{"id":3266,"date":"2026-04-23T13:26:10","date_gmt":"2026-04-23T20:26:10","guid":{"rendered":"https:\/\/quanergy.com\/?p=3266"},"modified":"2026-04-27T21:13:15","modified_gmt":"2026-04-28T04:13:15","slug":"3d-lidar-physical-ai","status":"publish","type":"post","link":"https:\/\/quanergy.com\/es\/3d-lidar-physical-ai\/","title":{"rendered":"3D LiDAR: The Sensing Layer That Makes Physical AI Real"},"content":{"rendered":"<p><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1\"><h2><strong>3 things to know before you read<\/strong><\/h2>\n<ul>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Generative AI works in 1D and 2D. Physical AI demands 3D, and cameras can&#8217;t provide it.<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">3D LiDAR is the missing sensing layer: real-time, centimeter-accurate, privacy-safe, and deployable where cameras legally can&#8217;t go.<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Jensen Huang calls Physical AI a $50 trillion market. The companies that own the sensing infrastructure will own the value.<\/span><\/li>\n<\/ul>\n<h2><strong>The Next Wave of AI Runs on Entirely Different Fuel<\/strong><\/h2>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Generative AI took the world by storm. But the next wave, Physical AI, will be ten times larger, and it runs on entirely different fuel: real-time 3D perception of the physical world. Without it, autonomous systems are blind. And cameras, the world&#8217;s most deployed sensor, can&#8217;t provide it. Stereo vision introduces latency, error and massive compute consumption that can never be designed around. Ultimately, 3D sensors will always win in the long run.<\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Physical AI refers to AI systems that perceive, reason about, and act within the physical world, not just processing data in software, but directly sensing and interacting with real environments through hardware. A robot navigating a warehouse, an airport system detecting a crowd bottleneck before it becomes a crisis, an autonomous vehicle braking for a child: all of these require the same core capability. They need to understand the world in three dimensions, in real time, without ambiguity.<\/p>\n<p><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Jensen Huang, CEO of NVIDIA, estimates that Physical AI represents a <\/span><a style=\"font-size: 20px;\" href=\"https:\/\/youtu.be\/gwW8GKwHB3I?si=hxQbK84J7hMUt5Ni&amp;t=655\" target=\"_blank\" rel=\"noopener noreferrer\" data-fusion-font=\"true\">$50 trillion market opportunity<\/a><span style=\"font-size: 20px;\" data-fusion-font=\"true\">, larger than every technology wave before it combined. The reason is simple: the physical world is where value is created, lost, and protected. And most of it has never been instrumented.<\/span><\/p>\n<blockquote>\n<p><strong><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\">&#8220;The next wave of AI isn&#8217;t about generating text or images. It&#8217;s about understanding and acting in the physical world in real time.&#8221;<\/span><\/em><\/strong><\/p>\n<\/blockquote>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">3D LiDAR is that core layer. It provides depth, dimension, position, and speed, turning raw motion in the physical world into structured, usable intelligence. Cameras have to guess at depth from flat images, at high compute cost and with unavoidable error. LiDAR measures it directly. Quanergy has spent a decade building the perception software that turns LiDAR data into decisions.<\/p>\n<blockquote>\n<p><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\"><b>&#8220;Generative AI works in 1D and 2D. Physical AI demands 3D, and cameras can&#8217;t provide it.&#8221; #PhysicalAI #LiDAR #Quanergy<\/b><\/span><\/em><\/p>\n<\/blockquote>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-2 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-1 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-2\"><h2><strong>Why 3D LiDAR, and Why Now<\/strong><\/h2>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">Georgetown University&#8217;s Center for Security and Emerging Technology (CSET) puts it plainly:<\/strong><\/p>\n<blockquote>\n<p><b><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\">&#8220;Large language models are one-dimensional&#8230; Image- and video-generation models are two-dimensional&#8230; None of these models can understand or interpret the 3D world.