Ngenxa yenkqubela phambili kubukrelekrele bokwenziwa (AI), utshintsho olukhulu luselubhakabhakeni kwihlabathi lolawulo lwezithuthi.Ukuphucula ukhuseleko lokuqhuba, ubugcisa bobukrelekrele bokwenziwa obufana neenkqubo zokubeka iliso kubaqhubi (i-DMS) kunye neenkqubo zokuncedisa abaqhubi eziphucukileyo (ADAS) zihlahl’ indlela yeendlela ezikhuselekileyo nezisebenzayo kwixesha elizayo.Kule bhlog, siphonononga ukuba i-AI ingasetyenziswa njani ukujonga indlela yokuziphatha engafanelekanga kunye nokunciphisa imingcipheko enokwenzeka, ukuguqula indlela ulawulo lwezithuthi olusebenza ngayo.
Khawube nomfanekiso-ngqondweni weqela leemoto ezineenkqubo ezikrelekrele ezikwaziyo ukujonga abaqhubi ngexesha lokwenyani, ukubona naziphi na iimpawu zokudinwa, ukuphazamiseka okanye ukuziphatha ngokungakhathali.Kulapho iinkqubo zokujongwa komqhubi (i-DMS) zingena khona, zisebenzisa i-algorithms yengqondo yokwenziwa ukuhlalutya ukuziphatha komqhubi ngokuqaphela ubuso, ukunyakaza kwamehlo kunye nokubeka intloko.I-DMS inokubona lula ukozela, ukuphazamiseka kwesixhobo esiphathwayo, kunye neziphumo zokunxila.I-DMS sisixhobo esibalulekileyo ekuthinteleni iingozi ezinokubakho ngokulumkisa abaqhubi kunye nabaphathi beenqanawa malunga naluphi na ukuphulwa.
Njengeteknoloji ehambelanayo, iiNkqubo zoNcedo loMqhubi oPhezulu (i-ADAS) nazo zidlala indima ebalulekileyo ekulawuleni iinqwelo.Ezi nkqubo zisebenzisa i-AI ukunceda abaqhubi kunye nokwandisa ukhuseleko ezindleleni ngokubonelela ngeempawu ezifana nesilumkiso sokuhamba kwindlela, ukuphepha ukungqubana kunye nolawulo lokuhamba ngenqanawa.I-ADAS ijonge ukuhlalutya idatha yexesha langempela ukusuka kwii-sensors ezahlukeneyo kunye neekhamera ezifakwe kwizithuthi ukunceda abaqhubi baphephe imingcipheko enokubakho kwaye baphuhlise imikhwa enoxanduva lokuqhuba.Ngokunciphisa impazamo yabantu, i-ADAS inciphisa ngokubonakalayo ukubakho kweengozi, kusizisa inyathelo elinye kufutshane nekamva lokuziqhuba.
I-synergy phakathi kwe-DMS kunye ne-ADAS sisiseko se-AI-based management fleet.Ngokudibanisa obu buchwepheshe, abaphathi bezithuthi banokufumana ukubonakala kwexesha lokwenyani kwindlela yokuziphatha kwabaqhubi kunye nokusebenza.Ii-algorithms zokufunda koomatshini zihlalutya inani elikhulu ledatha ukuchonga iipateni kunye neendlela zokuqhuba.Oku kuvumela abaphathi bezithuthi ukuba bazise iinkqubo zoqeqesho ekujoliswe kuzo, bajongane nemiba ethile, kwaye bathathe amanyathelo ayimfuneko ukunciphisa umngcipheko kunye nokuphucula ukhuseleko lokuqhuba lwezithuthi zabo.
Itekhnoloji ye-AI ayinakho kuphela ukunciphisa imingcipheko enokubakho enxulumene nokuqhuba ngokungafanelekanga, kodwa inokuzisa iinzuzo ezininzi kulawulo lwezithuthi.Ngokuzenzekelayo inkqubo yokubeka iliso, i-AI iphelisa imfuno yokubeka iliso ngesandla kunye nokunciphisa impazamo yomntu.Oku kwandisa iindleko kunye nokwandisa ukusebenza kakuhle ngenxa yokuba izixhobo zinokwabiwa ngokufanelekileyo.Ukongeza, ngokukhuthaza indlela yokuziphatha ekhuselekileyo, abaphathi bezithuthi banokulindela ukunciphisa iindleko zokugcinwa, ukuphucula ukusebenza kakuhle kwamafutha kunye nokunciphisa amabango e-inshurensi.Ukufakela izakhono ze-AI kulawulo lwezithuthi yimeko yokuphumelela kumashishini kunye nabaqhubi.
Ukuqukumbela, ukusetyenziswa kobukrelekrele bokwenziwa kulawulo lwezithuthi kuguqula ukhuseleko lokuqhuba.I-AI-powered driver monitoring systems (DMS) kunye ne-advanced driver assistance systems (ADAS) zisebenza kunye ukubeka iliso kwindlela yokuziphatha engafanelekanga nokunciphisa iingozi ezinokubakho.Ngokusebenzisa uhlalutyo lwedatha yexesha langempela, abaphathi bezithuthi banokujongana nemiba ethile, bazise iinkqubo zoqeqesho ekujoliswe kuzo, kwaye ekugqibeleni baphucule ukhuseleko lokuqhuba kwezithuthi zabo.Ukongeza, ngamanyathelo okhuseleko awandisiweyo, abaphathi bezithuthi banokulindela ukunciphisa iindleko, ukwandisa ukusebenza kakuhle, kunye nekamva elizinzileyo endleleni.Njengoko itekhnoloji iqhubeka nokuvela, ubukrelekrele bokwenziwa buhlala buyinxalenye ebalulekileyo yoshishino lolawulo lwezithuthi oluhlala lukhula.
Ixesha lokuposa: Jun-20-2023
