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60px}.cctv-ai265-v1 h1{font-size:clamp(42px,15vw,64px)}.cctv-ai265-v1 .lead{font-size:18px}.cctv-ai265-v1 .section{padding:72px 0}.cctv-ai265-v1 .concepts,.cctv-ai265-v1 .flow,.cctv-ai265-v1 .comparison,.cctv-ai265-v1 .result-grid,.cctv-ai265-v1 .knowledge{grid-template-columns:1fr}.cctv-ai265-v1 .flow-item:last-child{grid-column:auto}.cctv-ai265-v1 .cta-card{padding:34px 24px}}\n@media(prefers-reduced-motion:reduce){.cctv-ai265-v1 *{animation:none!important;transition:none!important;scroll-behavior:auto!important}}\n<\/style>\n<div class=\"cctv-ai265-v1\" id=\"cctv-ai265-page\">\n  <div class=\"topbar\"><div class=\"wrap topbar-inner\"><div class=\"version\">CCTV Academy \u00b7 AI Smart H.265+ \u00b7 v1.0 CONTRAST STAGING<\/div><div class=\"langs\" aria-label=\"Language\"><button class=\"lang\" type=\"button\" data-lang=\"nl\">NL<\/button><button class=\"lang\" type=\"button\" data-lang=\"fr\">FR<\/button><button class=\"lang\" type=\"button\" data-lang=\"en\">EN<\/button><button class=\"lang\" type=\"button\" data-lang=\"de\">DE<\/button><\/div><\/div><\/div>\n\n  <section class=\"hero\">\n    <div class=\"wrap hero-grid\">\n      <div>\n        <div class=\"eyebrow\" data-i18n=\"heroEyebrow\">CCTV Academy \u00b7 AI video compression<\/div>\n        <h1 data-i18n-html=\"heroTitle\">Niet elk deel van het beeld<br><em>verdient evenveel bits.<\/em><\/h1>\n        <p class=\"lead\" data-i18n=\"heroLead\">Dahua koppelt in de Academy-uitleg slimme compressie aan beweging, relevante objecten en sc\u00e8ne-informatie. Het doel: meer videodata bewaren waar die ertoe doet en minder verspillen aan statische of minder belangrijke beeldzones.<\/p>\n        <div class=\"hero-actions\"><a class=\"btn btn-primary\" href=\"#functies\" data-i18n=\"heroCta1\">Bekijk de AI-functies \u2192<\/a><a class=\"btn btn-secondary localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/dahua-codering-smart-h-264-h-265\/\" data-i18n=\"heroCta2\">Eerst Smart H.265+ begrijpen<\/a><\/div>\n        <div class=\"checks\"><span data-i18n=\"check1\">Motion-aware coding<\/span><span>AI-ROI<\/span><span data-i18n=\"check3\">Scene-adaptive coding<\/span><span data-i18n=\"check4\">Event-driven streaming<\/span><\/div>\n      <\/div>\n      <div class=\"ai-stage\" aria-label=\"AI ROI compression visual\">\n        <div class=\"screen\"><div class=\"screen-inner\"><div class=\"screen-grid\"><\/div><div class=\"scene-ground\"><\/div><div class=\"scene-line a\"><\/div><div class=\"scene-line b\"><\/div><div class=\"person\"><\/div><div class=\"roi\"><\/div><div class=\"hud\"><span>SMART H.265+ \/\/ ACTIVE<\/span><span>AI OBJECT \/\/ PRIORITY<\/span><\/div><div class=\"stream-bars\"><span><\/span><span><\/span><span><\/span><span><\/span><span><\/span><span><\/span><span><\/span><span><\/span><span><\/span><span><\/span><span><\/span><span><\/span><\/div><\/div><\/div>\n      <\/div>\n    <\/div>\n  <\/section>\n\n  <div class=\"jump-wrap\"><div class=\"wrap\"><nav class=\"jump\" aria-label=\"Page navigation\"><a href=\"#basis\" data-i18n=\"nav1\">Waarom AI-compressie?<\/a><a href=\"#functies\" data-i18n=\"nav2\">4 functies<\/a><a href=\"#werking\" data-i18n=\"nav3\">Werking<\/a><a href=\"#voorbeeld\" data-i18n=\"nav4\">Parkeerplaats<\/a><a href=\"#resultaat\" data-i18n=\"nav5\">Resultaat<\/a><a href=\"#media\" data-i18n=\"nav6\">Bestaand beeld<\/a><a href=\"#verder\" data-i18n=\"nav7\">Verder leren<\/a><\/nav><\/div><\/div>\n\n  <section class=\"section section-light\" id=\"basis\"><div class=\"wrap\"><div class=\"section-kicker\" data-i18n=\"s1Kicker\">Wat doet AI hier?<\/div><h2 data-i18n=\"s1Title\">Compressie wordt slimmer wanneer de camera eerst begrijpt wat belangrijk is.<\/h2><div class=\"split\"><div class=\"copy\"><p data-i18n=\"s1p1\">De huidige CCTV Academy-bron beschrijft AI-optimalisaties in Dahua Smart H.265+ als een manier om opslag en bandbreedte effici\u00ebnter te gebruiken zonder belangrijke details in beveiligingsbeelden zomaar weg te drukken.<\/p><p data-i18n=\"s1p2\">In plaats van ieder deel van het beeld gelijk te behandelen, wordt gekeken naar beweging, objecten en kritieke zones zoals personen, voertuigen, tripwire- en intrusion-gebeurtenissen.<\/p><p data-i18n=\"s1p3\">De compressielogica kan daardoor relatief meer aandacht geven aan relevante delen van de sc\u00e8ne en statische of minder belangrijke gebieden sterker comprimeren.<\/p><\/div><div class=\"comparison\"><article class=\"compare-box\"><small data-i18n=\"classicK\">Zonder AI-context<\/small><h3 data-i18n=\"classicH\">Alles ongeveer hetzelfde behandelen.<\/h3><p data-i18n=\"classicP\">Een vaste of algemene compressielogica maakt minder onderscheid tussen een lege achtergrond en een relevant beveiligingsobject.<\/p><\/article><article class=\"compare-box ai\"><small data-i18n=\"aiK\">Met AI-context<\/small><h3 data-i18n=\"aiH\">Meer aandacht waar het telt.<\/h3><p data-i18n=\"aiP\">De Academy-uitleg koppelt objectherkenning, ROI, sc\u00e8ne en events aan een slimmere verdeling van videodata.<\/p><\/article><\/div><\/div><\/div><\/section>\n\n  <section class=\"section section-dark\" id=\"functies\"><div class=\"wrap\"><div class=\"section-kicker\" data-i18n=\"s2Kicker\">Vier AI-gestuurde compressiefuncties<\/div><h2 data-i18n=\"s2Title\">Vier manieren waarop de Academy-pagina de optimalisatie uitlegt.<\/h2><p class=\"section-intro\" data-i18n=\"s2Intro\">De onderstaande blokken volgen de vier functies zoals ze op de huidige publieke CCTV Academy-pagina worden beschreven.<\/p><div class=\"concepts\">\n    <article class=\"concept\"><div class=\"concept-no\">01 \/\/ MOTION<\/div><h3 data-i18n=\"c1h\">Motion-aware codering<\/h3><p data-i18n=\"c1p\">Bij beweging kan meer bitrate worden ingezet. In statische sc\u00e8nes kan de bitrate lager blijven. De Academy-bron koppelt daarbij relevantie aan AI-detectie.<\/p><span class=\"chip\" data-i18n=\"c1chip\">Beweging \u2192 meer bits<\/span><\/article>\n    <article class=\"concept\"><div class=\"concept-no\">02 \/\/ ROI<\/div><h3>AI-ROI<\/h3><p data-i18n=\"c2p\">Relevante objecten zoals mensen of voertuigen kunnen als belangrijk gebied worden behandeld, terwijl lucht, muren of gras sterker worden gecomprimeerd.