isiZulu
How Camera Modules Improved Security in Retail Stores: From Blurry Footage to Real-Time Protection
Kwadalwa ngo 11.12
Ishibhile yokuncipha kwezohwebo ibiza amabhizinisi emhlabeni wonke ngaphezu kwezigidi eziyi-$100 ngonyaka, lapho ukuhweba, ubugebengu, kanye neziphakamiso zokusebenza kubalwa khona ku-70% yokulahleka [NRF 2024]. Kwesikhathi eside, amakhamera okuphepha ayebhekwa njengokuhlanganisa ubufakazi ngemva kwesigameko—okungacacile, okuphendulayo, futhi okungahlangene nezinsizakalo zansuku zonke. Namuhla, ukuthuthukiswaamamojula ekhamerababhala kabusha umthetho, bephendula ukubhekwa okungasebenzi kube yisistimu yokuphepha esebenzayo. Ake sihlole ukuthi lezi zinyathelo zobuchwepheshe zishintsha kanjani ukuphepha kokuthenga.
Izithiyo Zokubhekwa Kwezakhiwo Zangaphambili
Izinhlelo ze-CCTV zendabuko zehlulekile ezitolo ezintathu ezibalulekile. Okokuqala, izindawo ezingenalutho zaziningi: amakhamera abekwe ophahleni abawathathanga ama-checkout counters kodwa aphuthelwa ukwenziwa kwe-POS screen njengokucindezela okhiye bokukhansela noma ukwehliswa kwamanani. Izindlela zokuzihlola zaba izindawo zokweba, nezikhodi eziphonyiwe nezifinyezo ezingaphelele zidlula kubaphathi zingabonwa. Okwesibili, ukuxhumana kwedatha: Amarekhodi ezokuhweba nezithombe zevidiyo zikhona ezindaweni ezihlukene, kuthatha isikhathi ukucwaninga ubugebengu uma abahloli bedinga ubufakazi obunemigqa yesikhathi ukuze kuhlangatshezwane nezidingo ze-PCI-DSS. Okwesithathu, ukungasebenzi kahle kokuphathwa: Izitolo ze-chain zidinga ama-NVRs endaweni ngayinye, okwandisa izindleko zokugcinwa futhi kuvimbela ukubhekwa okuhlanganisiwe.
Lezi zikhala azikabizi kuphela—zib dangerous. Izigebengu ezihlelwe kahle zisebenzise ukuhlinzekwa kwezimemezelo ezibambezelekile ukuze zifeze ama-scam wokubuyisela imali, kanti ukuhlaselwa ngemva kwezinsuku kuvame ukuhamba kungabonwa kuze kube sekuseni. Amamojula wekhamera adinga ukuhlinzekwa kabusha ngokuphelele.
1. Ukuhlanganiswa kwe-POS: Ukuvalwa kwe-Screen Blind Spot
Ukuqhamuka kokuqala kwavela ekuhlanganiseni ukuhlinzekwa kwemakhamera nedatha yephuzu lokuthengisa (POS). Izixazululo ezifana neDeskCamera zikhulula isidingo sezinsiza ezengeziwe ngokusakaza ama-POS kanye nezikrini zokuzihlola ngqo kumasistimu okuphatha ividiyo (VMS). Le nhlanganisela ifaka umbhalo we-receipt, ama-ID abathengisi, kanye nezikhathi zokuhweba kuvidiyo ye-HD ephilayo, iguqula ubugebengu obungabonakali bube ubufakazi obusebenziseka.
A 2025 case study of a U.S. grocery chain found that POS-synced cameras reduced cashier fraud by 47% in six months. Loss-prevention teams used keyword searches to flag suspicious activities—like repeated voids or coupon abuse—the moment they occurred, instead of sifting through hours of footage. For self-checkout, specialized micro-cameras (such as Avigilon’s H5A modular units) with 5MP resolution discreetly monitor scan areas, detecting fake barcodes before items leave the store.
2. Edge Computing: Izexwayiso Zesikhathi Sangempela, hhayi Izithombe Zangemva Kwenqubo
I-Edge computing iguqule ama-module wekhamera abe yizinzwa ezihlakaniphile esikhundleni sokuba amathuluzi okurekhoda. Ngokucubungula idatha endaweni eseduze esikhundleni sokuyithumela efwini, lezi zinhlelo zikhombisa izaziso ezisheshayo ngisho nasemaphutheni e-inthanethi. Ukuhlaziywa okwenziwa yi-AI okuhlanganiswe kumadivayisi e-edge kuthola izinkinga ngesikhathi sangempela: ikhasimende efihla impahla, umqashi ofinyelela ezindaweni ezivinjelwe, noma iqembu elihamba ngokungajwayelekile.
