{"id":12991,"date":"2021-06-17T11:00:00","date_gmt":"2021-06-17T14:00:00","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/?p=12991"},"modified":"2022-10-18T08:09:15","modified_gmt":"2022-10-18T11:09:15","slug":"urban-computing-challenges-big-cities","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/lv\/pilsetvides-skaitlosanas-problemas-lielajas-pilsetas\/","title":{"rendered":"Pils\u0113tas skait\u013co\u0161ana: Lielpils\u0113tu lielo izaicin\u0101jumu risin\u0101\u0161ana"},"content":{"rendered":"<p>M\u016bsdien\u0101s liel\u0101s pils\u0113tas saskaras ar liel\u0101m probl\u0113m\u0101m, piem\u0113ram, satiksmes sastr\u0113gumiem, gaisa pies\u0101r\u0146ojumu un ener\u0123ijas pat\u0113ri\u0146u. \u0160\u012bs lielpils\u0113tu probl\u0113mas var risin\u0101t, izmantojot <a href=\"https:\/\/en.wikipedia.org\/wiki\/Big_data\"><strong>lielie dati<\/strong><\/a> (kas noz\u012bm\u0113 lielu datu apjomu apstr\u0101di).<\/p>\n\n\n\n<p>Tie\u0161i t\u0101da ir pils\u0113tvides skait\u013co\u0161ana. To var defin\u0113t vienk\u0101r\u0161i k\u0101 <em>lielo datu izmanto\u0161ana, lai risin\u0101tu lielpils\u0113tu liel\u0101s probl\u0113mas.<\/em>.<\/p>\n\n\n\n<p>Par to past\u0101st\u012bsim s\u012bk\u0101k.<\/p>\n\n\n\n<p>Pils\u0113tvides skait\u013co\u0161ana ietver lielu un neviendab\u012bgu datu, kas ieg\u016bti no da\u017e\u0101diem avotiem pils\u0113tvid\u0113, ieguves, integr\u0101cijas un anal\u012bzes procesu. \u0160\u0101di datu avoti ietver sensorus, mobil\u0101s ier\u012bces, transportl\u012bdzek\u013cus, \u0113kas un cilv\u0113kus.<\/p>\n\n\n\n<p class=\"has-large-font-size\"><strong>Kas ir pils\u0113tas skait\u013co\u0161ana?<\/strong><\/p>\n\n\n\n<p>Dokument\u0101 ar nosaukumu \"<a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/2629592\">Urb\u0101n\u0101 skait\u013co\u0161ana: koncepcijas, metodolo\u0123ijas un lietojumi<\/a>\" autori iepaz\u012bstina ar visp\u0101r\u0113ju sist\u0113mu, k\u0101 \u012bstenot pils\u0113tu skait\u013co\u0161anas sist\u0113mu.<\/p>\n\n\n\n<p>Urb\u0101n\u0101 skait\u013co\u0161ana apvieno neintrus\u012bvas un visur kl\u0101teso\u0161as uztver\u0161anas tehnolo\u0123ijas, progres\u012bvu datu p\u0101rvald\u012bbu, anal\u012btiskos mode\u013cus un jaunas vizualiz\u0101cijas metodes, lai rad\u012btu risin\u0101jumus, kas uzlabo pils\u0113tvidi, cilv\u0113ku dz\u012bves kvalit\u0101ti un pils\u0113tas darb\u012bbas sist\u0113mas.<\/p>\n\n\n\n<p>J\u0101uzsver ar\u012b tas, ka pils\u0113tu skait\u013co\u0161ana ir starpdisciplin\u0101ra joma. T\u0101 integr\u0113 skait\u013co\u0161anas zin\u0101tni ar cit\u0101m jom\u0101m, piem\u0113ram, transportu, in\u017eeniertehniku, ekonomiku, ekolo\u0123iju un sociolo\u0123iju pils\u0113tvides kontekst\u0101.<\/p>\n\n\n\n<p>Iesp\u0113jams, ka j\u016bsu pr\u0101t\u0101 \u0161obr\u012bd ir \u0161\u0101ds jaut\u0101jums: k\u0101 ieviest urb\u0101no skait\u013co\u0161anu, lai p\u0101rvar\u0113tu lielo pils\u0113tu probl\u0113mas?