&#8221;<\/span><br \/>\n<\/em><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\">&#8212; CSET Physical AI Report, 2024<\/span><\/em><\/b><\/p>\n<\/blockquote>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-3 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-2 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-image-element\" style=\"--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\"fusion-imageframe imageframe-none imageframe-1 hover-type-none\"><img decoding=\"async\" width=\"1927\" height=\"575\" alt=\"3D LiDAR point cloud visualization representing real-time spatial intelligence for Physical AI systems\" title=\"3D LiDAR Point Cloud for Physical AI\" src=\"https:\/\/quanergy.com\/wp-content\/uploads\/3d-lidar-physical-ai-3d-point-cloud-visualization.png\" class=\"img-responsive wp-image-3289\" srcset=\"https:\/\/quanergy.com\/wp-content\/uploads\/3d-lidar-physical-ai-3d-point-cloud-visualization-200x60.png 200w, https:\/\/quanergy.com\/wp-content\/uploads\/3d-lidar-physical-ai-3d-point-cloud-visualization-400x119.png 400w, https:\/\/quanergy.com\/wp-content\/uploads\/3d-lidar-physical-ai-3d-point-cloud-visualization-600x179.png 600w, https:\/\/quanergy.com\/wp-content\/uploads\/3d-lidar-physical-ai-3d-point-cloud-visualization-800x239.png 800w, https:\/\/quanergy.com\/wp-content\/uploads\/3d-lidar-physical-ai-3d-point-cloud-visualization-1200x358.png 1200w, https:\/\/quanergy.com\/wp-content\/uploads\/3d-lidar-physical-ai-3d-point-cloud-visualization.png 1927w\" sizes=\"(max-width: 640px) 100vw, 1200px\" \/><\/span><\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-4 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-padding-bottom:0px;--awb-margin-bottom:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-3 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-3\"><p style=\"font-size: 20px;\" data-fusion-font=\"true\">Physical AI has four requirements that no existing 2D sensor can fully satisfy:<\/p>\n<ul>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Grounding in the real world. The system must deal with noisy, unpredictable, continuously changing physical environments, not clean, structured datasets.<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Real-time operation. Decisions need to happen in milliseconds. A robot picking up an object or a self-driving car braking can&#8217;t wait for a cloud round-trip.<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Spatial and temporal reasoning. The AI must understand 3D space, object permanence, physics, and how things change over time.<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Closed-loop control. The system constantly senses, decides, acts, observes the result, and adjusts, rather than making one-off predictions.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-size: 20px;\" data-fusion-font=\"true\">3D LiDAR satisfies all four. By emitting its own laser pulses and measuring the time they take to return, LiDAR creates a real-time 3D point cloud of everything in its environment, with centimeter-level accuracy, across ranges up to 300 meters, in any lighting condition, day or night. A single LiDAR sensor can replace <\/span><span style=\"font-size: 20px;\"><a href=\"https:\/\/quanergy.com\/es\/alliance-bernstein-transforming-corporate-spaces-into-interactive-experiences-with-quanergys-3d-lidar\/\" target=\"_blank\" rel=\"noopener noreferrer\">seven or more cameras<\/a><\/span><span style=\"font-size: 20px;\" data-fusion-font=\"true\"> at a fraction of the total installation and networking cost.<\/span><\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">LiDAR captures shape, position, and velocity, not faces or biometrics. It&#8217;s privacy-safe by design, deployable in environments where cameras are legally restricted or politically problematic. That isn&#8217;t a feature. It&#8217;s a structural advantage.<\/p>\n<blockquote>\n<p><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\"><b>&#8220;A single LiDAR sensor can replace 7+ cameras at a fraction of the cost, and it captures zero biometric data.&#8221; #PhysicalAI #LiDAR #Quanergy<\/b><\/span><\/em><\/p>\n<\/blockquote>\n<h2><strong>Physical Sec<span style=\"color: #004f9b;\">urity: Wh<\/span>y Every Swaying Tree Looks Like a Threat<\/strong><\/h2>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Perimeter security is a high-stakes game. Whether it&#8217;s a data center, a utility substation, or a rail corridor, intrusions can cost millions and threaten business continuity. Security teams have invested heavily in video analytics over the past decade. And yet the core problem persists: cameras react to any motion.<\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">A dog wandering past a perimeter fence. A gust of wind rustling tree branches. A car driving along an adjacent road. To a camera-based system, all these look like potential threats. The result is an industry-wide false alarm epidemic. Industry studies put camera-based perimeter security false alarm rates at 90% or above in complex outdoor environments. Quanergy deployments in similar environments bring that down to under 5%.<\/p>\n<blockquote>\n<p><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\"><b>&#8220;Desensitized operators stop reacting. Missed threats slip past. The false alarm problem isn&#8217;t a nuisance. It&#8217;s a security failure.