Next-Gen Living: How AI Is Transforming Everyday Life

Artificial Intelligence (AI) is transforming modern living by employing personal assistants like Alexa and Google Assistant to control smart devices through voice commands. The impact of AI extends far beyond convenience, offering significant advantages in the automation of repetitive tasks, enhanced decision-making through data analysis, personalized customer experiences, increased productivity, and new opportunities for innovation. Embracing AI ensures competitiveness by optimizing operations, enhancing customer experiences, and driving inventions. The full potential of AI will be realized when the technology is ubiquitous and spans from the cloud to the Edge and endpoints.

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AI Systems Design

Edge AI systems consist of specialized hardware and software components, enabling the capture, processing, and analysis of sensor data locally (Figure 1). These systems include sensors and actuators for data acquisition, integrated with processing units and memory for data storage. However, modern sensors have inherent processing capabilities for preliminary data filtering and transformation. Due to limited computational resources at the Edge, pretrained, (use-case-specific) models are needed on the edge devices to optimize performance. To understand more about the AI system architecture and workflow, Click here

Figure 1: Components of Edge AI (element14)

Click here to know on ‘AI Revolution: From Algorithms to Real-World Impact’

Smart Home

The rise of AI technology has transformed the concept of a “smart home” into a reality for millions worldwide. Modern homes equipped with AI-driven systems are becoming intelligent ecosystems that learn, adapt, and make decisions to simplify and enhance lifestyles.

Smart Speakers: AI-powered smart speakers like Amazon Alexa, Google Assistant, and Apple Siri transform smart homes by interpreting complex commands, controlling smart devices, answering questions, and providing personalized recommendations using Natural Language Processing (NLP).
Smart Thermostats: Utilize AI to optimize energy consumption and reduce bills by learning user preferences and adjusting the temperature based on monitoring weather conditions and occupancy.
Smart Appliances: Home appliances with built-in AI, like refrigerators and washing machines, utilize sensor data and algorithms to monitor items inside the fridge, predict maintenance needs, optimize wash cycles, and adjust settings for optimal efficiency.
Multimedia Systems: Modern entertainment systems can provide personalized channel (movies or music) recommendations and monitor human presence to save energy, while lighting systems can automatically adjust brightness and colour temperature to simulate natural daylight and create a relaxing atmosphere.

Click here to learn about “Implementing AI and ML with embedded devices”.

Security and Surveillance

The latest generation of security systems are equipped with AI/ML to run facial recognition, parcel detection, and even theft detection. This is only possible with advanced machine learning and deep learning algorithms that analyze camera feeds, user behavior and system logs, all in real-time. Furthermore, AI/ML enables garage door or parking barrier automation by opening and closing doors based on recognizing a person or registered car approaching.

Click here to learn about “The modern challenges of facial recognition”.

Personal Healthcare

Most wearable devices now use AI to analyze data, provide actionable insights, and adapt to individual user needs in real-time. AI-powered wearables provide personalized fitness recommendations based on user activity, heart rate, and goals. It captures and analyze the data from accelerometers, gyroscopes, and heart rate sensors to track steps, calories burned, and workout intensity and provide fitness recommendations to achieve personal goals. For example, Fitbit analyses user activity levels, including breathing and sleep patterns. Apple Watch can identify accident or fall detection and contact predefined emergency services or contact persons. With AI’s help, some devices can also help manage chronic diseases like diabetes by monitoring glucose levels and providing actionable insights. Similarly, wearables are vital in mental health and stress management, as well as tracking stress levels and offering mindfulness exercises or breathing techniques.

Click here to learn about “MEMS sensors used for advanced ML implementation”.

Where to Start?

The architecture of AI is changing the world as we know it in multiple domains, from our day-to-day gadgets to healthcare, and making things easier. With the fast-changing environment of AI, engineers and developers must stay updated with new trends and technologies. If you want to take a dip into the deeper waters of AI and understand the building blocks of this domain with knowledge of application in real-time projects, then refer to our Technical Resources AI Hub. From image classification and speech recognition to condition monitoring and predictive maintenance, AI Hub provides a full set of product solutions, resources, and expertise to help you unlock the maximum Edge of AI. To get you started, here are some AI-enabled platforms to help you launch:

MAX78000 evaluation kit with convolutional Neural Network accelerator for AIoT applications

The ADI’s MAX78000 AI microcontroller is ideal for Edge IoT applications, combining energy-efficient AI processing with ultra-low-power microcontrollers.

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BeagleY-AI, low-cost, open-source full-featured SBC for today’s embedded AI workloads

The BeagleY-AI is an open-source, single-board computer based on TI’s AM67A ARM-based vision processor, designed explicitly for Edge AI applications.

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Raspberry Pi 5 and AI HAT+, built-in Hailo AI accelerator for cost effective and power-efficient high-performance AI applications

The Raspberry 5 and AI Hailo-8L AI acceleration HAT, features a built-in neural network accelerator, turning your Raspberry Pi 5 into a high-performance, accessible, and power-efficient AI machine.

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STM32N6 Discovery kit featuring ST Neural-ART Accelerator and NeoChrom 2.5D GPU for power-efficient Edge AI applications

The STM32N6 uses the Arm® Cortex®-M55 CPU and ST Neural-ART accelerator for power-efficient Edge AI applications.

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i.MX 93 applications processor with integrated Neural Processing Unit (NPU)designed for audio, voice and consumer AIoT applications

The NXP i.MX93 application processor delivers efficient machine learning (ML) acceleration and advanced security with an integrated EdgeLock® secure enclave to support energy-efficient edge computing.

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Conclusion

Artificial Intelligence is no longer a dream for the future; it’s an ongoing phenomenon. AI is revolutionizing life, from smart homes and personal healthcare to high-level security. The more this technology develops, the more unlimited opportunities for innovation and efficiency are created. To keep ahead, businesses and developers must adopt AI and use all its potential. The future of next gen living will be powered by AI.