<\/p>\n\n\n\n<p>Labas zi\u0146as - tam ir izstr\u0101d\u0101ta sist\u0113ma!<\/p>\n\n\n\n<p class=\"has-large-font-size\"><strong>Pils\u0113tas skait\u013co\u0161anas sist\u0113ma<\/strong><\/p>\n\n\n\n<p>Dokument\u0101 ar nosaukumu \"<a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/2629592\">Urb\u0101n\u0101 skait\u013co\u0161ana: koncepcijas, metodolo\u0123ijas un lietojumi<\/a>\" autori iepaz\u012bstina ar visp\u0101r\u0113ju sist\u0113mu, k\u0101 \u012bstenot pils\u0113tu skait\u013co\u0161anas sist\u0113mu.<\/p>\n\n\n\n<p>Sist\u0113mu veido \u010detri sl\u0101\u0146i: Pils\u0113tas uztver\u0161ana, pils\u0113tas datu p\u0101rvald\u012bba, datu anal\u012bze un pakalpojumu snieg\u0161ana. Katram sl\u0101nim ir \u012bpa\u0161a funkcija.<\/p>\n\n\n\n<p>Port\u0101ls <strong>Pils\u0113tu sensori<\/strong> sl\u0101nis ir atbild\u012bgs par datu v\u0101k\u0161anu no pils\u0113tvides. \u0160o datu v\u0101k\u0161anu var veikt, izmantojot da\u017e\u0101das metodes, piem\u0113ram, l\u012bdzdal\u012bbas uztver\u0161anu, p\u016b\u013ca uztver\u0161anu un mobilo uztver\u0161anu.<\/p>\n\n\n\n<p>Port\u0101ls <strong>Pils\u0113tu datu p\u0101rvald\u012bba<\/strong> sl\u0101nis \u013cauj organiz\u0113t datus, izmantojot indeks\u0113\u0161anas strukt\u016bru, kas ietver gan telpisko un laika inform\u0101ciju, gan tekstus, lai atbalst\u012btu efekt\u012bvu datu anal\u012bzi.<\/p>\n\n\n\n<p>In the<strong> Datu anal\u012bzes sl\u0101nis<\/strong>, da\u017e\u0101das metodes, piem\u0113ram. <a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_mining\">Datu ieguve<\/a>, <a href=\"https:\/\/en.wikipedia.org\/wiki\/Machine_learning\">Ma\u0161\u012bnm\u0101c\u012b\u0161an\u0101s<\/a>, un <a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_visualization\">Datu vizualiz\u0101cija<\/a> tiek izmantoti, lai identific\u0113tu likumsakar\u012bbas datos un ieg\u016btu no tiem v\u0113rt\u012bgu inform\u0101ciju turpm\u0101ku l\u0113mumu pie\u0146em\u0161anai.<\/p>\n\n\n\n<p>Port\u0101ls <strong>Pakalpojumu snieg\u0161ana<\/strong> sl\u0101nis ietver da\u017e\u0101dus risin\u0101jumus un pakalpojumus, kuru m\u0113r\u0137is ir uzlabot cilv\u0113ku brauk\u0161anas pieredzi, samazin\u0101t satiksmes sastr\u0113gumus, gaisa pies\u0101r\u0146ojumu un ener\u0123ijas pat\u0113ri\u0146u.  Piem\u0113ram, ja tiek konstat\u0113ta k\u0101da satiksmes anom\u0101lija, \u0161\u012b inform\u0101cija tiek nos\u016bt\u012bta transporta iest\u0101dei, lai t\u0101 var\u0113tu izklied\u0113t satiksmi un diagnostic\u0113t anom\u0101liju.<\/p>\n\n\n\n<p class=\"has-large-font-size\"><strong>Ar k\u0101diem izaicin\u0101jumiem saskaras pils\u0113tu skait\u013co\u0161ana?