Connectivity and compute may power the edge, but without sensing, devices are blind, deaf, and disconnected from the world around them.
Sensing is what gives the edge its awareness. It’s the foundation for context—understanding what’s happening in the environment, who is interacting, and what has changed. In a smart edge ecosystem, sensing is the trigger, the input, and the bridge between raw data and intelligent action.
From Inputs to Experience
At its core, sensing at the edge is about capturing signals—motion, audio, voice, vision, location, touch, vital signs—and interpreting them in real time. These inputs power personalized, predictive outputs: removing loud city street noise during a voice call, dimming lights in your living room, or tuning your in-car audio based on who’s in the driver’s seat.
This real-world feedback loop depends on more than just sensors. It requires integrated sensing platforms that combine signal processing, data fusion, and AI models, all optimized for low-power, always-on operation.
For sensing to unlock its full potential of enabling applications across many industries, it must be tightly coupled with both AI and connectivity—forming a triad of edge intelligence.
Sensing at the Source: Why Local Intelligence Matters
According to ABI Research , one of the most important shifts in edge AI is toward ultra-low-power, sensor-level intelligence. Instead of sending all data to a central processor—or worse, to the cloud—devices increasingly process signals right at the edge.
This approach reduces latency, preserves privacy, lowers costs, and saves energy. But it requires sensing systems that are not just passive collectors—they must interpret data in real time.
Ultra-Wideband (UWB) technology that allows highly accurate location tracking, for instance, enables precise spatial awareness—knowing not just that a device is nearby, but where it is in the room, and how it’s moving. Combine that with always-on sound analytics, gesture recognition, or vision-based context, and you can create devices that are responsive, adaptive, and even anticipatory.
Ceva: Enabling Multi-Modal Perception at the Edge
Ceva’s IP portfolio was built for this moment—combining specialized DSPs, neural processing, and sensing software to help devices not just collect data, but understand it and use this intelligence to take action.
Our sensing and perception technologies include:
- MotionEngine™ – Delivers precise motion tracking and activity classification using Inertial Measurement Units (IMU) that measure motion, orientation, and acceleration in wearables, headsets, XR devices, robots, and smart remotes.
- RealSpace® – Provides multi-channel spatial audio rendering with precise head tracking to create realistic, immersive listening experiences for headsets, assistive hearing, and XR devices.
- ClearVox™ – Enhances voice communications in noisy environments through advanced, AI environmental noise cancellation, voice isolation and keyword spotting.
- AI-enhanced DSPs – Enables low-power vision and audio processing, with support for inference at the sensor edge.
Together, these components allow devices to fuse multiple input modalities—voice, motion, vision, location—and generate rich, real-time user context.
Where It Comes to Life: Use Cases in Action
- Smart home: A smart TV remote control uses MotionEngine to precisely track users hand motions to control an onscreen cursor, allowing intuitive content navigation.
- IoT hearables: A wireless earbud uses RealSpace to spatialize audio, detect head movements, and filter background noise based on the user’s movement and environment—all without waking a host processor.
- Robotics: Consumer and industrial robots use DSPs to fuse data from multiple sensors and use MotionEngine for accurate heading and orientation, all to efficiently navigate their environment.
- Automotive: In-cabin sensors and audio DSPs personalize settings based on the driver’s voice, location, and presence—adjusting seat position, audio profile, and environmental settings.
These are real-world examples of how Ceva’s sensing IP is shaping the smart edge.
Sensing Is the Next Competitive Layer
In a world where connectivity is table stakes and AI is increasingly commoditized, the next layer of competitive differentiation is context. Devices that know who you are, where you are, and what you’re doing can deliver experiences that feel intuitive, responsive, and natural.
But this level of interaction doesn’t happen by accident. It requires sensing IP that is:
- Power-efficient enough to run continuously
- Smart enough to filter information, fuse data, and infer context
- Flexible enough to work seamlessly with AI and wireless systems
This is Ceva’s advantage—and its customers’ opportunity.
The Edge Experience Starts with Awareness
To deliver intelligent outcomes, edge devices must first perceive their environment. Sensing is the first step in that journey.
The Smart Edge doesn’t just process and connect. It understands. And with Ceva’s sensing and perception technologies built in, it understands in real time, in context, and at scale.
Chad Lucien