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Ukubona Ngamakhamera kuma-Elevator Ahlakaniphile Nezinhlelo Zokufinyelela: Ukuchaza Kabusha Ukuphepha, Ukusebenza Kahle, Nomuzwa Womsebenzisi
Kwadalwa ngo 01.07
Imakethe yezakhiwo ezihlakaniphile emhlabeni wonke iyachuma, kulindeleke ukuthi ifinyelele inani lamaRandi ayizigidi eziyizi-1.06 trillion ngo-2030 (Grand View Research). Ezingqimeni zale ngunguquko kukhona ukuhlanganiswa kobuchwepheshe obuthuthukisiwe obenza izakhiwo zibe nezingozi kancane, ziphatheke kahle, futhi zigxile kubasebenzisi. Phakathi kobuchwepheshe obunjalo, ukubona ngekhamera kuvele njengento eshintsha imidlalo ezindaweni ezimbili ezibalulekile: ama-elevator ahlakaniphile nezinhlelo zokufinyelela. Ngokungafani namathuluzi okugadwa ajwayelekile anomsebenzi wokurekhoda amavidiyo kuphela,ukubona ngekhamera yesimanje okunikezwe amandla ubuhlakani bokwenziwa (AI), ukufunda ngomshini (ML), nokubona ngekhompyutha—kwenza ukuthathwa kwezinqumo ngesikhathi sangempela, ukugcinwa okubikezelayo, nokuxhumana komsebenzisi okwenziwe ngezifiso. Kule blog, sizohlola ukuthi ukubona ngekhamera kushintsha kanjani ama-elevator ahlakaniphile nezinhlelo zokufinyelela, izimo zokusebenzisa ezintsha ezishukumisa ukwamukelwa, izinzuzo eziyinhloko kubaphathi bezakhiwo nabasebenzisi, kanye nezimo zesikhathi esizayo ezakha le ndawo eguquguqukayo.
Izinkinga zezinhlelo Zama-elevator Nokufinyelela Zendabuko
Ngaphambi kokucwilisa endimeni yombono wekhamera, kubalulekile ukuqonda ukushiyeka kwezixazululo ezijwayelekile zokulawula izindlu nokufinyelela. Izinhlelo zokufinyelela ezijwayelekile, njengamakhadi okhiye noma amakhodi e-PIN, zivame ukuba nezinkinga zokuphepha—amakhadi alahlekile noma ebiwe angasetshenziswa kabi, futhi ama-PIN angacashwa noma abelwane ngawo. Ziphinde zingabi namandla okuguquguquka, okwenza kube nzima ukuphatha izimvume zokufinyelela ezishintshayo (isibonelo, izivakashi zesikhashana noma abasebenzi abashintshayo).
Ngokufanayo, izindlu zokuhambisa abantu ezivamile zisebenza ngendlela yokuphendula. Ziyaphendula ezicini zabasebenzisi kodwa azazi umthwalo wabagibeli, izikhathi zokulinda, noma izingozi ezingenzeka. Lokhu kungasebenzi kahle kuholela ezikhathini ezinde zokulinda phakathi namahora aphithizelayo, ukuchitha amandla (njengoba izindlu zokuhambisa abantu zenza izitobhi ezingadingekile), kanye nezimpendulo ezibambezelekile ezimeni eziphuthumayo (isibonelo, umgibeli ewayo noma ebambekile). Ngaphezu kwalokho, ukugcinwa kuvame ukuhlelwa ngokusekelwe ezikhathini ezimisiwe kunokuba isimo sangempela sezinto, okuholela ekuphukeni okungalindelekile kanye nokulungiswa okubizayo.
Lezi zinkinga zigcizelela isidingo sendlela ehlakaniphile, enesinyathelo esiqhubekayo—futhi umbono wekhamera ugcwalisa lesi sikhala.