<\/strong><\/p>\n\n\n\n<p>Ide\u0101lai \u012bsteno\u0161anai pils\u0113tvides skait\u013co\u0161anas sist\u0113ma saskaras ar trim lieliem izaicin\u0101jumiem: <\/p>\n\n\n\n<p class=\"has-medium-font-size\">1.<strong>Uztver\u0161ana un datu ieg\u016b\u0161ana.<\/strong><\/p>\n\n\n\n<p>\u0160is uzdevums ir par to, k\u0101 neintrus\u012bvi un nep\u0101rtraukti v\u0101kt datus par pils\u0113tu, \u0146emot v\u0113r\u0101 pils\u0113t\u0101 izvietoto sensoru skaita ierobe\u017eojumus.&nbsp;<\/p>\n\n\n\n<p>M\u0113r\u0137i var\u0113tu sasniegt ar jaunu sensoru infrastrukt\u016bru izb\u016bvi, tom\u0113r tas palielin\u0101tu pils\u0113tu slogu.<\/p>\n\n\n\n<p>Cilv\u0113ks k\u0101 sensors ir jauns j\u0113dziens, kas var pal\u012bdz\u0113t risin\u0101t \u0161o probl\u0113mu, izmantojot vi\u0146a ierakstus soci\u0101lajos t\u012bklos vai GPS p\u0113das, lai saprastu apk\u0101rt notieko\u0161o.<\/p>\n\n\n\n<p>Cilv\u0113ki k\u0101 sensors rada jaunus izaicin\u0101jumus, piem\u0113ram:<\/p>\n\n\n\n<ul><li>Palielin\u0101s ier\u012b\u010du ener\u0123ijas izmanto\u0161ana;<\/li><li>Personas inform\u0101cijas konfidencialit\u0101te;<\/li><li>Neobjekt\u012bvi dati, jo lietot\u0101ji nav vienm\u0113r\u012bgi sadal\u012bti un nes\u016bta sensoru r\u0101d\u012bjumus ar vien\u0101du bie\u017eumu;<\/li><li>Nestruktur\u0113ti, netie\u0161i un trok\u0161\u0146aini dati, ko sniedz lietot\u0101ji. Turpret\u012b tradicion\u0101lo sensoru rad\u012btie dati ir labi struktur\u0113ti, skaidri, t\u012bri un viegli saprotami.&nbsp;<\/li><\/ul>\n\n\n\n<p class=\"has-medium-font-size\">2. <strong>Heterog\u0113ni dati.<\/strong><\/p>\n\n\n\n<p>Datu ieguves un ma\u0161\u012bnm\u0101c\u012b\u0161an\u0101s metodes parasti apstr\u0101d\u0101 viena veida datus. Tom\u0113r pils\u0113tvides probl\u0113mu risin\u0101\u0161ana ietver pla\u0161u faktoru kl\u0101stu (piem\u0113ram, gaisa pies\u0101r\u0146ojuma izp\u0113te ietver vienlaic\u012bgu satiksmes pl\u016bsmas, meteorolo\u0123ijas un zemes izmanto\u0161anas izp\u0113ti).<\/p>\n\n\n\n<p class=\"has-medium-font-size\">3. <strong>Hibr\u012bd\u0101s sist\u0113mas.<\/strong><\/p>\n\n\n\n<p>At\u0161\u0137ir\u012bb\u0101 no mekl\u0113t\u0101jprogrammas vai digit\u0101l\u0101s sp\u0113les, kur dati tiek \u0123ener\u0113ti un pat\u0113r\u0113ti digit\u0101laj\u0101 pasaul\u0113, pils\u0113tvides skait\u013co\u0161ana parasti integr\u0113 abu pasau\u013cu datus (apvienojot datpl\u016bsmu un soci\u0101los medijus).<\/p>\n\n\n\n<p>Hibr\u012bdsist\u0113mu projekt\u0113\u0161ana ir daudz sare\u017e\u0123\u012bt\u0101ka nek\u0101 parasto sist\u0113mu projekt\u0113\u0161ana, jo sist\u0113mai vienlaikus j\u0101sazin\u0101s ar daudz\u0101m ier\u012bc\u0113m un lietot\u0101jiem un j\u0101s\u016bta un j\u0101sa\u0146em da\u017e\u0101da form\u0101ta dati.<\/p>\n\n\n\n<p class=\"has-large-font-size\"><strong>K\u0101di ir galvenie urb\u0101n\u0101s skait\u013co\u0161anas lietojumi?<\/strong><\/p>\n\n\n\n<p>Urb\u0101n\u0101s skait\u013co\u0161anas lietojumi var\u0113tu b\u016bt neskait\u0101mi.