diff --git a/src/app/page.tsx b/src/app/page.tsx index 844699c..d02274e 100644 --- a/src/app/page.tsx +++ b/src/app/page.tsx @@ -29,14 +29,10 @@ export default function LandingPage() { @@ -90,15 +60,9 @@ export default function LandingPage() { textboxLayout="default" useInvertedBackground={false} metrics={[ - { - id: "1", icon: Zap, - title: "Latency", value: "< 500ms"}, - { - id: "2", icon: Star, - title: "PSRAM Usage", value: "4MB"}, - { - id: "3", icon: ShieldCheck, - title: "Accuracy", value: "94.2%"}, + { id: "1", icon: Zap, title: "Latency", value: "< 500ms" }, + { id: "2", icon: Star, title: "PSRAM Usage", value: "4MB" }, + { id: "3", icon: ShieldCheck, title: "Accuracy", value: "94.2%" }, ]} title="Live Inference Telemetry" description="Real-time statistics from the active ESP32-CAM inference pipeline." @@ -111,18 +75,10 @@ export default function LandingPage() { textboxLayout="default" useInvertedBackground={true} features={[ - { - icon: Camera, - title: "Capture", description: "High-fidelity OV2640 sensor stream initialization."}, - { - icon: Database, - title: "Pre-process", description: "Dynamic Grayscale mapping and frame resizing."}, - { - icon: Star, - title: "Inference", description: "FOMO model execution via C++ native loop."}, - { - icon: Globe, - title: "Result", description: "Transmission to local web-dashboard via MJPEG."}, + { icon: Camera, title: "Capture", description: "High-fidelity OV2640 sensor stream initialization." }, + { icon: Database, title: "Pre-process", description: "Dynamic Grayscale mapping and frame resizing." }, + { icon: Star, title: "Inference", description: "FOMO model execution via C++ native loop." }, + { icon: Globe, title: "Result", description: "Transmission to local web-dashboard via MJPEG." }, ]} title="The Inference Pipeline" description="Optimized workflow for edge intelligence." @@ -136,24 +92,8 @@ export default function LandingPage() { gridVariant="uniform-all-items-equal" useInvertedBackground={false} products={[ - { - id: "1", brand: "Sorting", name: "Industrial Sorting", price: "High Precision", rating: 5, - reviewCount: "1.2k", imageSrc: "http://img.b2bpic.net/free-photo/geometric-bokeh_1017-3221.jpg?_wi=2"}, - { - id: "2", brand: "Security", name: "Smart Monitoring", price: "Zero Cloud", rating: 5, - reviewCount: "800", imageSrc: "http://img.b2bpic.net/free-photo/close-up-shot-notebook-displaying-ai-machine-learning-algorithms_482257-122159.jpg?_wi=2"}, - { - id: "3", brand: "Nature", name: "Wildlife Tracking", price: "Low Energy", rating: 4, - reviewCount: "600", imageSrc: "http://img.b2bpic.net/free-photo/data-center-software-developer-using-computer-monitor-neural-network-ai-llm_482257-130078.jpg?_wi=2"}, - { - id: "4", brand: "Agro", name: "Crop Scouting", price: "Real-time", rating: 5, - reviewCount: "450", imageSrc: "http://img.b2bpic.net/free-photo/connecting-dots-background-network-communication-design_53876-160215.jpg?_wi=2"}, - { - id: "5", brand: "Retail", name: "Traffic Counting", price: "Localized", rating: 4, - reviewCount: "300", imageSrc: "http://img.b2bpic.net/free-photo/focus-laptop-data-center-with-ai-brain-used-by-engineers-background_482257-115526.jpg"}, - { - id: "6", brand: "Home", name: "Smart Doorbell", price: "Embedded", rating: 5, - reviewCount: "2.1k", imageSrc: "http://img.b2bpic.net/free-photo/blurred-night-lights_23-2148139360.jpg"}, + { id: "1", brand: "Security", name: "Smart Monitoring", price: "Zero Cloud", rating: 5, reviewCount: "800", imageSrc: "http://img.b2bpic.net/free-photo/close-up-shot-notebook-displaying-ai-machine-learning-algorithms_482257-122159.jpg?_wi=2" }, + { id: "2", brand: "Agro", name: "Crop Scouting", price: "Real-time", rating: 5, reviewCount: "450", imageSrc: "http://img.b2bpic.net/free-photo/connecting-dots-background-network-communication-design_53876-160215.jpg?_wi=2" }, ]} title="Industrial Applications" description="Versatile deployment scenarios for the ESP32-CAM module." @@ -165,12 +105,9 @@ export default function LandingPage() { textboxLayout="default" useInvertedBackground={true} faqs={[ - { - id: "1", title: "What model is used?", content: "We utilize a custom FOMO (Faster Objects, More Objects) model optimized for ESP32."}, - { - id: "2", title: "Is cloud connectivity required?", content: "No, inference runs 100% on the device for true Edge AI."}, - { - id: "3", title: "How is power managed?", content: "The system utilizes optimized sleep modes and hardware-level power gating."}, + { id: "1", title: "What model is used?", content: "We utilize a custom FOMO (Faster Objects, More Objects) model optimized for ESP32." }, + { id: "2", title: "Is cloud connectivity required?", content: "No, inference runs 100% on the device for true Edge AI." }, + { id: "3", title: "How is power managed?", content: "The system utilizes optimized sleep modes and hardware-level power gating." }, ]} title="Technical Questions" description="Get answers about the ESP32-CAM inference engine." @@ -181,22 +118,8 @@ export default function LandingPage() {