivering tailored content and recommendations. Consistent health monitoring has been made simpler, empowering users to proactively manage well-being through wearable devices. In addition to this, innovative technologies like biometric authentication provide a seamless way of adding an extra layer of protection to sensitive data. As a whole AI has redefined consumer electronics, enhancing convenience, safety, and the overall quality of user interactions with technology. As technology advances, we can only assume that this impact will be multiplied over the coming years.