<\/p>\n\n\n\n<p>Pielietojumus var iedal\u012bt septi\u0146\u0101s kategorij\u0101s: pils\u0113tpl\u0101no\u0161ana, transports, vide, sabiedr\u012bbas dro\u0161\u012bba un aizsardz\u012bba, ener\u0123\u0113tika, ekonomika, ekolo\u0123ija un soci\u0101l\u0101 joma.<\/p>\n\n\n\n<p>\u0160eit sniegts \u012bss apraksts par katru no tiem:<\/p>\n\n\n\n<ul><li><strong>Pils\u0113tpl\u0101no\u0161ana<\/strong>.&nbsp;<\/li><\/ul>\n\n\n\n<p>Pl\u0101no\u0161ana ir svar\u012bga viedo pils\u0113tu veido\u0161an\u0101. \u0160aj\u0101 kategorij\u0101 ietilpst pamatprobl\u0113mu atkl\u0101\u0161ana transporta t\u012bklos, funkcion\u0101lo re\u0123ionu atkl\u0101\u0161ana pils\u0113t\u0101 (piem\u0113ram, teritorijas, kas nodro\u0161ina da\u017e\u0101das cilv\u0113ku vajadz\u012bbas un kalpo k\u0101 organiz\u0113\u0161anas pa\u0146\u0113miens, piem\u0113ram, izgl\u012bt\u012bbas jomas vai uz\u0146\u0113m\u0113jdarb\u012bbas rajoni) un pils\u0113tas robe\u017eu noteik\u0161ana, lai izprastu t\u0101s att\u012bst\u012bbu.<\/p>\n\n\n\n<ul><li><strong>Transports.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>\u0160aj\u0101 kategorij\u0101 ietilpst: brauk\u0161anas pieredzes uzlabo\u0161ana, taksometru pakalpojumi un sabiedrisk\u0101 transporta sist\u0113mas.<\/p>\n\n\n\n<ul><li><strong>Vide.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>Urbaniz\u0101cijas strauj\u0101 att\u012bst\u012bba k\u013c\u016bs par potenci\u0101lu apdraud\u0113jumu pils\u0113tu videi. Pils\u0113tu vides skait\u013co\u0161ana ietver gaisa kvalit\u0101tes uzlabo\u0161anu pils\u0113t\u0101s un trok\u0161\u0146a pies\u0101r\u0146ojuma samazin\u0101\u0161anu.<\/p>\n\n\n\n<ul><li><strong>Sabiedrisk\u0101 dro\u0161\u012bba un aizsardz\u012bba.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>\u0160eit var min\u0113t \u0161\u0101dus lietojumus: satiksmes anom\u0101liju atkl\u0101\u0161ana, katastrofu atkl\u0101\u0161ana un negad\u012bjumu atkl\u0101\u0161ana.<\/p>\n\n\n\n<ul><li><strong>Ener\u0123ijas pat\u0113ri\u0146\u0161.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>Strauj\u0101 urbaniz\u0101cijas att\u012bst\u012bba pat\u0113r\u0113 arvien vair\u0101k ener\u0123ijas. \u0160\u012bs kategorijas lietojumi ir g\u0101zes un elektr\u012bbas pat\u0113ri\u0146a samazin\u0101\u0161ana.<\/p>\n\n\n\n<ul><li><strong>Ekonomika.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>Pils\u0113tas dinamika var nor\u0101d\u012bt uz pils\u0113tas ekonomikas tendenc\u0113m. \u0160\u012bs kategorijas pielietojuma piem\u0113rs ir akciju tirgus tenden\u010du prognoz\u0113\u0161ana.<\/p>\n\n\n\n<ul><li><strong>Soci\u0101l\u0101s jomas.<\/strong><\/li><\/ul>\n\n\n\n<p>\u0160\u012bs kategorijas lietojumprogrammas ir atra\u0161an\u0101s vietas ieteikumi, mar\u0161rutu pl\u0101no\u0161ana, atra\u0161an\u0101s vietas un aktivit\u0101\u0161u ieteik\u0161ana, k\u0101 ar\u012b pils\u0113tas dinamikas izpratne.