Umthengisi wezobuhle waseJapan, iCosme Company, ubone imiphumela emangalisayo ngemuva kokufaka amakhamera anokuxhumana kwe-edge ezindaweni eziyi-23. Le nkqubo isebenzisa ukutholwa kokunyakaza nokwaziswa kobuso ukuze ibhansile abathengisi abaphindaphindiwe, ithumela izaziso kuzo zonke izitolo lapho umuntu ophakanyisiwe engena. Izinsongo zokungena ziye zehla ngo-62% ngoba amakhamera akhiphe ama-alamu ngokushesha esikhundleni sokulinda amaqembu ezokuphepha ukuthi abuke izithombe. Ukusebenza kwe-edge kuphinde kwehlise izindleko ze-bandwidth ngo-35%—okubalulekile kumashalofu akhulayo afinyelela ezitolo eziyizinkulungwane.
3. Ukuklama Okumodular: Ukuvikeleka Okwenziwe Ngokwezifiso Kuwo Wonke Amacala
Izithombe ezilungele wonke umuntu sezidala. Izinhlelo zesithombe ezihlanganisiwe zanamuhla zishintsha ukuze zihlangabezane nezidingo ezihlukahlukene zokuthengisa: ama-lensi e-fisheye abamba izindawo ezingu-360° phansi ngedivayisi eyodwa, kanti ama-modules e-pinhole alandelela izindawo ezincane ezifana nezitolo zokugcina noma ama-ATM kiosks. Ikhamera ye-Avigilon H5A ehlelwe kahle ibonisa le msebenzi—iyunithi yayo eyinhloko isekela ama-imager amabili angashintshwa, ivumela abathengisi ukuthi bahlanganise ama-pinhole angama-right-angle ukuze balandele kahle ophahleni kanye nama-micro-bullets ukuze asetshenziswe ngaphandle okungamelana nezimo zezulu.
CP Plus ithatha ukwenziwa ngokwezifiso phambili ngezinsiza ezikhethekile: amakhamera e-bullet e-4K IR ezindaweni ezimnyama, amakhamera okubalelwa kwabantu ezicathulweni ukuze kuthuthukiswe abasebenzi, kanye nezindonga ezine-heatmap ezithola izindawo eziphakeme zokweba. I-chains yezimpahla yase-UK isebenzise lezi zinsiza ukuze ihlele kabusha ama-rack okukhombisa, yehlisa ukuhweba ezikhaleni "ezimfihlakalweni" ngo-40%. Ukuphindaphinda futhi kulula ukuthuthukisa—abathengisi bangangeza i-AI analytics ezinsizeni ezikhona esikhundleni sokushintsha izinhlelo eziphelele.
4. Ukuphathwa Okuphakathi: Ukulawulwa Kwezakhiwo Ezingaphezu Kwendawo
Abathengisi bechain babenqaba ngezokuphepha eziphukile—isitolo ngasinye sasigcina i-NVR yaso, okwenza kube nzima kakhulu ukwenza uphenyo phakathi kwezindawo. Amamojula amakhamera axhunywe ku-cloud manje avumela ukubhekwa okuhlanganisiwe ngezinkundla ezifana ne-FS’s VMS noma i-Verkada’s Alta Aware. I-Headquarters ingafinyelela izithombe zangempela ezivela kunoma yisiphi isitolo ngezimoto eziphathwayo, ibuyekeze izinsuku eziyi-90 zevidiyo ezigcinwe, futhi ilungise izilungiselelo zekhamera kude.
I-Company yeCosme yehlise izindleko zokusebenza ngo-30% ngokususa ama-NVRs asendaweni, igxile ekugcineni nasekulawuleni e-hedquarters yayo eTokyo. Kubhrendi zomhlaba, lokhu kusho izinqubo zokuphepha ezihambisanayo: umkhuba wokweba obonwa eParis ungavula ukuvuselelwa kwemigomo eNew York ngaphakathi kwamahora. Izinhlelo zeCloud nazo zenza kube lula ukuhambisana—zizenzakalelayo zenza izindlela zokuhlola ezilungile ze-GDPR ezinevidiyo enesikhathi sokuhlonza kanye nedatha ye-POS.