Umbono wekhamera ezinhlelweni zokufinyelela ezihlakaniphile: Ngaphezu kokuphepha okuyisisekelo
Izinhlelo zesimanje zokulawula ukungena azisasebenzi nje ngokuvimbela ukungena; zimayelana nokudala umuzwa ongaguquki, ophephile kubasebenzisi abagunyaziwe ngenkathi zigcina izinsongo zikude. Umbono wekhamera, uhlanganiswe ne-AI, uphakamisa lezi zinhlelo ezingeni eliphezulu ngokunika amandla ukuqinisekiswa kwezinto eziningi (MFA), ukuhlaziywa kokuziphatha, nokutholwa kwezinsongo ngesikhathi sangempela.
1. Ukuqashelwa kobuso okunamandla e-AI: Ukuqinisekiswa Okuphephile Nokungaguquki
Ukuqashelwa kobuso kungenye yezinhlelo zokusebenzisa izithombe zamakhamera ezisetshenziswa kakhulu ekulawuleni ukungena. Ngokungafani namakhadi angukhiye noma ama-PIN, izici zobuso ziyingqayizivele futhi azikwazi ukukhiqizwa kabusha kalula noma ukwabelwana ngazo. Ama-algorithm e-AI ahlaziya izindawo ezibalulekile zobuso (isibonelo, ibanga phakathi kwamehlo, ukuma komhlathi) ukuze aqinisekise ubunikazi ngokunemba okuphezulu—ngokuvamile ngezinga lokwamukelwa okungamanga (FAR) elingaphansi kuka-0.001%.
Lobuchwepheshe buletha umuzwa womsebenzisi ongabibikho: abasebenzi noma izakhamuzi zingangena ngokubheka nje ikhamera, okususa isidingo sokuzabalaza namakhiye noma amakhadi. Kubaphathi bezakhiwo, buletha ukulawula okuningiliziwe phezu kwezimvume zokungena. Ngokwesibonelo, abasizi bangase banikezwe ukungena okwesikhashana ezindaweni ezithile ngesikhathi esibekiwe, futhi izimvume zingasuswa ngokushesha uma kudingeka. Ezinye izinhlelo ezithuthukisiwe zihlanganisa ngisho nokuthola ukuthi umuntu uyaphila ukuze kuvinjelwe ukukhwabanisa (isibonelo, ukusebenzisa isithombe noma ividiyo ukukhohlisa uhlelo), okwengeza ukuvikeleka.
2. Ukuhlaziywa Kokuziphatha: Ukuthola Izinkinga Ngaphambi Kokuba Zenzeke
Ngaphandle kokuqinisekisa, ukubona ngekhamera kungahlaziya ukuziphatha komsebenzisi ukuthola izinsongo ezingaba khona zokuphepha noma ubungozi bezokuphepha. Ama-algorithm e-AI aqeqeshwe ukubona izindlela ezijwayelekile (isibonelo, ukuhamba ngejubane elizinzile, ukuswayipha ikhadi) futhi aqokomise izinto ezingajwayelekile (isibonelo, ukuzulazula endaweni enqatshelwe, ukugijima kakhulu, noma ukuzama ukuvula umnyango ngamandla).
Ngokwesibonelo, uma umuntu ehlezi eduze komnyango wegumbi leseva isikhathi esingaphezu kwemizuzu eyi-10, uhlelo lungathumela isexwayiso kubasebenzi bezokuphepha. Ngokufanayo, uma othile ezama ukulandela (ukulandela umsebenzisi ogunyaziwe emnyango ngaphandle kokuqinisekisa), ikhamera ingathola omunye umuntu bese yenza i-alamu. Le ndlela eqhubekayo isiza ukuvimbela ukwephulwa kwezokuphepha, ukwebiwa, noma ukonakala ngaphambi kokuba kwenzeke—into izinhlelo zokufinyelela zakudala ezingakwazi ukuyenza.