<\/p><span class=\"chip\" data-i18n=\"c2chip\">Object \u2192 prioriteit<\/span><\/article>\n    <article class=\"concept\"><div class=\"concept-no\">03 \/\/ SCENE<\/div><h3 data-i18n=\"c3h\">Scene-adaptive codering<\/h3><p data-i18n=\"c3p\">De Academy-uitleg beschrijft aanpassing op basis van sc\u00e8netype, dag\/nacht en drukte. Bij veel ruis wordt gezocht naar betekenisvolle veranderingen.<\/p><span class=\"chip\" data-i18n=\"c3chip\">Sc\u00e8ne \u2192 profiel<\/span><\/article>\n    <article class=\"concept\"><div class=\"concept-no\">04 \/\/ EVENT<\/div><h3 data-i18n=\"c4h\">Event-driven streaming<\/h3><p data-i18n=\"c4p\">Bij relevante AI-events zoals SMD of perimeter-alarm beschrijft de bron een tijdelijke kwaliteitsverhoging, terwijl buiten events sterker wordt gecomprimeerd.<\/p><span class=\"chip\" data-i18n=\"c4chip\">Event \u2192 hogere kwaliteit<\/span><\/article>\n  <\/div><\/div><\/section>\n\n  <section class=\"section section-dark\" id=\"werking\" style=\"padding-top:10px\"><div class=\"wrap\"><div class=\"section-kicker\" data-i18n=\"s3Kicker\">Van sc\u00e8ne naar stream<\/div><h2 data-i18n=\"s3Title\">De camera analyseert eerst. Daarna wordt de videodata verdeeld.<\/h2><div class=\"flow\"><div class=\"flow-item\"><strong>01 \u00b7 INPUT<\/strong><b data-i18n=\"f1h\">Sc\u00e8ne<\/b><span data-i18n=\"f1p\">De camera ziet achtergrond, beweging en objecten.<\/span><\/div><div class=\"flow-item\"><strong>02 \u00b7 AI<\/strong><b data-i18n=\"f2h\">Detectie<\/b><span data-i18n=\"f2p\">Relevante personen, voertuigen of events worden herkend.<\/span><\/div><div class=\"flow-item\"><strong>03 \u00b7 ROI<\/strong><b data-i18n=\"f3h\">Prioriteit<\/b><span data-i18n=\"f3p\">Belangrijke zones krijgen volgens de Academy-uitleg relatief meer aandacht.<\/span><\/div><div class=\"flow-item\"><strong>04 \u00b7 CODEC<\/strong><b>Smart H.265+<\/b><span data-i18n=\"f4p\">De stream wordt aangepast aan sc\u00e8ne, beweging en belang.<\/span><\/div><div class=\"flow-item\"><strong>05 \u00b7 OUTPUT<\/strong><b data-i18n=\"f5h\">Opslag & netwerk<\/b><span data-i18n=\"f5p\">De gecomprimeerde videodata gaat naar recorder, opslag of remote view.<\/span><\/div><\/div><\/div><\/section>\n\n  <section class=\"section section-light\" id=\"voorbeeld\"><div class=\"wrap\"><div class=\"section-kicker\" data-i18n=\"s4Kicker\">Praktisch voorbeeld uit de Academy-bron<\/div><h2 data-i18n=\"s4Title\">Een lege parkeerplaats verandert zodra een persoon in beeld komt.<\/h2><div class=\"split\"><div class=\"example-stage\" aria-hidden=\"true\"><div class=\"parking\"><\/div><div class=\"car\"><\/div><div class=\"subject\"><\/div><div class=\"subject-roi\"><\/div><div class=\"bg-label\" data-i18n=\"bgLabel\">STATISCHE ACHTERGROND \/\/ LAGERE PRIORITEIT<\/div><div class=\"bit-label\" data-i18n=\"bitLabel\">PERSOON \/\/ HOGERE PRIORITEIT<\/div><\/div><div class=\"copy\"><p data-i18n=\"s4p1\">De bestaande pagina gebruikt een lege parkeerplaats als voorbeeld. Zonder AI wordt de hele sc\u00e8ne volgens \u00e9\u00e9n algemene bitratebenadering opgeslagen.<\/p><p data-i18n=\"s4p2\">Met AI + Smart H.265+ beschrijft de bron dat de parkeerplaats zelf weinig bits kan krijgen. Zodra een persoon verschijnt, herkent de camera het relevante object.<\/p><p data-i18n=\"s4p3\">Die persoon wordt als belangrijke ROI behandeld, zodat kleur en detail van dat object beter kunnen worden behouden terwijl de rest sterker gecomprimeerd blijft.<\/p><\/div><\/div><\/div><\/section>\n\n  <section class=\"section section-light\" id=\"resultaat\" style=\"padding-top:10px\"><div class=\"wrap\"><div class=\"section-kicker\" data-i18n=\"s5Kicker\">Wat levert dat volgens de huidige Academy-pagina op?<\/div><h2 data-i18n=\"s5Title\">Minder data waar het kan. Meer detail waar het telt.<\/h2><div class=\"result-grid\"><article class=\"result\"><div class=\"big\">70\u201380%<\/div><h3 data-i18n=\"r1h\">Genoemde besparing<\/h3><p data-i18n=\"r1p\">De huidige Academy-bron noemt 70\u201380% besparing zonder verlies van bewijswaarde. Dit cijfer wordt hier als bronclaim weergegeven, niet als universele garantie.<\/p><\/article><article class=\"result\"><div class=\"big\">HDD<\/div><h3 data-i18n=\"r2h\">Minder opslagdruk<\/h3><p data-i18n=\"r2p\">Effici\u00ebntere compressie kan de benodigde opslagcapaciteit verlagen.<\/p><\/article><article class=\"result\"><div class=\"big\">NET<\/div><h3 data-i18n=\"r3h\">Lagere netwerkbelasting<\/h3><p data-i18n=\"r3p\">Minder videodata kan helpen bij netwerkverkeer en remote viewing.<\/p><\/article><article class=\"result\"><div class=\"big\">ROI<\/div><h3 data-i18n=\"r4h\">Detail op relevante zones<\/h3><p data-i18n=\"r4p\">De Academy-bron legt nadruk op personen, voertuigen, gezichten en nummerplaten als relevante detailzones.<\/p><\/article><\/div><div class=\"source-note\"><strong data-i18n=\"noteH\">Belangrijk bij technische claims<\/strong><p data-i18n=\"noteP\">Werkelijke opslagbesparing en beeldkwaliteit hangen af van sc\u00e8ne, firmware, instellingen, resolutie, framerate, bitrate, beweging, ruis en recorder\/camera-combinatie. De 70\u201380% hierboven is de claim op de huidige CCTV Academy-bronpagina.<\/p><\/div><\/div><\/section>\n\n  <section class=\"section section-dark\" id=\"media\"><div class=\"wrap\"><div class=\"section-kicker\" data-i18n=\"s6Kicker\">Bestaande Academy-media behouden<\/div><h2 data-i18n=\"s6Title\">De originele illustratie hoort bij deze les en mag niet verdwijnen.<\/h2><div class=\"media-preserve\"><div class=\"media-slot\"><div><div class=\"icon\">\u25a3<\/div><h3 data-i18n=\"mediaH\">Bestaande AI-optimalisatie-afbeelding<\/h3><p data-i18n=\"mediaP\">De publieke bron bevestigt een bestaande CCTV Academy-afbeelding met het onderwerp \u201cwat zijn AI optimalisaties\u201d. Neem bij de WordPress-merge de actuele media-URL en alt-tekst exact over.<\/p><\/div><\/div><div class=\"media-explain\"><h3 data-i18n=\"mediaWhyH\">Waarom staat hier bewust geen verzonnen afbeeldings-URL?