&#8221;<\/b><\/span><\/em><\/p>\n<\/blockquote>\n<p><span style=\"font-size: 20px;\"><a href=\"https:\/\/quanergy.com\/wp-content\/uploads\/Quanergy-LiDAR-vs-RADAR-for-Security-Applications.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">Radar has a different problem<\/a><\/span><span style=\"font-size: 20px;\" data-fusion-font=\"true\">. It&#8217;s typically optimized for either low-speed motion (people) or high-speed motion (vehicles), not both at once. In environments like utilities and rail, where both threats coexist, that gap is dangerous.<\/span><\/p>\n<p><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Across critical infrastructure, the financial stakes are real. According to <\/span><a href=\"https:\/\/www.wired.com\/story\/metal-theft-epidemic-copper-steel\/?utm_source=chatgpt.com\"><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">Wired<\/strong><\/a><span style=\"font-size: 20px;\" data-fusion-font=\"true\">, metal theft has become a global epidemic. Copper is repeatedly stolen from rail infrastructure, substations, and data center cooling systems because legacy sensors can&#8217;t distinguish a thief moving slowly among vehicles and equipment from background motion.<\/span><\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Quanergy&#8217;s 3D LiDAR perception platform changes this. It classifies every object in the scene, tracks each one as it moves through the environment, and triggers alerts only when behavior matches a defined threat pattern: loitering, trespassing, tailgating, boundary crossing. No faces. No biometrics. No false alarms from wind or wildlife.<\/p>\n<blockquote>\n<p><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\"><b>&#8220;Camera-based perimeter security generates up to 90% false alarms. Quanergy 3D LiDAR brings that to under 5%.&#8221; #PhysicalAI #LiDAR #Quanergy<\/b><\/span><\/em><\/p>\n<\/blockquote>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-5 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-4 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-5 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-4\"><h2 style=\"margin: 16.0pt 0in 6.0pt 0in;\"><b>Smart Spaces and Airports: Crowd Intelligence Requires 3D<\/b><\/h2>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-6 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-padding-bottom:0px;--awb-margin-top:0px;--awb-margin-bottom:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-6 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-5\"><p style=\"font-size: 20px;\" data-fusion-font=\"true\">Airports are among the most complex motion environments on earth. At any given moment, thousands of passengers are walking, pausing, turning around, entering queues, clustering near gates, and interacting with staff. Cameras need to process every image set to arrive at a guess of the most important information: what is physically present where. Airport operators need precise, real-time answers to questions cameras can&#8217;t answer at scale:<\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-7 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-7 fusion_builder_column_2_3 2_3 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:66.666666666667%;--awb-margin-top-large:0px;--awb-spacing-right-large:2.88%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:2.88%;--awb-width-medium:66.666666666667%;--awb-order-medium:0;--awb-spacing-right-medium:2.88%;--awb-spacing-left-medium:2.88%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-6\" style=\"--awb-margin-top:40px;\"><ul>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Where are bottlenecks forming, and how fast are they growing?<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">How long has a specific queue been at this length?<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">How many staff should be dispatched to Gate C in the next ten minutes?<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">How is retail dwell time correlated with gate assignments?<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-8 fusion_builder_column_1_3 1_3 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:33.333333333333%;--awb-margin-top-large:0px;--awb-spacing-right-large:5.76%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:5.76%;--awb-width-medium:33.333333333333%;--awb-order-medium:0;--awb-spacing-right-medium:5.76%;--awb-spacing-left-medium:5.76%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-image-element\" style=\"--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\"fusion-imageframe imageframe-none imageframe-2 hover-type-none\"><img decoding=\"async\" width=\"600\" height=\"353\" alt=\"Travelers at Vancouver airport with faces blurred, representing privacy-safe people counting using 3D LiDAR\" title=\"3D LiDAR People Counting at Vancouver Airport\" src=\"https:\/\/quanergy.com\/wp-content\/uploads\/lidar-people-counting-vancouver-airport-privacy-safe.png-600x353.png\" class=\"img-responsive