3. Ukuphathwa Kwezivakashi: Ukwenza Lula Inqubo Yokungena
Umbono wekhamera uguqula nokuphathwa kwezivakashi ezakhiweni zezentengiselwano nezokuhlala. Esikhundleni sokudinga ukuthi izivakashi zingenelele emagazini wephepha noma zilinde umsebenzi ukuba abayise, izinhlelo zokufinyelela ezihlakaniphile ezinekhono lekhamera zivumela ukungena okuzenzakalelayo. Izivakashi zingaskena ikhodi ye-QR (ethunyelwe nge-imeyili noma umyalezo) noma ziveze i-ID yazo kukhamera, ehlola ubunikazi bazo ngokumelene nohlu oluvunyelwe kusengaphambili. Uma seziqinisekisiwe, uhlelo lukhipha iphasela lokufinyelela lesikhashana (elidijithali noma elingokoqobo) futhi yazisa umphathi.
Lokhu akugcini nje ngokonga isikhathi izivakashi nabasebenzi kodwa futhi kuthuthukisa ukuphepha ngokuqinisekisa ukuthi izivakashi ezinemvume kuphela ezingena. Kuyakha futhi irekhodi ledijithali lazo zonke izivakashi, kwenze kube lula ukulandelela ukuthi ubani owayesakhiweni nokuthi nini—okubalulekile ukuze kuhambisane nemithetho kanye nophenyo lwezigameko.
Umbono wekhamera kuma-elevator ahlakaniphile: Kusukela ezokuthutha kuya ekuhambeni okuhlakaniphile
Ama-elevator ahlakaniphile awasewona nje ezokuthutha ezimile—ayizixazululo zokuhamba ezihlakaniphile ezivumelana nezidingo zomsebenzisi, zithuthukisa ukusebenza kahle, futhi zithuthukisa ukuphepha. Umbono wekhamera, uhlanganiswe ne-AI nezinzwa ze-Internet of Things (IoT), uyimbangela yalokhu kuguquka. Ngezansi izicelo eziyinhloko:
1. Ukutholwa kwabagibeli kanye nokwenza kahle kokuhamba
Enye yezinkinga ezinkulu kakhulu zamahhovisi endabuko yizikhathi ezinde zokulinda phakathi namahora aphezulu (isib. ukuphuma okusheshayo ekuseni ezakhiweni zamahhovisi). Umbono wekhamera ubhekana nalokhu ngokuthola ivolumu yabagibeli emalobini nasezindaweni zamahhovisi ngesikhathi sangempela. Ama-algorithm e-AI ahlaziya izithombe ukuze abike izindlela zethrafikhi futhi alungise ukuthunyelwa kwamahhovisi ngokufanele.
Ngokwesibonelo, uma ikhamera ithola isixuku esikhulu ehholo esitezi soku-1, ingathumela izinyunithi eziningana kuleso sitezi ngesikhathi esisodwa. Uma ikhabethe ligcwele, uhlelo lungakweqa izitobhi ezingadingekile ukuze abagibeli bafinyelele lapho beya khona ngokushesha. Lokhu akunciphisi nje kuphela izikhathi zokulinda (kuze kufike ku-30%, ngokusho kwezinye izifundo) kodwa futhi kusindisa amandla ngokunciphisa isikhathi sokungasebenzi nokunyakaza okungadingekile.
2. Ukuqapha Ezokuphepha Nokuphendula Ezimeni Eziphuthumayo
Ukubona ngekhamera kuthuthukisa ukuphepha kwezinyunithi ngokuqapha izingozi ezingenzeka nokuvumela ukusabela okusheshayo ezimeni eziphuthumayo. Amakhamera ngaphakathi kwamakhabethe angathola izigameko ezifana nabagibeli bewa, izimo eziphuthumayo zezokwelapha (isibonelo, umuntu ewa), noma ukuziphatha okungalawuleki. Ama-algorithm e-AI angakwazi ukubona lezi zigameko ngesikhathi sangempela futhi aqale izaziso kubaphathi besakhiwo noma ezinsizakalweni eziphuthumayo.
