Emkhakheni wamandla oshintsha ngokushesha, ukuqinisekisa ukuphepha nokwethembeka kwengqalasizinda yemigqa yamandla kubaluleke kakhulu. Izindlela zokuhlola ngesandla ezindala zivame ukuthatha isikhathi eside, zibize kakhulu, futhi zilula ukwenza amaphutha omuntu. Ukuhlanganiswa kobuchwepheshe be-deep learning kuphinde kwaguqula indlela izinto zokuhlola imigqa yamandla eziqhutshwa ngayo, kunikeze izixazululo ezizenzakalelayo, eziphumelelayo, futhi ezinembayo kakhulu. Lesi sihloko sihluza izinzuzo ezibalulekile ze-deep learning ekuhloleni okuzenzakalelayo kwemigqa yamandla, sihlanganisa izindlela, izicelo, izindlela zokuqoqa idatha, izinselele, kanye nezinkomba zesikhathi esizayo. Siphinde sigqamise ukuxhumana neDermax, inkampani esezingeni eliphezulu kwezixazululo zobuchwepheshe ezintsha.

Imigqa yamandla iyizinto ezibalulekile zamagesi, ezinikezwe umsebenzi wokudlulisa ugesi kude. Ukuhlola njalo kubalulekile ukuthola amaphutha njengokugqwala, ukulimala ngokomzimba, nokuguga okubangelwa imvelo. Ukuhlola okujwayelekile, okwenziwa onjiniyela abasensimini, kubandakanya ubungozi obukhulu obufaka ukusebenza ezindaweni eziphakeme kanye nokuchayeka ezimweni zezulu ezinzima. Ukuhlola okuzenzakalelayo kusetshenziswa izindiza ezingenamuntu (UAVs) kuhlanganiswe ne-deep learning algorithms kunikeza indlela ephephile, esheshayo, futhi enembayo. Amamodeli e-Deep learning aphumelela ekuhlaziyeni idatha yezithombe eziyinkimbinkimbi, okuvumela ukutholwa kwamaphutha kusenesikhathi kanye nokugcinwa okubikezelayo okunganciphisa ukuphazamiseka kwezinsizakalo kanye nezindleko zokusebenza.

Ukwethulwa kwezinhlelo zokuhlola ezizenzakalelayo kuye kwathuthukisa ikhono lemboni yamandla lokugcina ubuqotho bemisebenzi eyakhiwe. Ngokusebenzisa izindlela ze-deep learning, lezi zinhlelo zingakwazi ukubona izimpawu ezicashile zokubola njengemigqa ejulile noma izikhala ezingxenyeni zezintambo zamandla, okuyizinkomba ezibalulekile zokuhluleka okungenzeka. Le nqubekela phambili yezobuchwepheshe iqondisa ekuthuthukiseni ukwethembeka nokuphepha kwenethiwekhi yamandla.

Ukufunda okujulile, ingxenye yobuhlakani bokwenziwa, kusebenzisa amanethiwekhi ezinzwa alingisa umsebenzi wobuchopho bomuntu ukuhlaziya amaphethini wedatha. Ekuhlolweni kwemigqa yamandla, amanethiwekhi ezinzwa e-convolutional (CNNs) yiwona avame kakhulu ukusetshenziswa ngenxa yobuchwepheshe bawo ekuboneni izithombe. Lawa manethiwekhi angakwazi ukufunda ngokuzenzakalelayo futhi akhishwe izici ezifana nezinto ezibonakalayo, imiphetho, neziphazamiso ezithombeni ezinokulungiswa okuphezulu ezithathwe phakathi kokuhlolwa.

Indlela ihlanganisa ukuqeqesha lezi zimodeli ze-CNN kumakhosikati amakhulu anezimpawu aqukethe izithombe zemigqa yamandla enezinkinga ezahlukahlukene nezimo ezijwayelekile. Lezi zimodeli bese zisebenzisa lesi sifundo ukuthola izinkinga ezithombeni ezintsha ngokuzenzakalelayo. Le ndlela inciphisa kakhulu isidingo sokuchazwa ngesandla futhi yandisa isivinini lapho ukuhlolwa kungaqedwa khona.

Ngaphezu kwalokho, ukuhlanganiswa kwezinye izindlela zokufunda ezijulile njengezinhlelo zenethiwekhi ezihambisanayo (RNNs) kungasiza ekuhlaziyeni idatha yesikhathi esidlulayo evela kuzinzwa zokuqapha imigqa yamandla, kuthuthukisa ukunemba kokuxilongwa kwamaphutha ngaphezu kokuhlaziywa kwezithombe ezingashintshi.