<\/h3><p data-i18n=\"mediaWhyP\">De publieke index toont het beeld en de alt-omschrijving, maar levert niet betrouwbaar de actuele WordPress-mediabron. Daarom wordt in deze STAGING-versie niets vervangen of gehotlin kt.<\/p><code>&lt;!-- WORDPRESS MERGE: behoud hier het actuele originele img\/media-blok van de huidige pagina --&gt;<\/code><\/div><\/div><\/div><\/section>\n\n  <section class=\"section section-light\" id=\"verder\"><div class=\"wrap\"><div class=\"section-kicker\" data-i18n=\"s7Kicker\">Bouw verder op deze kennis<\/div><h2 data-i18n=\"s7Title\">AI-compressie is \u00e9\u00e9n schakel in de volledige CCTV-videoketen.<\/h2><p class=\"section-intro\" data-i18n=\"s7Intro\">Gebruik de volgende Academy-onderwerpen om codec, camera, AI en recorder in samenhang te begrijpen.<\/p><div class=\"knowledge\">\n    <a class=\"localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/dahua-codering-smart-h-264-h-265\/\"><div class=\"card-tag\">Codec<\/div><h3>Smart H.265+<\/h3><p data-i18n=\"k1p\">Begrijp eerst de basis van H.265 en Dahua Smart H.265+.<\/p><div class=\"card-link\" data-i18n=\"k1c\">Bekijk codec \u2192<\/div><\/a>\n    <a class=\"localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/dahuas-smart-h-265-versus-hikvisions-h-265\/\"><div class=\"card-tag\">Vergelijking<\/div><h3>Dahua vs Hikvision<\/h3><p data-i18n=\"k2p\">Vergelijk de fabrikant-eigen H.265+-optimalisaties.<\/p><div class=\"card-link\" data-i18n=\"k2c\">Vergelijk codecs \u2192<\/div><\/a>\n    <a class=\"localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/8-megapixel-ip-turret-camera-met-smart-dual-light-verlichting\/\"><div class=\"card-tag\">Camera<\/div><h3 data-i18n=\"k3h\">8MP AI-camera<\/h3><p data-i18n=\"k3p\">Bekijk codec, sensor, lens, verlichting en AI als \u00e9\u00e9n toestel.<\/p><div class=\"card-link\" data-i18n=\"k3c\">Bekijk camera \u2192<\/div><\/a>\n    <a class=\"localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/ai-chip-in-de-8-megapixel-ip-camera-van-dahua\/\"><div class=\"card-tag\">AI<\/div><h3 data-i18n=\"k4h\">AI-chip in de camera<\/h3><p data-i18n=\"k4p\">Begrijp waar intelligente analyse in de camera plaatsvindt.<\/p><div class=\"card-link\" data-i18n=\"k4c\">Bekijk AI-chip \u2192<\/div><\/a>\n    <a class=\"localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/beeldsensor-8mp-dahua-ip-camera\/\"><div class=\"card-tag\">Sensor<\/div><h3 data-i18n=\"k5h\">8MP beeldsensor<\/h3><p data-i18n=\"k5p\">Compressie begint pas nadat lens en sensor een beeld hebben opgebouwd.<\/p><div class=\"card-link\" data-i18n=\"k5c\">Bekijk sensor \u2192<\/div><\/a>\n    <a class=\"localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/2-8mm-fixed-focal-netwerk-camera\/\"><div class=\"card-tag\">Optiek<\/div><h3>2.8mm Fixed Focal<\/h3><p data-i18n=\"k6p\">De lens bepaalt welke sc\u00e8ne uiteindelijk moet worden gecodeerd.<\/p><div class=\"card-link\" data-i18n=\"k6c\">Bekijk lens \u2192<\/div><\/a>\n    <a class=\"localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/opleiding-camerabewaking-fort-knox-het-ai-opnamesysteem\/\"><div class=\"card-tag\">NVR<\/div><h3 data-i18n=\"k7h\">AI-opnamesysteem<\/h3><p data-i18n=\"k7p\">Leer wat de recorder met inkomende videostreams moet verwerken.<\/p><div class=\"card-link\" data-i18n=\"k7c\">Bekijk NVR-training \u2192<\/div><\/a>\n    <a class=\"localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/installateur-camerabewaking-opleidingen-in-kortrijk\/\"><div class=\"card-tag\">Hands-on<\/div><h3>CCTV Micro-Learning<\/h3><p data-i18n=\"k8p\">Vergelijk bitrate, beweging, ROI en opnamekwaliteit zelf in de praktijk.<\/p><div class=\"card-link\" data-i18n=\"k8c\">Ontdek Micro-Learning \u2192<\/div><\/a>\n  <\/div><\/div><\/section>\n\n  <div class=\"ticker\" aria-hidden=\"true\"><div class=\"ticker-track\"><span>SMART H.265+<\/span><span>AI ROI<\/span><span>MOTION AWARE CODING<\/span><span>SCENE ADAPTIVE<\/span><span>EVENT DRIVEN STREAMING<\/span><span>BITRATE<\/span><span>SMART H.265+<\/span><span>AI ROI<\/span><span>MOTION AWARE CODING<\/span><span>SCENE ADAPTIVE<\/span><span>EVENT DRIVEN STREAMING<\/span><span>BITRATE<\/span><\/div><\/div>\n\n  <section class=\"cta\"><div class=\"wrap\"><div class=\"cta-card\"><div class=\"section-kicker\" style=\"color:var(--accent2)\" data-i18n=\"ctaKicker\">CCTV Micro-Learning<\/div><h2 data-i18n=\"ctaTitle\">Slimme compressie begrijp je pas wanneer je bitrate, beweging en opslag samen ziet veranderen.<\/h2><p data-i18n=\"ctaText\">Test Smart H.265+, beweging, nachtbeeld en AI-events op echte camera's en recorders. Vergelijk wat er met beeldkwaliteit, bitrate en opslag gebeurt wanneer de sc\u00e8ne verandert.<\/p><div class=\"cta-actions\"><a class=\"btn btn-primary localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/installateur-camerabewaking-opleidingen-in-kortrijk\/\" data-i18n=\"cta1\">Ontdek CCTV Micro-Learning \u2192<\/a><a class=\"btn btn-secondary localized-link\" href=\"https:\/\/cctvacademy.be\/nl\/opleiding-installatie-en-onderhoud-camerabewakingssystemen\/\" data-i18n=\"cta2\">Bekijk de CCTV-opleidingen<\/a><\/div><\/div><\/div><\/section>\n<\/div>\n<script>\n(function(){\n var root=document.getElementById('cctv-ai265-page');if(!root)return;\n var copy={\n  nl:{heroEyebrow:'CCTV Academy \u00b7 AI video compression',heroTitle:'Niet elk deel van het beeld<br><em>verdient evenveel bits.