Emcimbini wokucisha kukagesi noma ukuphuka kweliftsi, amakhamera angakwazi ukubonisa ngaphakathi kweliftsi, avumele abasindisi ukuthi bahlole isimo (isibonelo, inani labagibeli, ukuthi kukhona olimele) ngaphambi kokuphendula. Ezinye izinhlelo zihlanganisa ngisho nokuxhumana ngezwi, okwenza abasindisi bakwazi ukuxhumana nabagibeli ngqo—kunciphisa ukukhathazeka nokuthuthukisa imiphumela yokuphepha.
3. Ukugcinwa Okubikezelayo: Ukunciphisa Isikhathi Sokungasebenzi
Ukuphuka kwamaliftsi kubiza kakhulu futhi kuyaphazamisa. Ukubona ngamakhamera, kuhlanganiswe ne-AI, kuvumela ukugcinwa okubikezelayo ngokugada isimo sezinto ezakha iliftsi (isibonelo, iminyango, izintambo, izinkinobho) ngesikhathi sangempela. Amakhamera angathola izimpawu zokuguga nokulimala (isibonelo, umnyango ongavali ngendlela efanele, intambo ekhanyayo) noma ukunyakaza okungajwayelekile (isibonelo, ukudlidliza okweqile).
Ama-algorithm we-AI ahlaziya le datha ukuze aqagulele ukuthi izingxenye zizobhujiswa nini futhi yazise amaqembu okugcinwa ngaphambi kokuba kube khona ukuphazamiseka. Lokhu kuguqula ukugcinwa kusuka kumodeli yokuphendula, esekelwe esikhathini, iye kumodeli yokubhekana nezinto ngaphambi kwesikhathi, esekelwe esimweni—kunciphisa isikhathi sokuphumula ngama-50%, ngokusho kwemibiko yomkhakha. Iphinde yandise impilo yezingxenye zezinyusi futhi yehlise izindleko zokugcinwa ngokuhamba kwesikhathi.
4. Ukulawula Okungathintwa: Inhlanzeko Nokulula
Ubhubhane lwe-COVID-19 lwakhulisa ukwamukelwa kobuchwepheshe obungathintwa, futhi umbono wekhamera udlale indima enkulu ekwenzeni izinyusi zihlanzeke kakhudlwana. Izinhlelo zokubona ngekhamera zingathola izimpawu zezandla (isb., ukunyakazisa, ukukhombisa) ukuvumela abasebenzisi ukuthi bakhethe izitezi ngaphandle kokuthinta izinkinobho. Ngokwesibonelo, umsebenzisi anganyakazisa isandla sakhe phambi kwekhamera ukubiza isinyusi noma akhombise inombolo yesitezi esibukweni sedijithali.
Lokhu akunciphisi nje ukusabalala kwezifo kodwa futhi kuthuthukisa ukuba lula kubasebenzisi abanezandla ezigcwele (isibonelo, ukuphatha izimpahla noma imithwalo). Ezinye izinhlelo ezithuthukile zisebenzisa ngisho nokuqashelwa kobuso ukuze kukhethwe ngokuzenzakalelayo isitezi esivakashelwa njalo ngumsebenzisi—kwakha umuzwa ogcwele, ongathintwa.
Izinzuzo Eziyinhloko Zokubona Nge-Camera Kubaphathi Bezakhiwo Nasebenzisi
Ukuhlanganisa ukubona nge-camera kumagunjana ahlakaniphile nezinhlelo zokufinyelela kunikeza izinzuzo eziningi kubaphathi bezakhiwo nabasebenzisi ngokufanayo:
Ukuphepha Okuthuthukisiwe: Kuncishiswe ubungozi bokufinyelela okungagunyaziwe, ukwebiwa, kanye nokuphulwa kwezokuphepha ngokusebenzisa ukuqinisekiswa okusekelwe ku-AI kanye nokutholwa kwezinto ezingajwayelekile.