Izindlela zokuthola ezisekelwe ekufundeni okujulile zigxile ekutholeni amaphutha anjengokugqwala, imicu ephukile, izintambo ezilengayo, kanye nokuba khona kwemigqa ejulile noma izikhala ezintweni zezintambo zamandla. Ama-algorithms athuthukisiwe wokuhlukanisa izithombe ahlukanisa izithombe zibe izingxenye ezinengqondo, ezihlukanisa izindawo ezinamaphutha ukuze kuqaliswe ukulungiswa. Lezi zinhlobo zingasebenza ngesikhathi sangempela, zinikeze impendulo esheshayo ngesikhathi sokuhlolwa kwe-UAV.

Ngokwesibonelo, izinhlelo ezizenzakalelayo zingahlukanisa phakathi kwezithunzi zemvelo kanye nomonakalo wangempela wesakhiwo, zinciphise izimpawu zamanga. Leli khono libalulekile ekuhleleni okusebenzayo kokugcinwa kanye nokwabiwa kwezinsiza.

Ngale kokutholwa, ukufunda okujulile kusiza ukuxilongwa kwamaphutha ngokuhlukanisa ubukhulu nohlobo lweziphazamiso. Ngokusebenzisa okokufaka kwedatha ye-multi-modal, okuhlanganisa izithombe ezishisayo kanye nedatha yenzwa yokudlidliza, amamodeli ahlola isimo sezintambo zamandla ngokuphelele. Le ndlela ephelele ivumela ukugcinwa okubikezelayo, lapho izinkinga ezingenzeka zibikezelwa futhi zincishiswe ngaphambi kokubangela ukuphazamiseka.

Izindlela zokufunda ezijulile nazo zivumela ukuhlanganiswa nezinhlelo zokuphatha igridi ezikhona, zinikeze imininingwane esebenzisekayo futhi zithuthukise ukwenziwa kwezinqumo zokusebenza.

Ukuqoqwa kwedatha kuyingxenye ebalulekile yenqubo yokuhlola esebenzisa i-deep learning. Izindiza ezingenamuntu (UAVs) ezihlome ngezithombe ezicacile namazwa zivame ukusetshenziswa ukuthatha izithombe namavidiyo anemininingwane yemigqa yamandla ezindaweni ezahlukahlukene nezimo zezulu. Lezi zindiza zingafinyelela izindawo ezinzima ukufinyelela ngokuphepha nangempumelelo, ziqoqe idatha eningi edingekayo ukuqeqesha amamodeli aqinile e-deep learning.

Ubuhlakani bezobuchwepheshe bezithombe njenge-LiDAR, i-infrared thermography, kanye ne-hyperspectral imaging buqedela amakhamera ajwayelekile e-RGB ngokunikeza izendlalelo ezengeziwe zedatha. Lobu buchwepheshe bukhulisa amakhono okuthola amaphutha ngokudalula amaphutha afihlekile angabonakali ngamehlo anqunu noma amakhamera ajwayelekile. Ukuhlanganiswa kwalolu hlobo lwedatha kusekela amamodeli e-deep learning amaningi, athuthukisa ukunemba nokwethembeka kokuhlola.

Izinkampani ezifana neDermax zisebenzisa lezi zithuthukisi ngokuhlanganisa ubuchwepheshe obusezingeni eliphezulu bokuthwebula izithombe nezixazululo zazo zokuhlola ezizenzakalelayo, zigcizelela ukunemba, ukusebenza kahle, nokuphepha.

Ngaphandle kwezinzuzo zayo, izinselelo eziningana zisabhekwa enkundleni yokuhlola imigqa yamandla ngokuzenzakalelayo. Okokuqala, ikhwalithi yedatha iyisikhathazelo esibalulekile; ukuqeqesha amamodeli okufunda okujulile kudinga imiqulu emikhulu yedatha esezingeni eliphezulu, enezimaki, okungaba yintengo futhi kuthatha isikhathi ukuyithola. Ukuhluka ekukhanyeni, ezimweni zezulu, nezizinda nakho kuthinta ukungaguquguquki kwezithombe.