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/preview-348518.png\"><img decoding=\"async\" loading=\"lazy\" width=\"1024\" height=\"768\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/preview-348518-1024x768.png\" alt=\"za\u013c\u0101 pils\u0113ta\" class=\"wp-image-13003\" srcset=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/preview-348518-1024x768.png 1024w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/preview-348518-300x225.png 300w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/preview-348518-768x576.png 768w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/preview-348518-1536x1152.png 1536w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/preview-348518-2048x1536.png 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n\n\n\n<p class=\"has-large-font-size\"><strong>Vai ir k\u0101das tehnolo\u0123ijas, kas \u013cauj izmantot pils\u0113tvides skait\u013co\u0161anu?<\/strong><\/p>\n\n\n\n<p>Ir vair\u0101kas pils\u0113tvides skait\u013co\u0161anas pamattehnolo\u0123ijas, kas ir sagrup\u0113tas kategorij\u0101s. Bie\u017e\u0101k izmantot\u0101s kategorijas ir \u0161\u0101das:&nbsp;<\/p>\n\n\n\n<p>Pils\u0113tu sensoru metodes. Tradicion\u0101l\u0101 uztver\u0161ana un m\u0113r\u012b\u0161ana, uzst\u0101dot sensorus, pas\u012bv\u0101 p\u016b\u013ca uztver\u0161ana, kas izmanto eso\u0161o infrastrukt\u016bru, lai apkopotu p\u016b\u013ca rad\u012btos datus, un l\u012bdzdal\u012bbas uztver\u0161ana, kad cilv\u0113ki akt\u012bvi pal\u012bdz ieg\u016bt inform\u0101ciju, kas vi\u0146iem ir apk\u0101rt;<\/p>\n\n\n\n<p>Pils\u0113tu datu p\u0101rvald\u012bbas metodes \u013cauj organiz\u0113t vair\u0101kus heterog\u0113nus datu avotus turpm\u0101kajam datu ieguves procesam;<\/p>\n\n\n\n<p>Zin\u0101\u0161anu apvieno\u0161anas metodes \u013cauj efekt\u012bvi apvienot zin\u0101\u0161anas, kas ieg\u016btas no vair\u0101kiem heterog\u0113niem datu avotiem;<\/p>\n\n\n\n<p>Pils\u0113tvides datu vizualiz\u0101cijas metod\u0113m ne tikai j\u0101att\u0113lo neapstr\u0101d\u0101ti dati un j\u0101sniedz rezult\u0101ti, bet ar\u012b j\u0101\u013cauj atkl\u0101t un aprakst\u012bt datu mode\u013cus, tendences un attiec\u012bbas.<\/p>\n\n\n\n<p>K\u0101 redzat, pils\u0113tvides skait\u013co\u0161ana var b\u016bt \u013coti noder\u012bgs instruments, lai risin\u0101tu galven\u0101s m\u016bsdienu pils\u0113tu probl\u0113mas.<\/p>\n\n\n\n<p>Izaicin\u0101jumi, ar kuriem saskaras pils\u0113tu skait\u013co\u0161ana, galu gal\u0101 tiks p\u0101rvar\u0113ti, t\u0101d\u0113j\u0101di \u013caujot mums nodro\u0161in\u0101t lab\u0101ku n\u0101kotni m\u016bsu pils\u0113t\u0101m.