<\/em>',heroLead:'Dahua koppelt in de Academy-uitleg slimme compressie aan beweging, relevante objecten en sc\u00e8ne-informatie. Het doel: meer videodata bewaren waar die ertoe doet en minder verspillen aan statische of minder belangrijke beeldzones.',heroCta1:'Bekijk de AI-functies \u2192',heroCta2:'Eerst Smart H.265+ begrijpen',check1:'Motion-aware coding',check3:'Scene-adaptive coding',check4:'Event-driven streaming',nav1:'Waarom AI-compressie?',nav2:'4 functies',nav3:'Werking',nav4:'Parkeerplaats',nav5:'Resultaat',nav6:'Bestaand beeld',nav7:'Verder leren',s1Kicker:'Wat doet AI hier?',s1Title:'Compressie wordt slimmer wanneer de camera eerst begrijpt wat belangrijk is.',s1p1:'De huidige CCTV Academy-bron beschrijft AI-optimalisaties in Dahua Smart H.265+ als een manier om opslag en bandbreedte effici\u00ebnter te gebruiken zonder belangrijke details in beveiligingsbeelden zomaar weg te drukken.',s1p2:'In plaats van ieder deel van het beeld gelijk te behandelen, wordt gekeken naar beweging, objecten en kritieke zones zoals personen, voertuigen, tripwire- en intrusion-gebeurtenissen.',s1p3:'De compressielogica kan daardoor relatief meer aandacht geven aan relevante delen van de sc\u00e8ne en statische of minder belangrijke gebieden sterker comprimeren.',classicK:'Zonder AI-context',classicH:'Alles ongeveer hetzelfde behandelen.',classicP:'Een vaste of algemene compressielogica maakt minder onderscheid tussen een lege achtergrond en een relevant beveiligingsobject.',aiK:'Met AI-context',aiH:'Meer aandacht waar het telt.',aiP:'De Academy-uitleg koppelt objectherkenning, ROI, sc\u00e8ne en events aan een slimmere verdeling van videodata.',s2Kicker:'Vier AI-gestuurde compressiefuncties',s2Title:'Vier manieren waarop de Academy-pagina de optimalisatie uitlegt.',s2Intro:'De onderstaande blokken volgen de vier functies zoals ze op de huidige publieke CCTV Academy-pagina worden beschreven.',c1h:'Motion-aware codering',c1p:'Bij beweging kan meer bitrate worden ingezet. In statische sc\u00e8nes kan de bitrate lager blijven. De Academy-bron koppelt daarbij relevantie aan AI-detectie.',c1chip:'Beweging \u2192 meer bits',c2p:'Relevante objecten zoals mensen of voertuigen kunnen als belangrijk gebied worden behandeld, terwijl lucht, muren of gras sterker worden gecomprimeerd.',c2chip:'Object \u2192 prioriteit',c3h:'Scene-adaptive codering',c3p:'De Academy-uitleg beschrijft aanpassing op basis van sc\u00e8netype, dag\/nacht en drukte. Bij veel ruis wordt gezocht naar betekenisvolle veranderingen.',c3chip:'Sc\u00e8ne \u2192 profiel',c4h:'Event-driven streaming',c4p:'Bij relevante AI-events zoals SMD of perimeter-alarm beschrijft de bron een tijdelijke kwaliteitsverhoging, terwijl buiten events sterker wordt gecomprimeerd.',c4chip:'Event \u2192 hogere kwaliteit',s3Kicker:'Van sc\u00e8ne naar stream',s3Title:'De camera analyseert eerst. Daarna wordt de videodata verdeeld.',f1h:'Sc\u00e8ne',f1p:'De camera ziet achtergrond, beweging en objecten.',f2h:'Detectie',f2p:'Relevante personen, voertuigen of events worden herkend.',f3h:'Prioriteit',f3p:'Belangrijke zones krijgen volgens de Academy-uitleg relatief meer aandacht.',f4p:'De stream wordt aangepast aan sc\u00e8ne, beweging en belang.',f5h:'Opslag & netwerk',f5p:'De gecomprimeerde videodata gaat naar recorder, opslag of remote view.',s4Kicker:'Praktisch voorbeeld uit de Academy-bron',s4Title:'Een lege parkeerplaats verandert zodra een persoon in beeld komt.',bgLabel:'STATISCHE ACHTERGROND \/\/ LAGERE PRIORITEIT',bitLabel:'PERSOON \/\/ HOGERE PRIORITEIT',s4p1:'De bestaande pagina gebruikt een lege parkeerplaats als voorbeeld. Zonder AI wordt de hele sc\u00e8ne volgens \u00e9\u00e9n algemene bitratebenadering opgeslagen.',s4p2:'Met AI + Smart H.265+ beschrijft de bron dat de parkeerplaats zelf weinig bits kan krijgen. Zodra een persoon verschijnt, herkent de camera het relevante object.',s4p3:'Die persoon wordt als belangrijke ROI behandeld, zodat kleur en detail van dat object beter kunnen worden behouden terwijl de rest sterker gecomprimeerd blijft.',s5Kicker:'Wat levert dat volgens de huidige Academy-pagina op?',s5Title:'Minder data waar het kan. Meer detail waar het telt.',r1h:'Genoemde besparing',r1p:'De huidige Academy-bron noemt 70\u201380% besparing zonder verlies van bewijswaarde. Dit cijfer wordt hier als bronclaim weergegeven, niet als universele garantie.',r2h:'Minder opslagdruk',r2p:'Effici\u00ebntere compressie kan de benodigde opslagcapaciteit verlagen.',r3h:'Lagere netwerkbelasting',r3p:'Minder videodata kan helpen bij netwerkverkeer en remote viewing.',r4h:'Detail op relevante zones',r4p:'De Academy-bron legt nadruk op personen, voertuigen, gezichten en nummerplaten als relevante detailzones.',noteH:'Belangrijk bij technische claims',noteP:'Werkelijke opslagbesparing en beeldkwaliteit hangen af van sc\u00e8ne, firmware, instellingen, resolutie, framerate, bitrate, beweging, ruis en recorder\/camera-combinatie. De 70\u201380% hierboven is de claim op de huidige CCTV Academy-bronpagina.',s6Kicker:'Bestaande Academy-media behouden',s6Title:'De originele illustratie hoort bij deze les en mag niet verdwijnen.',mediaH:'Bestaande AI-optimalisatie-afbeelding',mediaP:'De publieke bron bevestigt een bestaande CCTV Academy-afbeelding met het onderwerp \u201cwat zijn AI optimalisaties\u201d. Neem bij de WordPress-merge de actuele media-URL en alt-tekst exact over.',mediaWhyH:'Waarom staat hier bewust geen verzonnen afbeeldings-URL?',mediaWhyP:'De publieke index toont het beeld en de alt-omschrijving, maar levert niet betrouwbaar de actuele WordPress-mediabron. Daarom wordt in deze STAGING-versie niets vervangen of gehotlin kt.',s7Kicker:'Bouw verder op deze kennis',s7Title:'AI-compressie is \u00e9\u00e9n schakel in de volledige CCTV-videoketen.',s7Intro:'Gebruik de volgende Academy-onderwerpen om codec, camera, AI en recorder in samenhang te begrijpen.',k1p:'Begrijp eerst de basis van H.265 en Dahua Smart H.265+.',k1c:'Bekijk codec \u2192',k2p:'Vergelijk de fabrikant-eigen H.265+-optimalisaties.',k2c:'Vergelijk codecs \u2192',k3h:'8MP AI-camera',k3p:'Bekijk codec, sensor, lens, verlichting en AI als \u00e9\u00e9n toestel.',k3c:'Bekijk camera \u2192',k4h:'AI-chip in de camera',k4p:'Begrijp waar intelligente analyse in de camera plaatsvindt.',k4c:'Bekijk AI-chip \u2192',k5h:'8MP beeldsensor',k5p:'Compressie begint pas nadat lens en sensor een beeld hebben opgebouwd.',k5c:'Bekijk sensor \u2192',k6p:'De lens bepaalt welke sc\u00e8ne uiteindelijk moet worden gecodeerd.',k6c:'Bekijk lens \u2192',k7h:'AI-opnamesysteem',k7p:'Leer wat de recorder met inkomende videostreams moet verwerken.',k7c:'Bekijk NVR-training \u2192',k8p:'Vergelijk bitrate, beweging, ROI en opnamekwaliteit zelf in de praktijk.',k8c:'Ontdek Micro-Learning \u2192',ctaKicker:'CCTV Micro-Learning',ctaTitle:'Slimme compressie begrijp je pas wanneer je bitrate, beweging en opslag samen ziet veranderen.',ctaText:'Test Smart H.265+, beweging, nachtbeeld en AI-events op echte camera\\'s en recorders. Vergelijk wat er met beeldkwaliteit, bitrate en opslag gebeurt wanneer de sc\u00e8ne verandert.',cta1:'Ontdek CCTV Micro-Learning \u2192',cta2:'Bekijk de CCTV-opleidingen'},\n  fr:{heroEyebrow:'CCTV Academy \u00b7 Compression vid\u00e9o IA',heroTitle:'Toutes les zones de l\u2019image<br><em>ne m\u00e9ritent pas le m\u00eame nombre de bits.