• Ukusebenza Okuthuthukisiwe: Ukuthunyelwa kwamagunjana okwenziwe kahle kunciphisa izikhathi zokulinda nokusetshenziswa kwamandla; ukulawulwa kokufinyelela okwenziwe kahle nokuphathwa kwezivakashi konga isikhathi sabasebenzi.
• Ukonga Izindleko: Ukugcinwa okubikezelayo kunciphisa izindleko zokulungisa nesikhathi sokungasebenzi; ukusetshenziswa kwamandla okuncishisiwe kunciphisa izikweletu zamandla; izinqubo ezizenzakalelayo zinciphisa izindleko zabasebenzi.
• Okuhlangenwe Nakho Okungcono Komsebenzisi: Ukufinyelela okungenazinkinga, ukulawula okungenathinta, kanye nezinsizakalo eziqondene nawe (isib. ukukhethwa kwesitezi okuzenzakalelayo) kuthuthukisa ukulula nokwaneliseka.
• Ukuthobela kanye Nomthwalo Womsebenzi: Amarekhodi edijithali wokufinyelela kanye nomsebenzi wezivakashi asiza izakhiwo ukuthi zithobele izidingo zemithetho (isib. i-GDPR, i-HIPAA) futhi kube lula uphenyo lwezehlakalo.
• Ukuphepha Okuthuthukisiwe: Ukuqapha okungokoqobo kwamahhovisi kanye nezindawo zokufinyelela kuvumela ukusabela okusheshayo ezimeni eziphuthumayo kanye nezingozi ezingenzeka.
Ukubhekana Nezinkathazo: Ubumfihlo kanye Nokuphepha Kwemininingwane
Ngenkathi umbono wekhamera unikeza izinzuzo ezibalulekile, uphinde uphakamise izinkathazo mayelana nobumfihlo nokuphepha kwemininingwane. Abaphathi bezakhiwo kufanele bathathe izinyathelo zokuqala ukuze baqinisekise ukuthobela imithetho yokuvikela idatha (isib. i-GDPR e-EU, i-CCPA eCalifornia) futhi bagcine ukwethembana komsebenzisi.
Izinyathelo eziyinhloko zobumfihlo zihlanganisa: Ukucaca: Ukwazisa abasebenzisi ngokusetshenziswa kombono wekhamera (isibonelo, ngokusebenzisa izimpawu, izinqubomgomo zobumfihlo) kanye nezinhlobo zedatha eqoqwayo; Ukunciphisa Idatha: Ukuqoqa kuphela idatha edingekayo engozini ehlosekayo (isibonelo, idatha yokubona ubuso ukuze kuqinisekiswe, hhayi ukuze kube ukuqapha); Ukungaziwa: Ukwenza idatha ingaziwa noma nini lapho kungenzeka khona (isibonelo, ukufiphaza ubuso ezindaweni zomphakathi lapho ukuqinisekiswa kungadingeki); Isitoreji Esiphephile: Ukugcina idatha kumalondolozi afakwe ubumfihlo futhi ukukhawulela ukufinyelela kubantu abagunyaziwe kuphela; Imikhawulo Yokugcinwa Kwemininingwane: Ukusula idatha ngemuva kokuba ingasadingeki (isibonelo, idatha yezivakashi ngemuva kokuphela kokuvakasha kwazo).
Ngokusebenzisa lezi zinyathelo, abaphathi bezakhiwo bangasebenzisa izinzuzo zombono wekhamera ngenkathi bevikela ubumfihlo babasebenzisi.
Izitayela Eziyeza: Yini Elandelayo kuMbono Wakhamera Ezakhiweni Ezihlakaniphile?