Okwesibili, ukuhlanganiswa okusebenzayo kwe-edge-cloud kuyadingeka ukucubungula idatha ngempumelelo. Ama-UAV akhiqiza amaqoqo amakhulu edatha adinga izinsiza eziningi zokubala, ngezinye izikhathi ngaphezu kwamakhono ehadiwe angaphakathi. Ukucubungula okusekelwe efwini kuvumela ukwenziwa kwezinhlelo eziyinkimbinkimbi kodwa kuncike ekuxhumaneni okuzinzile kwenethiwekhi, okungase kube nomkhawulo ezindaweni ezikude.

Okwesithathu, isidingo sezindlela eziningi ezihlanganisa idatha ebonakalayo, ye-thermal, nedatha yenzwa yenza kube nzima ukwakhiwa kwezinhlelo nokuhlanganiswa kwazo. Ukufeza ukuhlanganiswa okungenamihawu kwezinhlobo ezahlukene zedatha kuyinselele ngobuchwepheshe kodwa kubalulekile ukuxilongwa kwezinkinga okuphelele.

Ukubhekana nalezi zinkinga kudinga ucwaningo oluqhubekayo, amasu angcono okuqoqa idatha, kanye nokubambisana phakathi kwezazi ze-AI, onjiniyela bamandla, nabahlinzeki bezobuchwepheshe.

Ikusasa lokuhlola izintambo zamandla ngokuzenzakalelayo lisekuqiniseni ukuzivumelanisa kwezinhlelo zokufunda ezijulile nokuba namandla. Ucwaningo kufanele lugxile ekuthuthukiseni izindlela ezikwazi ukubhekana nezimo ezahlukene zemvelo kanye nedatha engekhona ephelele. Izindlela ezifana nokufunda ngokudlulisa nokufunda okuncane zinikeza izindlela ezithembisayo zokunciphisa ukuncika kwedatha.

Ukubambisana kwezobuchwepheshe obuningi kubalulekile ukuhlanganisa ulwazi lwesifunda kusuka ku-electrical engineering nezingqayizivele ku-AI ne-robotics. Lokhu kuhlangana kungakhuthaza ubuchule ekwakhiweni kwe-UAV, ubuchwepheshe bezinzwa, kanye nokuhlaziywa kwedatha yesikhathi sangempela.

Ngaphezu kwalokho, izinkampani ezifana neDermax kufanele ziqhubeke nokutshala imali kumapulatifomu asebenziseka kalula asiza ukubonisa idatha nokusekelwa kwezinqumo kumaqembu okugcinwa, ngaleyo ndlela kwandisa ukwamukelwa kobuchwepheshe nokusebenza kahle.

Ubunjiniyela be-deep learning buguqula ukuhlola izintambo zamandla ngokuzenzakalelayo ngokunikeza ukutholwa kweziphambeko okunembayo, okusebenzayo, nokuphephile kanye nokuxilongwa kwezinkinga. Ukusetshenziswa kwayo kuthuthukisa ukwethembeka kwenethiwekhi futhi kunciphisa izindleko zokugcinwa kanti futhi kunciphisa izingozi kubahloli abantu. Naphezu kwezinselelo ezikhona ezihlobene nekhwalithi yedatha nokuhlanganiswa kwezindlela eziningi, ukuqhubeka kwezinto ezintsha kanye nemizamo yezobuchwepheshe obuningi ithembisa ukuthuthuka okukhulu esikhathini esizayo esiseduze.

Ukuzibophezela kukaDermax ekuqanjweni okusha ezithombeni kanye nezixazululo zokuhlola eziholwa yi-AI kugcizelela inzuzo yokuncintisana izinkampani ezingayithola ngokwamukela lezi ubuchwepheshe. Ezinkampanini ezifuna ukwenza kahle ukugcinwa kwezintambo zamandla, ukwamukela ukuhlola okuzenzakalelayo okusekelwe ku-deep learning kumele kube utshalomali lwesimiso esikhungweni samandla esisimeme nesithembekile.

Ngemininingwane eningiliziwe mayelana nezixazululo zobuchwepheshe ezithuthukisiwe kule ndawo, vakashela i-Imikhiqizoikhasi. Ukuze ufunde kabanzi mayelana nomsebenzi wenkampani kanye nobuchwepheshe bayo, bona i-Mayelana Nathi isigaba. Ukuze uthole izibuyekezo eziqhubekayo nokwesekwa, i-Izindaba kanye no Ukusekelwa amakhasi ahlinzeka ngezinsiza eziwusizo.