[Editor's Note] While conventional AI focuses on inference and generation within digital data, Physical AI directly acts and reacts in the real world through sensors, edge computing, robots, and control systems. The implementation of Physical AI can significantly advance industrial innovation and automation because it directly acts and solves problems in the real world, and it directly interacts with the real world. Accordingly, global companies such as Nvidia, Tesla, and Google are making massive investments in Physical AI, and the related market is expected to grow explosively. To implement this Physical AI, recognition technologies such as sensors, as well as edge computing and embedded systems for real-time data processing, local computing, robotics, and control technologies are essential. Accordingly, e4ds News has prepared a series of articles to examine the core technologies and implementation strategies of physical AI, including the concept, market outlook, related technologies, and actual cases.


The era of 'physical AI' is coming, where artificial intelligence (AI) moves and interacts directly in the real world, moving beyond the digital realm where it generates text and images.

As various forms of physical AI, such as self-driving cars, drones, and humanoid robots, spread across industrial settings and daily life, sensors are attracting attention as a core technology.

Sensors are 'sensory organs' that allow physical AI to perceive and react to the external world, just like the five senses of humans.

■ Technology expanded from the five senses

Sensors used in physical AI are broadly categorized into visual, auditory, tactile, position/motion, and environmental sensors.

Representative visual sensors include cameras, LiDAR, radar, and infrared sensors.

Cameras are used for lane recognition and object detection, lidar for 3D map creation and distance measurement, and radar for speed detection.

Acoustic sensors include microphones and ultrasonic sensors.

It is essential for voice recognition, sound direction tracking, and close-range obstacle avoidance.

Tactile sensors detect pressure, vibration,Force sensors applied to robotic hands or skin enable delicate object manipulation and safe human-robot interaction.

Position and motion sensors, such as IMU (accelerometer/gyroscope), GPS, and magnetic sensors, are used to maintain the balance and track the path of drones and robots.

Environmental sensors include temperature, humidity, gas, and light sensors to detect environmental changes in industrial sites or living spaces.

■ A bridge connecting the real world and AI

Sensors are not simply devices that collect data; they are the starting point for physical AI to achieve autonomy and adaptability.

From an environmental awareness perspective, external stimuli are converted into electrical signals so that AI can process them.

Additionally, collision avoidance in autonomous vehicles, altitude maintenance in drones, and balance control in robots require that sensor input be reflected immediately.

Additionally, sensor data serves as raw material for AI learning, enabling environmental adaptation and self-improvement.

In addition, it combines multiple sensor data to perform more accurate recognition and judgment. For example, self-driving cars use cameras, lidar, radar, and GPS simultaneously to comprehensively understand road conditions.

Looking at the sensor combinations for each case, autonomous vehicles perform road recognition and collision avoidance by combining cameras, lidar, radar, GPS, and ultrasonic sensors.

Drones use IMU, GPS, vision sensors, and ultrasonic sensors to ensure flight stability and route tracking.

Humanoid robots can maintain balance, manipulate objects, and interact with humans using IMUs, RGB-D cameras, force-torque sensors, tactile sensors, and microphones.

■ The competitiveness of physical AI

Reports and experts commonly define sensors as a core infrastructure for physical AI.

Without sensors, AI would be disconnected from the real world.

In particular, advances in sensor fusion and intelligent sensors are laying the foundation for physical AI to go beyond simple automation and enable it to collaborate with humans and act autonomously in complex environments.

Furthermore, sensor technology is directly linked to national competitiveness. In the autonomous vehicle and robotics industries, the domestic production and advancement of sensors are considered essential tasks, and major countries are designating them as strategic technologies and expanding R&D and investment.

■ Sensor advancements will lead to the evolution of physical AI.

The era of physical AI goes beyond mere "moving AI" to encompass intelligent systems that organically interact with the real world. At its core are sensors that replace the human five senses. The advancement of sensors will soon lead to the evolution of physical AI and will become a driving force for innovation across industry and society.