<\/p>\n\n\n\n<p><strong>Atsauces<\/strong><\/p>\n\n\n\n<p><a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/2629592\">Zheng, Y., Capra, L., Wolfson, O., &amp; Yang, H. (2014). Urb\u0101n\u0101 skait\u013co\u0161ana: koncepcijas, metodolo\u0123ijas un lietojumi. <em>ACM Transactions on Intelligent Systems and Technology (TIST)<\/em>, <em>5<\/em>(3), 1-55.<\/a><\/p>\n\n\n\n<p>T.  Kindberg, M. Chalmers un E. Paulos.  2007.  Viesredaktoru ievads:  Urban computing. Pervasive Computing 6, 3, 18-20.<\/p>\n\n\n\n<p><a href=\"https:\/\/ideas.repec.org\/a\/igg\/jksr00\/v7y2016i1p113-119.html\">Torres-Ruiz, Miguel &amp; Lytras, Miltiadis. (2016). Pils\u0113tu skait\u013co\u0161anas un viedo pils\u0113tu lietojumprogrammas zin\u0101\u0161anu sabiedr\u012bbai. International Journal of Knowledge Society Research. 7. 113-119. 10.4018\/IJKSR.2016010108.<\/a><\/p>\n\n\n\n<p>Noklik\u0161\u0137iniet uz zem\u0101k redzam\u0101 att\u0113la, lai apskat\u012btu m\u016bsu Mind the Graph pils\u0113tas skait\u013co\u0161anas ilustr\u0101cijas.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large\"><a href=\"https:\/\/mindthegraph.com\/app\/illustrations?search=urban%20computing\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" loading=\"lazy\" width=\"1024\" height=\"643\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/image-1-1024x643.png\" alt=\"\" class=\"wp-image-13046\" srcset=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/image-1-1024x643.png 1024w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/image-1-300x188.png 300w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/image-1-768x482.png 768w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2021\/06\/image-1.png 1286w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure><\/div>\n\n\n\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>M\u016bsdien\u0101s liel\u0101s pils\u0113tas saskaras ar liel\u0101m probl\u0113m\u0101m, piem\u0113ram, satiksmes sastr\u0113gumiem, gaisa pies\u0101r\u0146ojumu un ener\u0123ijas pat\u0113ri\u0146u. \u0160\u012bs lielpils\u0113tu liel\u0101s probl\u0113mas var risin\u0101t, izmantojot lielos datus (kas noz\u012bm\u0113 lielu datu apjomu apstr\u0101di). Tie\u0161i t\u0101 ir pils\u0113tvides skait\u013co\u0161ana. Vienk\u0101r\u0161i to var defin\u0113t k\u0101 lielo datu izmanto\u0161anu, lai [...]<\/p>","protected":false},"author":18,"featured_media":13002,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[959,28],"tags":[554,250],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Urban Computing Challenges in Big Cities<\/title>\n<meta name=\"description\" content=\"Urban Computing gathers a large amount of data with the purpose to create solutions that improve the big cities&#039; environment and human life quality.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mindthegraph.com\/blog\/lv\/pilsetvides-skaitlosanas-problemas-lielajas-pilsetas\/\" \/>\n<meta property=\"og:locale\" content=\"lv_LV\" \/>\n<meta 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