wp-image-3292\" srcset=\"https:\/\/quanergy.com\/wp-content\/uploads\/lidar-people-counting-vancouver-airport-privacy-safe.png-200x118.png 200w, https:\/\/quanergy.com\/wp-content\/uploads\/lidar-people-counting-vancouver-airport-privacy-safe.png-400x235.png 400w, https:\/\/quanergy.com\/wp-content\/uploads\/lidar-people-counting-vancouver-airport-privacy-safe.png-600x353.png 600w, https:\/\/quanergy.com\/wp-content\/uploads\/lidar-people-counting-vancouver-airport-privacy-safe.png-800x471.png 800w, https:\/\/quanergy.com\/wp-content\/uploads\/lidar-people-counting-vancouver-airport-privacy-safe.png-1200x706.png 1200w, https:\/\/quanergy.com\/wp-content\/uploads\/lidar-people-counting-vancouver-airport-privacy-safe.png.png 1635w\" sizes=\"(max-width: 640px) 100vw, 400px\" \/><\/span><\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-8 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-9 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-7\"><div><\/div>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Cameras capture images. They don&#8217;t track the flow of people across a terminal as a unified, three-dimensional stream of motion. To get meaningful intelligence from cameras across a large airport terminal, operators would need hundreds or thousands of sensors, plus the networking, cabling, and integration infrastructure to connect them, at a cost that quickly becomes impractical.<\/p>\n<p><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Vancouver International Airport (YVR), voted the best airport in North America, faced exactly this problem. After deploying Quanergy&#8217;s <\/span><a style=\"font-size: 20px;\" href=\"https:\/\/quanergy.com\/es\/products\/q-track\/\" data-fusion-font=\"true\">Q-TRACK<\/a><span style=\"font-size: 20px;\" data-fusion-font=\"true\"> LiDAR platform across the terminal, YVR gained real-time visibility into passenger volumes and wait times, plus the ability to trigger automated alerts the moment a queue approached a predefined threshold. In the words of Jason Williams, Dir<span style=\"font-size: 20px;\" data-fusion-font=\"true\">ector Software Development and Digital Channel at YVR: <\/span><\/span><a style=\"font-size: 20px;\" href=\"https:\/\/quanergy.com\/es\/vancouver-international-airport-3d-lidar-deployment\/\" data-fusion-font=\"true\">the system delivered precision that no camera-based approach could match.<\/a><\/p>\n<blockquote>\n<p><strong><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Gartner predicts:<\/span><br \/>\n<\/strong><b><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\">&#8220;80% of 3D imaging sensors for smart spaces will use LiDAR or millimeter-wave radar as the primary vision imaging sensor by 2030.&#8221;<\/span><br \/>\n<\/em><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\">&#8212; Gartner, Smart Spaces Technology Forecast<\/span><\/em><\/b><\/p>\n<\/blockquote>\n<p><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Beyond airports, the same intelligence layer applies to stadiums, convention centers, retail environments, and any space where understanding the flow and behavior of people translates directly into operational efficiency and revenue. Quanergy&#8217;s <\/span><a style=\"font-size: 20px;\" href=\"https:\/\/quanergy.com\/es\/products\/q-insights\/\" data-fusion-font=\"true\">Q-INSIGHTS<\/a><span style=\"font-size: 20px;\" data-fusion-font=\"true\"> platform delivers measurable improvements in queue wait times, occupancy and staffing optimization across airports, retail, and venues.<\/span><\/p>\n<blockquote>\n<p><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\"><b>&#8220;Cameras see images. LiDAR sees motion. For airport crowd intelligence, the difference is everything.&#8221; #PhysicalAI #LiDAR #Quanergy<\/b><\/span><\/em><\/p>\n<\/blockquote>\n<h2><strong>Transportation: Real-Time People Counting Where Cameras Fail<\/strong><\/h2>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">In rail stations and metro environments, the sensing challenge intensifies. Consider a seemingly simple question: how many people just boarded that train?<\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Now add the layers of complexity every transit operator faces: trains are large, fast, and reflective. People are small and slow-moving. Metal surfaces and glass doors create reflections that distort camera images. Lighting varies wildly between bright platforms and dark tunnels. And in international or privacy-sensitive transit environments, cameras introduce regulatory constraints that limit where and how they can be deployed.