<\/em>',heroLead:'Dans l\u2019explication Academy, Dahua relie la compression intelligente au mouvement, aux objets pertinents et aux informations de sc\u00e8ne. L\u2019objectif : conserver davantage de donn\u00e9es l\u00e0 o\u00f9 elles comptent et moins en gaspiller sur les zones statiques ou moins importantes.',heroCta1:'Voir les fonctions IA \u2192',heroCta2:'Comprendre d\u2019abord Smart H.265+',check1:'Codage sensible au mouvement',check3:'Codage adaptatif \u00e0 la sc\u00e8ne',check4:'Streaming pilot\u00e9 par \u00e9v\u00e9nement',nav1:'Pourquoi l\u2019IA ?',nav2:'4 fonctions',nav3:'Fonctionnement',nav4:'Parking',nav5:'R\u00e9sultat',nav6:'Image existante',nav7:'Continuer',s1Kicker:'Que fait l\u2019IA ici ?',s1Title:'La compression devient plus intelligente lorsque la cam\u00e9ra comprend d\u2019abord ce qui est important.',s1p1:'La source CCTV Academy actuelle d\u00e9crit les optimisations IA de Dahua Smart H.265+ comme un moyen d\u2019utiliser plus efficacement le stockage et la bande passante sans \u00e9liminer simplement les d\u00e9tails importants des images de s\u00e9curit\u00e9.',s1p2:'Au lieu de traiter chaque zone de l\u2019image de la m\u00eame fa\u00e7on, le syst\u00e8me tient compte du mouvement, des objets et de zones critiques telles que personnes, v\u00e9hicules, tripwire et intrusion.',s1p3:'La logique de compression peut ainsi accorder relativement plus d\u2019attention aux parties pertinentes de la sc\u00e8ne et compresser davantage les zones statiques ou moins importantes.',classicK:'Sans contexte IA',classicH:'Traiter presque tout de la m\u00eame mani\u00e8re.',classicP:'Une logique g\u00e9n\u00e9rale ou fixe distingue moins un arri\u00e8re-plan vide d\u2019un objet de s\u00e9curit\u00e9 pertinent.',aiK:'Avec contexte IA',aiH:'Plus d\u2019attention l\u00e0 o\u00f9 cela compte.',aiP:'L\u2019explication Academy associe reconnaissance d\u2019objets, ROI, sc\u00e8ne et \u00e9v\u00e9nements \u00e0 une r\u00e9partition plus intelligente des donn\u00e9es vid\u00e9o.',s2Kicker:'Quatre fonctions de compression pilot\u00e9es par IA',s2Title:'Quatre fa\u00e7ons dont la page Academy explique l\u2019optimisation.',s2Intro:'Les blocs ci-dessous suivent les quatre fonctions d\u00e9crites sur la page publique CCTV Academy actuelle.',c1h:'Codage sensible au mouvement',c1p:'Lorsqu\u2019il y a du mouvement, davantage de d\u00e9bit peut \u00eatre utilis\u00e9. Dans les sc\u00e8nes statiques, le d\u00e9bit peut rester plus faible. La source Academy relie aussi la pertinence \u00e0 la d\u00e9tection IA.',c1chip:'Mouvement \u2192 plus de bits',c2p:'Les objets pertinents comme les personnes ou v\u00e9hicules peuvent recevoir une priorit\u00e9 plus \u00e9lev\u00e9e, tandis que ciel, murs ou herbe sont davantage compress\u00e9s.',c2chip:'Objet \u2192 priorit\u00e9',c3h:'Codage adaptatif \u00e0 la sc\u00e8ne',c3p:'L\u2019explication Academy d\u00e9crit une adaptation selon le type de sc\u00e8ne, jour\/nuit et niveau d\u2019activit\u00e9. En pr\u00e9sence de bruit, le syst\u00e8me cherche des changements significatifs.',c3chip:'Sc\u00e8ne \u2192 profil',c4h:'Streaming pilot\u00e9 par \u00e9v\u00e9nement',c4p:'Pour des \u00e9v\u00e9nements IA pertinents comme SMD ou alarme p\u00e9rim\u00e9trique, la source d\u00e9crit une hausse temporaire de qualit\u00e9, avec une compression plus forte hors \u00e9v\u00e9nement.',c4chip:'\u00c9v\u00e9nement \u2192 qualit\u00e9 sup\u00e9rieure',s3Kicker:'De la sc\u00e8ne au flux',s3Title:'La cam\u00e9ra analyse d\u2019abord. Ensuite, les donn\u00e9es vid\u00e9o sont r\u00e9parties.',f1h:'Sc\u00e8ne',f1p:'La cam\u00e9ra voit l\u2019arri\u00e8re-plan, le mouvement et les objets.',f2h:'D\u00e9tection',f2p:'Les personnes, v\u00e9hicules ou \u00e9v\u00e9nements pertinents sont reconnus.',f3h:'Priorit\u00e9',f3p:'Les zones importantes re\u00e7oivent relativement plus d\u2019attention selon l\u2019explication Academy.',f4p:'Le flux est adapt\u00e9 \u00e0 la sc\u00e8ne, au mouvement et \u00e0 l\u2019importance.',f5h:'Stockage & r\u00e9seau',f5p:'Les donn\u00e9es compress\u00e9es vont vers l\u2019enregistreur, le stockage ou la visualisation distante.',s4Kicker:'Exemple pratique de la source Academy',s4Title:'Un parking vide change d\u00e8s qu\u2019une personne appara\u00eet.',bgLabel:'ARRI\u00c8RE-PLAN STATIQUE \/\/ PRIORIT\u00c9 FAIBLE',bitLabel:'PERSONNE \/\/ PRIORIT\u00c9 \u00c9LEV\u00c9E',s4p1:'La page actuelle utilise un parking vide comme exemple. Sans IA, toute la sc\u00e8ne est enregistr\u00e9e selon une approche g\u00e9n\u00e9rale de d\u00e9bit.',s4p2:'Avec IA + Smart H.265+, la source d\u00e9crit que le parking lui-m\u00eame peut recevoir peu de bits. D\u00e8s qu\u2019une personne appara\u00eet, la cam\u00e9ra reconna\u00eet l\u2019objet pertinent.',s4p3:'Cette personne est trait\u00e9e comme ROI importante afin de mieux conserver couleur et d\u00e9tail pendant que le reste reste davantage compress\u00e9.',s5Kicker:'Quel r\u00e9sultat selon la page Academy actuelle ?',s5Title:'Moins de donn\u00e9es l\u00e0 o\u00f9 c\u2019est possible. Plus de d\u00e9tail l\u00e0 o\u00f9 cela compte.',r1h:'\u00c9conomie annonc\u00e9e',r1p:'La source Academy actuelle mentionne 70\u201380 % d\u2019\u00e9conomie sans perte de valeur probante. Ce chiffre est pr\u00e9sent\u00e9 ici comme une affirmation de la source, pas comme une garantie universelle.',r2h:'Moins de pression sur le stockage',r2p:'Une compression plus efficace peut r\u00e9duire la capacit\u00e9 de stockage n\u00e9cessaire.',r3h:'Charge r\u00e9seau plus faible',r3p:'Moins de donn\u00e9es vid\u00e9o peut aider le trafic r\u00e9seau et la visualisation distante.',r4h:'D\u00e9tail sur les zones pertinentes',r4p:'La source Academy met l\u2019accent sur personnes, v\u00e9hicules, visages et plaques comme zones de d\u00e9tail pertinentes.',noteH:'Important