Ikusasa lombono wakhamera ezindaweni ezihlakaniphile ezifana nezindlu zokugibela nezimiso zokungena lithembisa, kunezindlela eziningana ezibalulekile ezizayo:
1. Ukuhlanganiswa nezinye iziMiso Zezakhiwo Ezihlakaniphile
Umbono wakhamera uzohlanganiswa kakhulu nezinye iziMiso zezakhiwo ezihlakaniphile, njenge-HVAC, ukukhanyisa, nokuphepha komlilo. Ngokwesibonelo, uma ikhamera ithola ukuthi igumbi lenkomfa ligcwele, ingalungisa izinga lokushisa nokukhanyisa ukuze kuthuthukiswe induduzo. Uma umlilo utholakele, umbono wakhamera ungakwazi ukusiza ukuhola izindlu zokugibela ezindaweni eziphephile futhi uqondise imizila yokuphuma.
2. Ukuqhubeka Kwe-AI Nokuphatha Okuhlakaniphile
Njengoba iziMiso ze-AI ne-ML ziba ngcono, iziMiso zombono wakhamera zizoba nezinembayo futhi zisebenze ngezindlela eziningi. Zizokwazi ukubona izindlela eziyinkimbinkimbi, ukubikezela izindlela zethrafikhi ngokunemba okukhulu, futhi zivumelane nezidingo zomsebenzisi eziguquguqukayo ngesikhathi sangempela.
3. I-Edge Computing Yokucubungula Ngokwesikhathi Sangempela
I-Edge computing—ukucubungula idatha endaweni (kudivayisi noma emaphethelweni enethiwekhi) esikhundleni sokuba sefu—izoba yinto ejwayelekile. Lokhu kunciphisa ukubambezeleka, kuvumela ukwenziwa kwezinqumo ngesikhathi sangempela (okubalulekile ekuphenduleni ezimeni eziphuthumayo nasekuphathweni kwama-elevator) futhi kuthuthukisa ukuphepha kwedatha ngokugcina ulwazi olubucayi endaweni.
4. Ukugxila ekusimameni
Ukubona ngekhamera kuzoba nendima enkulu ekwenzeni izakhiwo zisimame kakhudlwana. Ngokwenza kahle ukuhamba kwama-elevator nokunciphisa ukusetshenziswa kwamandla, kuzosiza ekwehliseni ukukhishwa kwekhabhoni. Ngaphezu kwalokho, ukubona ngekhamera kungaqapha ukusetshenziswa kwamandla ezindaweni zokungena (isib. ukukhanyisa, ukushisa) futhi kutholakale amathuba okuthuthukisa ukusebenza kahle.
Isiphetho
Umbono wekhamera awuseyona nje into yokugada—uyisisekelo sobuchwepheshe esibuyekeza indlela esisebenzisana ngayo nezindlu zokugibela ezihlakaniphile nezinhlelo zokungena. Ngokunika amandla ukuqinisekiswa okuphephile, okungenamihawu, ukuthuthukisa ukusebenza kahle kwezindlu zokugibela, ukuthuthukisa ukuphepha, nokuthuthukisa ulwazi lomsebenzisi, kusiza ekwakheni izakhiwo ezihlakaniphile, eziphumelela kakhudlwana, futhi eziphephile. Njengoba ubuchwepheshe buqhubeka nokuthuthuka, ukuhlanganisa umbono wekhamera nezinye izinhlelo zezakhiwo ezihlakaniphile kuzovula amathuba amaningi, kuguqule izakhiwo kusuka ezindaweni nje zokusebenza noma zokuhlala zibe izindawo ezihlakaniphile ezivumelana nezidingo zethu.
Kubaphathi bezakhiwo abafuna ukuhlala phambili, ukutshala imali kubuchwepheshe bezithombe zamakhamera kuyisinqumo esihlakaniphile. Ngokubhekana nezikhalazo zobumfihlo nokusebenzisa izinto ezintsha zakamuva, bangavula amandla aphelele obuchwepheshe obuguqula izinto futhi bakhe izakhiwo eziphephile, eziphumelela kakhudlwana, futhi ezigxile kubasebenzisi kakhulu.
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