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From Sensor-Empowered Ubiquitous Computing to Embodied Intelligence: Architectures, Paradigm Evolution, and Emerging
Ali Jia1, Ziwei Cai2, Xiaoyuan Liu3
1Shanxi Province Intelligent Optoelectronic Sensing Application Technology Innovation Center, Yuncheng University, Yuncheng 044000, China.
Sensors (Basel, Switzerland)
|July 28, 2026
Summary
Highly integrated sensing systems are crucial for the intelligent evolution of AI, enabling embodied intelligence. This review explores advancements in sensors, communication, and learning for next-generation intelligent devices.
Area of Science:
- * Artificial Intelligence and Robotics
- * Intelligent Systems and Sensor Technology
Background:
- * Rapid AI development necessitates advanced technologies like mobile robots, wearable agents, self-driving cars, and UAVs.
- * Traditional discrete sensor architectures struggle to meet the speed, efficiency, and reliability demands of intelligent devices.
- * The integration of perception, communication, and computing accelerates system intelligence, ushering in the era of embodied intelligence.
Purpose of the Study:
- * To review key technological advancements driving embodied intelligence.
- * To clarify the implementation path for integrated sensing systems.
- * To highlight the transformation of sensors from passive tools to core components.
Main Methods:
- * Review of sensor technology, multi-modal perception, wireless communication, and edge computing.
- * Analysis of limitations in traditional sensors and independent computing models (latency, energy efficiency, reliability).
- * Introduction of advanced learning mechanisms: multi-agent systems, reinforcement learning, and federated learning.
Main Results:
- * Highly integrated sensing systems offer superior performance over traditional architectures.
- * Innovative learning mechanisms are key drivers for embodied intelligence development.
- * Comparison of application scenarios between traditional and embodied intelligence paradigms.
Conclusions:
- * Sensors are now central to perception-action loops in intelligent systems.
- * Embodied intelligence requires advancements in integrated sensing, communication, and learning.
- * Future research should address challenges in standardization and explore new directions.
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