pour les affirmations techniques',noteP:'Les \u00e9conomies r\u00e9elles et la qualit\u00e9 d\u2019image d\u00e9pendent de la sc\u00e8ne, du firmware, des r\u00e9glages, de la r\u00e9solution, de la fr\u00e9quence d\u2019image, du d\u00e9bit, du mouvement, du bruit et de la combinaison cam\u00e9ra\/enregistreur. Les 70\u201380 % ci-dessus proviennent de la page source CCTV Academy actuelle.',s6Kicker:'Conserver les m\u00e9dias Academy existants',s6Title:'L\u2019illustration originale fait partie de cette le\u00e7on et ne doit pas dispara\u00eetre.',mediaH:'Image d\u2019optimisation IA existante',mediaP:'La source publique confirme une image CCTV Academy existante sur le th\u00e8me \u201cwat zijn AI optimalisaties\u201d. Lors de la fusion WordPress, reprenez exactement l\u2019URL m\u00e9dia et le texte alternatif actuels.',mediaWhyH:'Pourquoi ne pas inventer une URL d\u2019image ?',mediaWhyP:'L\u2019index public montre l\u2019image et sa description alternative, mais pas de mani\u00e8re fiable la source m\u00e9dia WordPress actuelle. Cette version STAGING ne remplace donc rien.',s7Kicker:'Approfondir',s7Title:'La compression IA n\u2019est qu\u2019un maillon de la cha\u00eene vid\u00e9o CCTV.',s7Intro:'Utilisez les sujets Academy suivants pour comprendre ensemble codec, cam\u00e9ra, IA et enregistreur.',k1p:'Comprenez d\u2019abord les bases de H.265 et Dahua Smart H.265+.',k1c:'Voir le codec \u2192',k2p:'Comparez les optimisations H.265+ propres aux fabricants.',k2c:'Comparer les codecs \u2192',k3h:'Cam\u00e9ra IA 8 MP',k3p:'Voyez codec, capteur, objectif, \u00e9clairage et IA dans un seul appareil.',k3c:'Voir la cam\u00e9ra \u2192',k4h:'Puce IA dans la cam\u00e9ra',k4p:'Comprenez o\u00f9 l\u2019analyse intelligente se d\u00e9roule dans la cam\u00e9ra.',k4c:'Voir la puce IA \u2192',k5h:'Capteur 8 MP',k5p:'La compression commence seulement apr\u00e8s la cr\u00e9ation de l\u2019image par l\u2019objectif et le capteur.',k5c:'Voir le capteur \u2192',k6p:'L\u2019objectif d\u00e9termine quelle sc\u00e8ne devra ensuite \u00eatre encod\u00e9e.',k6c:'Voir l\u2019objectif \u2192',k7h:'Syst\u00e8me d\u2019enregistrement IA',k7p:'Apprenez ce que l\u2019enregistreur doit traiter \u00e0 partir des flux entrants.',k7c:'Voir la formation NVR \u2192',k8p:'Comparez vous-m\u00eame d\u00e9bit, mouvement, ROI et qualit\u00e9 d\u2019enregistrement.',k8c:'D\u00e9couvrir le Micro-Learning \u2192',ctaKicker:'CCTV Micro-Learning',ctaTitle:'On comprend la compression intelligente lorsque l\u2019on voit d\u00e9bit, mouvement et stockage \u00e9voluer ensemble.',ctaText:'Testez Smart H.265+, le mouvement, la vision nocturne et les \u00e9v\u00e9nements IA sur de vraies cam\u00e9ras et de vrais enregistreurs. Comparez ce qui arrive \u00e0 la qualit\u00e9, au d\u00e9bit et au stockage quand la sc\u00e8ne change.',cta1:'D\u00e9couvrir CCTV Micro-Learning \u2192',cta2:'Voir les formations CCTV'},\n  en:{heroEyebrow:'CCTV Academy \u00b7 AI video compression',heroTitle:'Not every part of the image<br><em>deserves the same number of bits.<\/em>',heroLead:'In the Academy explanation, Dahua links smart compression to motion, relevant objects and scene information. The goal: preserve more video data where it matters and waste less on static or less important image areas.',heroCta1:'View the AI functions \u2192',heroCta2:'Understand Smart H.265+ first',check1:'Motion-aware coding',check3:'Scene-adaptive coding',check4:'Event-driven streaming',nav1:'Why AI compression?',nav2:'4 functions',nav3:'How it works',nav4:'Car park',nav5:'Result',nav6:'Existing image',nav7:'Continue learning',s1Kicker:'What does AI do here?',s1Title:'Compression becomes smarter when the camera first understands what matters.',s1p1:'The current CCTV Academy source describes AI optimizations in Dahua Smart H.265+ as a way to use storage and bandwidth more efficiently without simply discarding important detail in security footage.',s1p2:'Instead of treating every area of the image equally, it considers motion, objects and critical zones such as people, vehicles, tripwire and intrusion events.',s1p3:'The compression logic can therefore give relatively more attention to relevant parts of the scene and compress static or less important areas more strongly.',classicK:'Without AI context',classicH:'Treat almost everything the same.',classicP:'A fixed or general compression approach makes less distinction between an empty background and a relevant security object.',aiK:'With AI context',aiH:'More attention where it matters.',aiP:'The Academy explanation links object recognition, ROI, scene and events to a smarter distribution of video data.',s2Kicker:'Four AI-driven compression functions',s2Title:'Four ways the Academy page explains the optimization.',s2Intro:'The blocks below follow the four functions described on the current public CCTV Academy page.',c1h:'Motion-aware coding',c1p:'When motion occurs, more bitrate can be used. In static scenes, bitrate can remain lower. The Academy source also links relevance to AI detection.',c1chip:'Motion \u2192 more bits',c2p:'Relevant objects such as people or vehicles can be treated as important areas, while sky, walls or grass receive stronger compression.',c2chip:'Object \u2192 priority',c3h:'Scene-adaptive coding',c3p:'The Academy explanation describes adjustment based on scene type, day\/night and activity. With noisy night images it focuses on meaningful changes.',c3chip:'Scene \u2192 profile',c4h:'Event-driven streaming',c4p:'For relevant AI events such as SMD or perimeter alarms, the source describes a temporary quality increase while the stream stays more compressed outside events.',c4chip:'Event \u2192 higher quality',s3Kicker:'From scene to stream',s3Title:'The camera analyses first. Then the video data is distributed.',f1h:'Scene',f1p:'The camera sees background, motion and objects.',f2h:'Detection',f2p:'Relevant people, vehicles or events are recognized.',f3h:'Priority',f3p:'Important zones receive relatively more attention according to the Academy explanation.',f4p:'The stream is adapted to scene, motion and importance.',f5h:'Storage & network',f5p:'Compressed video