Ukulinganisa Ukuvikeleka Nokwethembeka Kwamakhasimende
Ukubhekwa okuqhubekayo kukhuphula ukukhathazeka ngokuqinisekiswa, kodwa amamojula amakhamera anamuhla abhekana nalokhu ngokucacile nangokunembile. Izinhlelo ze-AI zigwema ukuhamba phambili kokuhlonza ubuso ngokugxila ezimisweni zokuziphatha (isb. ukuhlinzeka okungajwayelekile) esikhundleni sedatha ye-biometric. Izimpawu zekhamera ezibonakalayo zivikela ubugebengu ngenkathi ziqinisekisa amakhasimende ukuthi ukuphepha kwabo kubalulekile—ucwaningo lwe-Verkada luthole ukuthi u-68% wabathengi uzizwa ephephile kakhulu ezitolo ezinezibhengezo ezibonakalayo, ezithuthukisiwe zokubhekwa.
Izici zokuhambisana ezifana ne-FIPS 140-2 encryption (kuhlelo lwe-Unity lwe-Avigilon) kanye ne-ONVIF interoperability ziqinisekisa ukuvikelwa kwedatha. Abathengisi bangaphinde banciphise ukufinyelela: abaphathi bezitolo babona ama-feed aphilayo, kanti abaphathi bendawo bafinyelela imibiko ye-analytics yamasonto onke—akukho ukuvezwa kwedatha okungadingekile.
Ikusasa: Ukuvikeleka Okubikezelayo
Amamojula ekhamera ayaguquka aphuma ezikhathini zokwazisa ngesikhathi sangempela abe amathuluzi okubikezela. Ama-algorithms okufunda ngomshini ahlaziya idatha yokweba esikhathini esedlule ukuze abikezele izikhathi eziphakeme zokubhekelela (isb. amaholo ezinsuku zokuphumula noma imicimbi yokuthengisa ngemva kokuthengisa), okukhuthaza ukulungiswa kokusebenza ngaphambi kwesikhathi. Ukuhlanganiswa nezinsiza ze-IoT kuzokwenza lokhu kube ngcono: ama-shelf akhanyayo akhuthaza ukugxila kwekhamera uma izinto zishintshwa, noma ama-sensor ezicabha ahambisana nokwaziswa kobuso ukuze abikezele ukufika okungagunyaziwe ngemva kwezinsuku zokusebenza.
Kubantu abancane bezamabhizinisi, ukuthengeka kuyathuthuka futhi. Izinhlelo ezisekelwe efwini ezine-akhawunti yokukhokha njengoba usebenzisa ziqeda izindleko zokuqala zehardware, zenza ukuthi ukuphepha okwenziwa nge-AI kube kufinyeleleka kubathengisi abazimele.
Isiphetho: Ukutshalwa kwezimali kuZibambiso Zobuhlakani
Ukushintsha kusuka kwi-CCTV esezingeni eliphezulu kuya kumamojula amakhamera athuthukile akusikho kuphela ukuphuculwa kwezobuchwepheshe—kuyisidingo sebhizinisi. Ngokuvala izikhala eziphumayo ze-POS, ukuhlinzeka ngezixwayiso zangesikhathi sangempela, ukujolisa kumaphuzu ahlukile ezitolo, nokuvumela ukulawulwa okuhlanganisiwe, lezi zinhlelo zinciphisa ukulahleka ngenkathi zithuthukisa ukuphepha kwabathengi nabasebenzi. Idatha ikhuluma yona: abathengisi abasebenzisa izixazululo zamakhamera ezihlanganisiwe babona ukwehla okuphakathi kuka-38% ekulahlekeni kanye nokwanda okungu-22% ekusebenzeni kahle [Retail Technology Insider 2025].
Njengoba ubugebengu bokuthengisa obuhlelwe bukhula futhi izidingo zokuhambisana ziba nzima, amamojula wekhamera azohlala engumgomo wokuqala wokuvikela. Kubathengisi abakulungele ukudlulela phambili kokubheka okuphendulayo, ikusasa lokuphepha lihlelekile, lihlanganisiwe, futhi libalulekile.
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