<\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">3D LiDAR cuts through this complexity. It tracks accurately across reflective surfaces, through varying light conditions, and without capturing any identifiable data. A major US transit agency deployed Quanergy&#8217;s LiDAR platform to dramatically increase safety by detecting people and vehicles on the tracks and therefore activating an alarm to stop an oncoming train in real-time, a mission-critical function that a camera system couldn&#8217;t achieve.<\/p>\n<h2><strong>Industrial Automation: What&#8217;s in My Path, and What Is It?<\/strong><\/h2>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Physical AI is transforming industrial automation, not by making robots more precise, but by making them perceptive. For the first time, machines can operate in dynamic, unstructured environments without exhaustive pre-programming. The sensor that makes this possible is 3D LiDAR.<\/p>\n<p><span style=\"font-size: 20px;\" data-fusion-font=\"true\">In warehouses, manufacturing plants, and fulfillment centers, <\/span><a style=\"font-size: 20px;\" href=\"https:\/\/quanergy.com\/es\/quanergy-lidar-vecna-robotics-material-handling\/\" data-fusion-font=\"true\">autonomous guided vehicles<\/a><span style=\"font-size: 20px;\" data-fusion-font=\"true\"> (AGVs) and autonomous mobile robots (AMRs) face a constant challenge: the environment is dynamic, unpredictable, and shared with humans.<\/span><\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">A pallet needs to be picked up. A worker walks into the robot&#8217;s path. A hanging load protrudes from a shelf. With 2D LiDAR or cameras, the AGV may detect that something is present, but it can&#8217;t determine what it is, and without that context, it can&#8217;t choose the right response. The result is unnecessary stops, slowdowns, and in the worst cases, accidents.<\/p>\n<p><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Quanergy <\/span><a style=\"font-size: 20px;\" href=\"https:\/\/quanergy.com\/es\/products\/q-vision\/\" data-fusion-font=\"true\">Q-VISION 3D LiDAR<\/a><span style=\"font-size: 20px;\" data-fusion-font=\"true\"> paired with perception software gives AGVs the ability to classify objects in real time: person, pallet, forklift, hanging load. Each classification carries a different response profile. That&#8217;s the shift from motion detection to motion intelligence, and it&#8217;s the difference between an AGV that stops at every shadow and one that operates continuously at full efficiency.<\/span><\/p>\n<blockquote>\n<p><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\"><b>&#8220;With 2D sensors, AGVs detect that something is there. With 3D LiDAR, they know what it is, and act accordingly.&#8221; #PhysicalAI #LiDAR #Quanergy<\/b><\/span><\/em><\/p>\n<\/blockquote>\n<h2><strong>The Quanergy Platform: From Motion Detection to Motion Intelligence<\/strong><\/h2>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Across physical security, smart spaces, transportation, and industrial automation, the pattern is the same: legacy sensing systems can detect that something is moving. They can&#8217;t tell you what it is, where it&#8217;s going, or what it means.<\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Quanergy&#8217;s platform fills that gap. We combine 3D LiDAR hardware with proprietary perception software: Q-TRACK for real-time object classification and tracking, and Q-INSIGHTS for analytics and business intelligence. Together they deliver a complete stack from light to insight. The platform is AWS-hosted, GDPR\/CCPA compliant, and integrates with 80+ existing VMS, PTZ, and enterprise security systems, so it deploys on top of what customers already have rather than requiring a rip-and-replace.<\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">The core technical capability that makes this work is object persistence: knowing that the person tracked in Zone A is the same person who appears in Zone B, despite occlusion, crowding, and changing context. This requires three capabilities that Quanergy has spent a decade engineering to 98%+ accuracy:<\/p>\n<ul>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Segmentation: defining the precise boundaries of each object in a scene.<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Tracking: following each object continuously through 3D space as it moves.<\/span><\/li>\n<li><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Association: maintaining object identity across time, zones, and transitions.<\/span><\/li>\n<\/ul>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">The result isn&#8217;t a better camera system. It&#8217;s a different category of sensing entirely, designed for a world where motion is the data and intelligence is the product.<\/p>\n<blockquote>\n<p><em><span style=\"font-size: 20px;\" data-fusion-font=\"true\"><b>&#8220;It&#8217;s not just motion detection. It&#8217;s motion interpretation. This is what Physical AI infrastructure actually looks like.