{"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\/da\/computerudfordringer-i-storbyerne\/","title":{"rendered":"Urban Computing: De store udfordringer i de store byer"},"content":{"rendered":"<p>Nu om dage st\u00e5r storbyer over for store problemer som trafikpropper, luftforurening og energiforbrug. Disse store problemer i storbyer kan tackles ved at bruge <a href=\"https:\/\/en.wikipedia.org\/wiki\/Big_data\"><strong>Big data<\/strong><\/a> (hvilket betyder behandling af store datam\u00e6ngder).<\/p>\n\n\n\n<p>Det er pr\u00e6cis, hvad urban computing er. Det kan ganske enkelt defineres som <em>brugen af big data til at h\u00e5ndtere de store problemer i storbyer<\/em>.<\/p>\n\n\n\n<p>Lad os uddybe det lidt mere.<\/p>\n\n\n\n<p>Urban Computing involverer en proces med indsamling, integration og analyse af store og heterogene data, der genereres af forskellige kilder i byrummet. S\u00e5danne datakilder omfatter sensorer, mobile enheder, k\u00f8ret\u00f8jer, bygninger og mennesker.<\/p>\n\n\n\n<p class=\"has-large-font-size\"><strong>Hvad er urban computing?<\/strong><\/p>\n\n\n\n<p>I artiklen med titlen \"<a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/2629592\">Urban computing: koncepter, metodologier og anvendelser<\/a>\", introducerer forfatterne en generel ramme for implementering af Urban Computing.<\/p>\n\n\n\n<p>Urban Computing forbinder ikke-p\u00e5tr\u00e6ngende og allestedsn\u00e6rv\u00e6rende sensorteknologier, avanceret datah\u00e5ndtering, analytiske modeller og nye visualiseringsmetoder for at skabe l\u00f8sninger, der forbedrer bymilj\u00f8et, menneskers livskvalitet og byernes driftssystemer.<\/p>\n\n\n\n<p>Vi m\u00e5 ogs\u00e5 fremh\u00e6ve, at Urban Computing er et tv\u00e6rfagligt felt. Det integrerer computervidenskab med andre omr\u00e5der som transport, civilingeni\u00f8r, \u00f8konomi, \u00f8kologi og sociologi i forbindelse med byrum.<\/p>\n\n\n\n<p>Det store sp\u00f8rgsm\u00e5l, der sp\u00f8ger i dit hoved, er sikkert: Hvordan implementerer man urban computing for at l\u00f8se storbyernes problemer?<\/p>\n\n\n\n<p>Godt nyt, der findes en ramme for det!<\/p>\n\n\n\n<p class=\"has-large-font-size\"><strong>Rammev\u00e6rk for urban computing<\/strong><\/p>\n\n\n\n<p>I artiklen med titlen \"<a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/2629592\">Urban computing: koncepter, metodologier og anvendelser<\/a>\", introducerer forfatterne en generel ramme for implementering af Urban Computing.<\/p>\n\n\n\n<p>Frameworket er sammensat af fire lag: Urban Sensing, Urban Data Management, Data Analytics og Service Providing. Hvert lag har en specifik funktion.<\/p>\n\n\n\n<p>Den <strong>Urban sensing<\/strong> lag har ansvaret for at indsamle data fra byrummet. Denne dataindsamling kan udf\u00f8res ved hj\u00e6lp af forskellige teknikker som participatory sensing, crowdsensing og mobile sensing.<\/p>\n\n\n\n<p>Den <strong>Forvaltning af bydata<\/strong> laget g\u00f8r det muligt at organisere data ved hj\u00e6lp af en indekseringsstruktur, der inkorporerer b\u00e5de spatio-temporal information og tekster for at underst\u00f8tte effektiv dataanalyse.<\/p>\n\n\n\n<p>I den<strong> Lag til dataanalyse<\/strong>, forskellige teknikker som f.eks. <a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_mining\">Datamining<\/a>, <a href=\"https:\/\/en.wikipedia.org\/wiki\/Machine_learning\">Maskinl\u00e6ring<\/a>, og <a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_visualization\">Datavisualisering<\/a> bruges til at identificere m\u00f8nstre i data og f\u00e5 v\u00e6rdifuld information fra dem til efterf\u00f8lgende beslutningstagning.<\/p>\n\n\n\n<p>Den <strong>Levering af tjenester<\/strong> omfatter forskellige l\u00f8sninger og tjenester, der har til form\u00e5l at forbedre folks k\u00f8reoplevelser, reducere trafikpropper, luftforurening og energiforbrug.  