data goes to recorder, storage or remote view.',s4Kicker:'Practical example from the Academy source',s4Title:'An empty car park changes as soon as a person enters the image.',bgLabel:'STATIC BACKGROUND \/\/ LOWER PRIORITY',bitLabel:'PERSON \/\/ HIGHER PRIORITY',s4p1:'The existing page uses an empty car park as its example. Without AI, the whole scene is stored using one general bitrate approach.',s4p2:'With AI + Smart H.265+, the source describes the car park itself receiving few bits. As soon as a person appears, the camera recognizes the relevant object.',s4p3:'That person is treated as an important ROI so colour and detail can be preserved better while the rest remains more heavily compressed.',s5Kicker:'What does that deliver according to the current Academy page?',s5Title:'Less data where possible. More detail where it matters.',r1h:'Claimed saving',r1p:'The current Academy source states 70\u201380% saving without loss of evidential value. This figure is shown here as a source claim, not a universal guarantee.',r2h:'Lower storage pressure',r2p:'More efficient compression can reduce required storage capacity.',r3h:'Lower network load',r3p:'Less video data can help with network traffic and remote viewing.',r4h:'Detail on relevant zones',r4p:'The Academy source highlights people, vehicles, faces and number plates as relevant detail zones.',noteH:'Important for technical claims',noteP:'Actual storage savings and image quality depend on scene, firmware, settings, resolution, frame rate, bitrate, motion, noise and camera\/recorder combination. The 70\u201380% above is the claim on the current CCTV Academy source page.',s6Kicker:'Preserve existing Academy media',s6Title:'The original illustration belongs to this lesson and must not disappear.',mediaH:'Existing AI optimization image',mediaP:'The public source confirms an existing CCTV Academy image about \u201cwat zijn AI optimalisaties\u201d. During the WordPress merge, preserve the current media URL and alt text exactly.',mediaWhyH:'Why is there deliberately no invented image URL here?',mediaWhyP:'The public index shows the image and alt description but does not reliably expose the current WordPress media source. This STAGING version therefore replaces nothing.',s7Kicker:'Build further on this knowledge',s7Title:'AI compression is one link in the complete CCTV video chain.',s7Intro:'Use the following Academy topics to understand codec, camera, AI and recorder together.',k1p:'First understand the basics of H.265 and Dahua Smart H.265+.',k1c:'View codec \u2192',k2p:'Compare manufacturer-specific H.265+ optimizations.',k2c:'Compare codecs \u2192',k3h:'8MP AI camera',k3p:'See codec, sensor, lens, lighting and AI as one device.',k3c:'View camera \u2192',k4h:'AI chip in the camera',k4p:'Understand where intelligent analysis happens inside the camera.',k4c:'View AI chip \u2192',k5h:'8MP image sensor',k5p:'Compression only begins after lens and sensor have built the image.',k5c:'View sensor \u2192',k6p:'The lens determines which scene ultimately needs to be encoded.',k6c:'View lens \u2192',k7h:'AI recording system',k7p:'Learn what the recorder must process from incoming video streams.',k7c:'View NVR training \u2192',k8p:'Compare bitrate, motion, ROI and recording quality yourself in practice.',k8c:'Discover Micro-Learning \u2192',ctaKicker:'CCTV Micro-Learning',ctaTitle:'You understand smart compression when you can see bitrate, motion and storage change together.',ctaText:'Test Smart H.265+, motion, night scenes and AI events on real cameras and recorders. Compare what happens to image quality, bitrate and storage when the scene changes.',cta1:'Discover CCTV Micro-Learning \u2192',cta2:'View CCTV training'},\n  de:{heroEyebrow:'CCTV Academy \u00b7 KI-Videokompression',heroTitle:'Nicht jeder Bildbereich<br><em>verdient gleich viele Bits.<\/em>',heroLead:'In der Academy-Erkl\u00e4rung verbindet Dahua intelligente Kompression mit Bewegung, relevanten Objekten und Szeneninformationen. Das Ziel: mehr Videodaten dort bewahren, wo sie wichtig sind, und weniger f\u00fcr statische oder weniger relevante Bildbereiche verschwenden.',heroCta1:'KI-Funktionen ansehen \u2192',heroCta2:'Zuerst Smart H.265+ verstehen',check1:'Motion-aware Coding',check3:'Szenenadaptive Codierung',check4:'Event-gesteuertes Streaming',nav1:'Warum KI-Kompression?',nav2:'4 Funktionen',nav3:'Funktionsweise',nav4:'Parkplatz',nav5:'Ergebnis',nav6:'Bestehendes Bild',nav7:'Weiterlernen',s1Kicker:'Was macht die KI hier?',s1Title:'Kompression wird intelligenter, wenn die Kamera zuerst versteht, was wichtig ist.',s1p1:'Die aktuelle CCTV-Academy-Quelle beschreibt KI-Optimierungen in Dahua Smart H.265+ als M\u00f6glichkeit, Speicher und Bandbreite effizienter zu nutzen, ohne wichtige Details in Sicherheitsbildern einfach zu verwerfen.',s1p2:'Statt jeden Bildbereich gleich zu behandeln, werden Bewegung, Objekte und kritische Zonen wie Personen, Fahrzeuge, Tripwire- und Intrusion-Ereignisse ber\u00fccksichtigt.',s1p3:'Dadurch kann die Kompressionslogik relevanten Teilen der Szene relativ mehr Aufmerksamkeit geben und statische oder weniger wichtige Bereiche st\u00e4rker komprimieren.',classicK:'Ohne KI-Kontext',classicH:'Fast alles gleich behandeln.',classicP:'Eine feste oder allgemeine Kompressionslogik unterscheidet weniger zwischen leerem Hintergrund und relevantem Sicherheitsobjekt.',aiK:'Mit KI-Kontext',aiH:'Mehr Aufmerksamkeit dort, wo es z\u00e4hlt.',aiP:'Die Academy-Erkl\u00e4rung verbindet Objekterkennung, ROI, Szene und Ereignisse mit einer intelligenteren Verteilung der Videodaten.',s2Kicker:'Vier KI-gesteuerte Kompressionsfunktionen',s2Title:'Vier Arten, wie die Academy-Seite die Optimierung erkl\u00e4rt.',s2Intro:'Die folgenden Bl\u00f6cke folgen den vier Funktionen, die auf der aktuellen \u00f6ffentlichen CCTV-Academy-Seite beschrieben werden.',c1h:'Motion-aware Codierung',c1p:'Bei Bewegung kann mehr Bitrate eingesetzt werden. In statischen Szenen kann die Bitrate niedriger bleiben. Die Academy-Quelle verkn\u00fcpft Relevanz zus\u00e4tzlich mit KI-Erkennung.',c1chip:'Bewegung \u2192 mehr Bits',c2p:'Relevante Objekte wie Personen oder Fahrzeuge