&#8221;<\/b><\/span><\/em><\/p>\n<\/blockquote>\n<h2><strong>Frequently Asked Questions About 3D LiDAR and Physical AI<\/strong><\/h2>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">What is Physical AI and how is it different from Generative AI?<\/strong><\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Generative AI processes text, images, and video to produce new content. Physical AI perceives, reasons about, and acts within the physical world in real time, controlling robots, managing security systems, optimizing crowd flow, and automating logistics. Where Generative AI works in one or two dimensions, Physical AI requires accurate 3D spatial data. That&#8217;s what makes 3D LiDAR the key enabling technology.<\/p>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">Why is 3D LiDAR better than cameras for physical security?<\/strong><\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Cameras are passive 2D sensors that must guess at depth, consuming significant compute in the process and introducing unavoidable error, which is why false alarm rates in complex outdoor environments reach 90% or higher. They react to any motion, wind, animals, shadows, generating false alarm rates of 90% or higher in complex outdoor environments. 3D LiDAR actively measures position, speed, and object geometry in three dimensions, enabling precise classification of every object in a scene. Quanergy deployments consistently bring false alarm rates to under 5%, while also operating effectively in complete darkness, fog, and rain where cameras fail entirely.<\/p>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">How does 3D LiDAR protect privacy compared to cameras?<\/strong><\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">LiDAR captures geometric point cloud data: shape, position, and velocity. It doesn&#8217;t capture faces, skin tone, clothing, or any identifiable imagery. This makes it inherently GDPR and CCPA compliant, and deployable in environments like international airport terminals, healthcare facilities, and public transit, where cameras face significant regulatory or political constraints.<\/p>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">What is the addressable market for Physical AI and 3D LiDAR?<\/strong><\/p>\n<p><span style=\"font-size: 20px;\" data-fusion-font=\"true\">Anywhere tasks are carried out in the physical world. Jensen Huang of NVIDIA has described Physical AI as a <\/span><a style=\"font-size: 20px;\" href=\"https:\/\/youtu.be\/gwW8GKwHB3I?si=TUOphb-na3WzmQj7&amp;t=646\" target=\"_blank\" rel=\"noopener noreferrer\" data-fusion-font=\"true\">$50 trillion market opportunity<\/a><span style=\"font-size: 20px;\" data-fusion-font=\"true\">. Quanergy addresses a $26 billion serviceable segment spanning physical security, smart spaces (airports, venues, retail), transportation, and industrial automation. Gartner predicts that 80% of 3D imaging sensors for smart spaces will use LiDAR or millimeter-wave radar as the primary sensing modality by 2030.<\/span><\/p>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">How does Quanergy&#8217;s LiDAR platform work in airports and smart buildings?<\/strong><\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Quanergy&#8217;s Q-TRACK platform deploys LiDAR sensors across a facility to create a continuous real-time 3D map of every person and object in motion. The Q-INSIGHTS SaaS layer translates this data into operational dashboards: queue lengths, wait times, throughput rates, flow patterns, and staffing recommendations. It triggers automated alerts when predefined thresholds are crossed. A single LiDAR sensor can cover the area that would require seven or more cameras, at significantly lower total installation cost.<\/p>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">What industries does Quanergy serve?<\/strong><\/p>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Quanergy currently serves six verticals: physical security (data centers, utilities, critical infrastructure, rail), smart spaces (airports, stadiums, venues, retail), transportation (rail stations, metro systems, smart intersections), industrial automation (AGVs, AMRs, warehouse robotics), urban mobility (smart city traffic intelligence), and an emerging urban data marketplace that monetizes city-scale LiDAR data as a service.<\/p>\n<h2><strong>See 3D LiDAR in Action<\/strong><\/h2>\n<p style=\"font-size: 20px;\" data-fusion-font=\"true\">Quanergy has deployed 3D LiDAR Physical AI infrastructure across 150+ sites in six verticals, across international airports, data centers, rail corridors, and fulfillment centers. If you&#8217;re evaluating sensing technology for physical security, crowd management, or industrial automation, we&#8217;d be glad to show you what motion intelligence looks like in your environment.