Hvis der f.eks. opdages en trafikanomali, vil denne information blive leveret til transportmyndighederne, s\u00e5 de kan sprede trafikken og diagnosticere anomalien.<\/p>\n\n\n\n<p class=\"has-large-font-size\"><strong>S\u00e5 hvilke udfordringer st\u00e5r Urban Computing over for?<\/strong><\/p>\n\n\n\n<p>For en ideel implementering st\u00e5r Urban Computing over for tre store udfordringer: <\/p>\n\n\n\n<p class=\"has-medium-font-size\">1.<strong>Sensing og dataindsamling.<\/strong><\/p>\n\n\n\n<p>Denne udfordring handler om, hvordan man indsamler bydata p\u00e5 en ikke-p\u00e5tr\u00e6ngende og kontinuerlig m\u00e5de i betragtning af begr\u00e6nsningerne i antallet af sensorer fordelt i byen.&nbsp;<\/p>\n\n\n\n<p>Opbygning af nye sensorinfrastrukturer kunne n\u00e5 m\u00e5let, men det ville \u00f8ge byrden for byerne.<\/p>\n\n\n\n<p>Mennesker som sensor er et nyt koncept, der kan hj\u00e6lpe med at tackle denne udfordring ved at bruge deres indl\u00e6g p\u00e5 sociale medier eller deres GPS-spor til at forst\u00e5 de begivenheder, der sker omkring dem.<\/p>\n\n\n\n<p>Mennesket som sensor giver nye udfordringer som f.eks:<\/p>\n\n\n\n<ul><li>Stigende brug af enheder energi;<\/li><li>Beskyttelse af personlige oplysninger;<\/li><li>Sk\u00e6vvredne data, da brugerne ikke er ensartet fordelt, og de ikke sender sensorm\u00e5linger med samme frekvens;<\/li><li>Ustrukturerede, implicitte og st\u00f8jende data, som brugerne bidrager med. I mods\u00e6tning hertil er de data, der genereres af traditionelle sensorer, velstrukturerede, eksplicitte, rene og lette at forst\u00e5.&nbsp;<\/li><\/ul>\n\n\n\n<p class=\"has-medium-font-size\">2. <strong>Heterogene data.<\/strong><\/p>\n\n\n\n<p>Data Mining og Machine Learning-teknikker h\u00e5ndterer normalt \u00e9n slags data. Men at l\u00f8se bym\u00e6ssige udfordringer involverer en bred vifte af faktorer (for eksempel involverer udforskning af luftforurening samtidig unders\u00f8gelse af trafikflow, meteorologi og arealanvendelse).<\/p>\n\n\n\n<p class=\"has-medium-font-size\">3. <strong>Hybride systemer.<\/strong><\/p>\n\n\n\n<p>I mods\u00e6tning til en s\u00f8gemaskine eller et digitalt spil, hvor data genereres og forbruges i den digitale verden, integrerer urban computing normalt data fra begge verdener (ved at kombinere trafik med sociale medier).<\/p>\n\n\n\n<p>Designet af hybride systemer er meget mere udfordrende end for konventionelle systemer, da systemet skal kommunikere med mange enheder og brugere p\u00e5 samme tid og sende og modtage data i forskellige formater.<\/p>\n\n\n\n<p class=\"has-large-font-size\"><strong>Hvad er de vigtigste anvendelser af Urban Computing?<\/strong><\/p>\n\n\n\n<p>Anvendelsesmulighederne for Urban Computing kan v\u00e6re utallige.<\/p>\n\n\n\n<p>Anvendelserne kan grupperes i syv kategorier: byplanl\u00e6gning, transport, milj\u00f8, offentlig sikkerhed, energi, \u00f8konomi, \u00f8kologi og det sociale.<\/p>\n\n\n\n<p>Her er en meget kort beskrivelse af hver enkelt af dem:<\/p>\n\n\n\n<ul><li><strong>Byplanl\u00e6gning<\/strong>.&nbsp;<\/li><\/ul>\n\n\n\n<p>Planl\u00e6gning er vigtig for opbygningen af smarte byer. Denne kategori omfatter opdagelse af underliggende problemer i transportnetv\u00e6rk, opdagelse af funktionelle regioner i en by (s\u00e5som omr\u00e5der, der underst\u00f8tter forskellige behov hos mennesker og fungerer som en organiseringsteknik s\u00e5som uddannelsesomr\u00e5der eller forretningsdistrikter) og opdagelse af byens gr\u00e6nser for at forst\u00e5 dens udvikling.<\/p>\n\n\n\n<ul><li><strong>Transport.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>Denne kategori omfatter: forbedring af k\u00f8reoplevelsen, taxitjenester og offentlige transportsystemer.<\/p>\n\n\n\n<ul><li><strong>Milj\u00f8.