k\u00f6nnen als wichtige Bereiche behandelt werden, w\u00e4hrend Himmel, W\u00e4nde oder Gras st\u00e4rker komprimiert werden.',c2chip:'Objekt \u2192 Priorit\u00e4t',c3h:'Szenenadaptive Codierung',c3p:'Die Academy-Erkl\u00e4rung beschreibt Anpassungen nach Szenentyp, Tag\/Nacht und Aktivit\u00e4t. Bei verrauschten Nachtbildern geht es um bedeutungsvolle \u00c4nderungen.',c3chip:'Szene \u2192 Profil',c4h:'Event-gesteuertes Streaming',c4p:'Bei relevanten KI-Ereignissen wie SMD oder Perimeteralarm beschreibt die Quelle eine vor\u00fcbergehende Qualit\u00e4tssteigerung, w\u00e4hrend au\u00dferhalb von Ereignissen st\u00e4rker komprimiert wird.',c4chip:'Event \u2192 h\u00f6here Qualit\u00e4t',s3Kicker:'Von der Szene zum Stream',s3Title:'Die Kamera analysiert zuerst. Danach werden die Videodaten verteilt.',f1h:'Szene',f1p:'Die Kamera sieht Hintergrund, Bewegung und Objekte.',f2h:'Erkennung',f2p:'Relevante Personen, Fahrzeuge oder Ereignisse werden erkannt.',f3h:'Priorit\u00e4t',f3p:'Wichtige Zonen erhalten laut Academy-Erkl\u00e4rung relativ mehr Aufmerksamkeit.',f4p:'Der Stream wird an Szene, Bewegung und Bedeutung angepasst.',f5h:'Speicher & Netzwerk',f5p:'Komprimierte Videodaten gehen an Recorder, Speicher oder Remote View.',s4Kicker:'Praxisbeispiel aus der Academy-Quelle',s4Title:'Ein leerer Parkplatz ver\u00e4ndert sich, sobald eine Person ins Bild kommt.',bgLabel:'STATISCHER HINTERGRUND \/\/ NIEDRIGERE PRIORIT\u00c4T',bitLabel:'PERSON \/\/ H\u00d6HERE PRIORIT\u00c4T',s4p1:'Die bestehende Seite verwendet einen leeren Parkplatz als Beispiel. Ohne KI wird die gesamte Szene nach einem allgemeinen Bitratenansatz gespeichert.',s4p2:'Mit KI + Smart H.265+ beschreibt die Quelle, dass der Parkplatz selbst wenige Bits erhalten kann. Sobald eine Person erscheint, erkennt die Kamera das relevante Objekt.',s4p3:'Diese Person wird als wichtige ROI behandelt, damit Farbe und Detail besser erhalten bleiben, w\u00e4hrend der Rest st\u00e4rker komprimiert bleibt.',s5Kicker:'Was bringt das laut aktueller Academy-Seite?',s5Title:'Weniger Daten, wo es m\u00f6glich ist. Mehr Detail, wo es z\u00e4hlt.',r1h:'Genannte Einsparung',r1p:'Die aktuelle Academy-Quelle nennt 70\u201380% Einsparung ohne Verlust des Beweiswerts. Diese Zahl wird hier als Quellenbehauptung gezeigt, nicht als universelle Garantie.',r2h:'Weniger Speicherdruck',r2p:'Effizientere Kompression kann die ben\u00f6tigte Speicherkapazit\u00e4t reduzieren.',r3h:'Geringere Netzwerklast',r3p:'Weniger Videodaten k\u00f6nnen Netzwerkverkehr und Remote Viewing entlasten.',r4h:'Detail in relevanten Zonen',r4p:'Die Academy-Quelle betont Personen, Fahrzeuge, Gesichter und Kennzeichen als relevante Detailzonen.',noteH:'Wichtig bei technischen Aussagen',noteP:'Tats\u00e4chliche Speicherersparnis und Bildqualit\u00e4t h\u00e4ngen von Szene, Firmware, Einstellungen, Aufl\u00f6sung, Bildrate, Bitrate, Bewegung, Rauschen und Kamera\/Recorder-Kombination ab. Die oben genannten 70\u201380% sind die Aussage der aktuellen CCTV-Academy-Quellseite.',s6Kicker:'Bestehende Academy-Medien erhalten',s6Title:'Die urspr\u00fcngliche Illustration geh\u00f6rt zu dieser Lektion und darf nicht verschwinden.',mediaH:'Bestehendes Bild zu KI-Optimierungen',mediaP:'Die \u00f6ffentliche Quelle best\u00e4tigt ein vorhandenes CCTV-Academy-Bild zum Thema \u201ewat zijn AI optimalisaties\u201c. Beim WordPress-Merge m\u00fcssen aktuelle Medien-URL und Alt-Text exakt \u00fcbernommen werden.',mediaWhyH:'Warum steht hier bewusst keine erfundene Bild-URL?',mediaWhyP:'Der \u00f6ffentliche Index zeigt Bild und Alt-Beschreibung, legt die aktuelle WordPress-Medienquelle aber nicht zuverl\u00e4ssig offen. Diese STAGING-Version ersetzt deshalb nichts.',s7Kicker:'Auf diesem Wissen aufbauen',s7Title:'KI-Kompression ist nur ein Glied der gesamten CCTV-Videokette.',s7Intro:'Nutze die folgenden Academy-Themen, um Codec, Kamera, KI und Recorder gemeinsam zu verstehen.',k1p:'Verstehe zuerst die Grundlagen von H.265 und Dahua Smart H.265+.',k1c:'Codec ansehen \u2192',k2p:'Vergleiche herstellerspezifische H.265+-Optimierungen.',k2c:'Codecs vergleichen \u2192',k3h:'8-MP-KI-Kamera',k3p:'Betrachte Codec, Sensor, Objektiv, Beleuchtung und KI als ein Ger\u00e4t.',k3c:'Kamera ansehen \u2192',k4h:'KI-Chip in der Kamera',k4p:'Verstehe, wo intelligente Analyse in der Kamera stattfindet.',k4c:'KI-Chip ansehen \u2192',k5h:'8-MP-Bildsensor',k5p:'Kompression beginnt erst, nachdem Objektiv und Sensor das Bild aufgebaut haben.',k5c:'Sensor ansehen \u2192',k6p:'Das Objektiv bestimmt, welche Szene sp\u00e4ter codiert werden muss.',k6c:'Objektiv ansehen \u2192',k7h:'KI-Aufzeichnungssystem',k7p:'Lerne, was der Recorder aus eingehenden Videostreams verarbeiten muss.',k7c:'NVR-Training ansehen \u2192',k8p:'Vergleiche Bitrate, Bewegung, ROI und Aufnahmequalit\u00e4t selbst in der Praxis.',k8c:'Micro-Learning entdecken \u2192',ctaKicker:'CCTV Micro-Learning',ctaTitle:'Intelligente Kompression versteht man, wenn man sieht, wie sich Bitrate, Bewegung und Speicher gemeinsam ver\u00e4ndern.',ctaText:'Teste Smart H.265+, Bewegung, Nachtbild und KI-Ereignisse an echten Kameras und Recordern. Vergleiche, was mit Bildqualit\u00e4t, Bitrate und Speicher passiert, wenn sich die Szene ver\u00e4ndert.',cta1:'CCTV Micro-Learning entdecken \u2192',cta2:'CCTV-Schulungen ansehen'}\n };\n function detectedLang(){var p=new URLSearchParams(location.search).get('lang');if(copy[p])return p;var m=location.pathname.match(\/^\\\/(nl|fr|en|de)(?:\\\/|$)\/i);return m&&copy[m[1].toLowerCase()]?m[1].toLowerCase():'nl'}\n var current=detectedLang();\n function localizeLinks(){root.querySelectorAll('a.localized-link').forEach(function(a){var original=a.getAttribute('data-original-href')||a.getAttribute('href');if(!a.getAttribute('data-original-href'))a.setAttribute('data-original-href',original);try{var u=new URL(original,location.origin);u.searchParams.set('lang',current);a.setAttribute('href',u.toString())}catch(e){a.setAttribute('href',original)}})}\n function apply(lang){if(!copy[lang])lang='nl';current=lang;root.querySelectorAll('[data-i18n]').forEach(function(el){var 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