<\/p>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">Request a Demo: <\/strong><u><a style=\"font-size: 20px;\" href=\"https:\/\/calendar.app.google\/Zn2Qn8p9ZSu7S1EP7\" target=\"_blank\" rel=\"noopener noreferrer\" data-fusion-font=\"true\">quanergy.com<\/a><\/u><\/p>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">Download: <\/strong><u><span style=\"font-size: 20px;\" data-fusion-font=\"true\">LiDAR vs. Radar: The Technical Comparison<\/span><\/u><\/p>\n<p><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">Case Study: <\/strong><u><span style=\"font-size: 20px;\" data-fusion-font=\"true\">How Vancouver International Airport Transformed Passenger Intelligence with Quanergy<\/span><\/u><\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-9 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-10 fusion_builder_column_2_3 2_3 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:66.666666666667%;--awb-margin-top-large:0px;--awb-spacing-right-large:2.88%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:2.88%;--awb-width-medium:66.666666666667%;--awb-order-medium:0;--awb-spacing-right-medium:2.88%;--awb-spacing-left-medium:2.88%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-8\"><blockquote>\n<p><strong><span style=\"font-size: 20px;\" data-fusion-font=\"true\">About the Author<br \/>\n<\/span><\/strong><strong style=\"font-size: 20px;\" data-fusion-font=\"true\">Enzo Signore <\/strong><span style=\"font-size: 20px;\" data-fusion-font=\"true\">is CEO and Co-Founder of Quanergy Solutions, a Physical AI infrastructure company delivering 3D LiDAR sensing and perception software across physical security, smart spaces, transportation, and industrial automation. He has built fast-growing businesses, achieved multiple successful exits and spearheaded the strategy to build the layer for the next wave of AI. Follow him on LinkedIn or reach him at <span \n                data-original-string='V6PPWHdBM5V8hkycHyie5g==d9buK4yOW\/v8uwtqaB1Vem2ugphjdvZSSQeTtrG5QzMNAM='\n                class='apbct-email-encoder'\n                title='This contact has been encoded by Anti-Spam by CleanTalk. Click to decode. To finish the decoding make sure that JavaScript is enabled in your browser.'>en<span class=\"apbct-blur\">**********<\/span>@<span class=\"apbct-blur\">******<\/span>gy.com<\/span>.<\/span><\/p>\n<\/blockquote>\n<\/div><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-11 fusion_builder_column_1_3 1_3 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:33.333333333333%;--awb-margin-top-large:0px;--awb-spacing-right-large:5.76%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:5.76%;--awb-width-medium:33.333333333333%;--awb-order-medium:0;--awb-spacing-right-medium:5.76%;--awb-spacing-left-medium:5.76%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-image-element\" style=\"--awb-caption-title-font-family:var(--h2_typography-font-family);--awb-caption-title-font-weight:var(--h2_typography-font-weight);--awb-caption-title-font-style:var(--h2_typography-font-style);--awb-caption-title-size:var(--h2_typography-font-size);--awb-caption-title-transform:var(--h2_typography-text-transform);--awb-caption-title-line-height:var(--h2_typography-line-height);--awb-caption-title-letter-spacing:var(--h2_typography-letter-spacing);\"><span class=\"fusion-imageframe imageframe-none imageframe-3 hover-type-none\"><img decoding=\"async\" width=\"300\" height=\"300\" alt=\"Enzo Signore, CEO, Board Member &amp; Co-Founder\" title=\"profile_Enzo-BIO_white-bkgrd-300&#215;300-1\" src=\"https:\/\/quanergy.com\/wp-content\/uploads\/profile_Enzo-BIO_white-bkgrd-300x300-1.jpg\" class=\"img-responsive wp-image-1314\" srcset=\"https:\/\/quanergy.com\/wp-content\/uploads\/profile_Enzo-BIO_white-bkgrd-300x300-1-200x200.jpg 200w, https:\/\/quanergy.com\/wp-content\/uploads\/profile_Enzo-BIO_white-bkgrd-300x300-1.jpg 300w\" sizes=\"(max-width: 640px) 100vw, 300px\" \/><\/span><\/div><\/div><\/div><\/div><\/div><\/p>","protected":false},"excerpt":{"rendered":"","protected":false},"author":7,"featured_media":3244,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","_has_post_settings":{"highlight_sharing":"default","image_sharing":"default","headline_sharing":"default"},"footnotes":""},"categories":[11],"tags":[],"hashtags":[],"class_list":["post-3266","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog-posts"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.8 (Yoast SEO v26.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>3D LiDAR: The Sensing Layer Powering Physical AI | Quanergy<\/title>\n<meta name=\"description\" content=\"3D LiDAR is the sensing layer behind Physical AI. Learn how it enables accurate detection, real-time tracking, and spatial intelligence beyond traditional cameras.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/quanergy.com\/es\/3d-lidar-physical-ai\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"3D LiDAR: The Sensing Layer Powering Physical AI\" \/>\n<meta property=\"og:description\" content=\"Physical AI starts with real-world perception. 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