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>Urbaniseringens hurtige fremskridt vil blive en potentiel trussel mod byernes milj\u00f8. Urban computing for milj\u00f8et omfatter: forbedring af luftkvaliteten i byerne og reduktion af st\u00f8jforurening.<\/p>\n\n\n\n<ul><li><strong>Offentlig sikkerhed og tryghed.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>Her kan vi n\u00e6vne f\u00f8lgende anvendelser: detektering af trafikanomalier, detektering af katastrofer og detektering af ulykker.<\/p>\n\n\n\n<ul><li><strong>Energiforbrug.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>Den hurtige udvikling i urbaniseringen forbruger mere og mere energi. Anvendelser i denne kategori er reduktion af gas- og elforbrug.<\/p>\n\n\n\n<ul><li><strong>\u00d8konomi.<\/strong>&nbsp;<\/li><\/ul>\n\n\n\n<p>Dynamikken i en by kan indikere tendensen i byens \u00f8konomi. Et eksempel p\u00e5 anvendelse i denne kategori er forudsigelse af udviklingen p\u00e5 et aktiemarked.<\/p>\n\n\n\n<ul><li><strong>Social.<\/strong><\/li><\/ul>\n\n\n\n<p>Anvendelser i denne kategori er lokationsanbefalinger, rejseplanl\u00e6gning, lokations- og aktivitetsanbefalinger og forst\u00e5else af byens dynamik.<\/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=\"gr\u00f8n by\" 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>Er der nogle teknologier, der kan muligg\u00f8re Urban Computing?<\/strong><\/p>\n\n\n\n<p>Der findes flere teknologier til Urban Computing, som er grupperet i kategorier. De hyppigst anvendte kategorier er:&nbsp;<\/p>\n\n\n\n<p>Urban sensing-teknikker. Traditionel sensing og m\u00e5ling gennem installation af sensorer, passiv crowd sensing, der bruger eksisterende infrastruktur til at indsamle data genereret af menneskem\u00e6ngder, og participatory sensing, hvor folk aktivt bidrager med information omkring dem;<\/p>\n\n\n\n<p>Urban Data Management-teknikker g\u00f8r det muligt at organisere flere heterogene datakilder til den efterf\u00f8lgende Data Mining-proces;<\/p>\n\n\n\n<p>Teknikker til vidensfusion g\u00f8r det muligt effektivt at fusionere viden fra flere heterogene datakilder;<\/p>\n\n\n\n<p>Visualiseringsteknikker til bydata skal ikke kun vise r\u00e5data og pr\u00e6sentere resultater, men de skal ogs\u00e5 g\u00f8re det muligt at opdage og beskrive m\u00f8nstre, tendenser og relationer i data.<\/p>\n\n\n\n<p>Som du kan se, kan Urban Computing v\u00e6re et meget nyttigt v\u00e6rkt\u00f8j til at l\u00f8se de store problemer i moderne byer.<\/p>\n\n\n\n<p>De udfordringer, som Urban Computing st\u00e5r over for, vil i sidste ende blive overvundet, s\u00e5 vi kan f\u00e5 en bedre fremtid for vores byer.<\/p>\n\n\n\n<p><strong>Referencer<\/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). Urban computing: koncepter, metodologier og applikationer. <em>ACM Transactions om intelligente systemer og teknologi (TIST)<\/em>, <em>5<\/em>(3), 1-55.<\/a><\/p>\n\n\n\n<p>T.  Kindberg, M. Chalmers og E. Paulos.  2007.  G\u00e6steredakt\u00f8rernes introduktion:  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). Urban Computing og Smart Cities-applikationer til videnssamfundet. International Journal of Knowledge Society Research. 7. 113-119. 10.4018\/IJKSR.2016010108.<\/a><\/p>\n\n\n\n<p>Klik p\u00e5 billedet nedenfor for at se vores Mind the Graph for urban computing-illustrationer.<\/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>I dag st\u00e5r storbyer over for store problemer som trafikpropper, luftforurening og energiforbrug. Disse store problemer i storbyer kan tackles ved hj\u00e6lp af big data (hvilket betyder behandling af store m\u00e6ngder data). Det er pr\u00e6cis, hvad urban computing er. Det kan ganske enkelt defineres som brugen af big data til at [...]<\/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\/da\/computerudfordringer-i-storbyerne\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta 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