Olsem nambawan samting bilong skelim wara risos menesmen, ol wara mita i no save rekodim tasol hamas wara ol i yusim. Stat long taim ol i wokim ol masin wara mita bihain long Indastrial Revolusen long 19 senseri i go inap long taim ol i yusim ol smat wara mita we i gat pawa long IoT teknoloji long 21 senseri, dispela instramen i luk olsem ol nomol samting i bin soim olsem ol manmeri i gat bikpela wok long painim aut yusim bilong ol wara risos long sait bilong saiens. Long nau we saiens na teknoloji i wok bung wantaim, bikpela wok bilong saiens bilong ol mita bilong wara i go bikpela na i karamapim planti samting, olsem wok bilong sekim ol risos, skelim envairomen, na wok bilong bosim ol manmeri, na dispela i kamap olsem wanpela bikpela samting we i save konektim pasin bilong yusim wara long makro-level wantaim ol makro-level wara risos strateji.
As bilong Saiens bilong Stretpela Skelim: Stat long Empirikal Jajmen i go long Kwantitativ Analisis
Taim ol tumbuna agrikalsa sosaiti i dipen long ol wara we i stap long ples, tingting bilong "wara long laik" i bosim pasin bilong yusim wara. Tasol, indastrialisesen na urbanisesen i senisim tru dispela tingting. Taim ol i wokim ol wara mita, long namba wan taim, i givim ol evidens bilong ol manmeri long yusim wara-na ol i yusim ol samting olsem 'impeller rotation', 'piston displacement', o 'electromagnetic induction' long senisim ol wara i ron we yumi no inap lukim i kamap ol dijitel signal we yumi ken ritim. Dispela stretpela skelim inap em i no wanpela teknikel prerekwisit tasol bilong stretim wara bil tasol tu em i as bilong saiens wara risos menesmen. Olsem, long sait bilong yusim wara long haus, ol data bilong wara mita inap helpim ol risetsa long skelim wok bung namel long ol kain kain pasin bilong laipstail (olsem taim bilong waswas na hamas taim ol i save yusim masin bilong wasim klos) na hamas wara ol i save dring. Long level bilong urban plening, skelim ol data bilong ol rijonal masta mita wantaim ol hauslain mita inap long soim ol bikpela indiketa olsem ol paip netwok lik reit na wara efisiensi distribusen.
Ol wok i kamap long 'metrology' bilong nau i helpim moa yet long kamapim gutpela wok bilong skelim wara mita. Intanesenel Rekomendasen R49, we Intanesenel Ogenaisesen bilong Ligel Metroloji (OIML) i kamapim, i tok klia long mak bilong asua we ol i ken mekim long ol wara mita bilong ol haus (planti taim ±2% i go inap ±5%), na ol wara mita bilong laboratori-greid hai-presisen wara mita inap long kamapim ol asua insait long ±0.1%. Dispela stretpela wok i larim ol data bilong wara mita long helpim ol wok painimaut bilong saiens: ol haidrolik enjinia i save yusim ol longpela taim data bilong ron bilong wara long wokim ol model bilong yusim wara long ol taun, ol ekolojis i save yusim skelim bilong ol wara mita insait long wanpela wara long bihainim ol pasin bilong yusim tumas wara aninit long graun, na tu ol risetsa bilong klaimet senis i ken kisim ol evidens long ol samting we i kamap long weta (olsem wara i pundaun wantu tasol long taim bilong draut na ol paip netwok lod i go antap long taim bilong ren ol sisen). Wanpela Frontier long Risos Monitoring na Envairomen Saiens
Long wanem, hevi bilong sot long wara long wol i wok long go antap, ol wara mita i kamap olsem ol bikpela sensa insait long ol envairomen monitoring netwok. Ol smat wara mita i save salim ol ril-taim data long planti samting, olsem ron, presa, na tempereja, na i save givim wanpela hai-resolusen infomesen sos bilong skelim ol wara risos. Olsem, long rot bilong skelim ol senis long data bilong wara mita long wanpela indastrial pak, ol atoriti bilong lukautim envairomen i ken luksave long ol pipia wara we i no stret long lo. Taim ol i skelim ol riding bilong mita namel long ol wara mita bilong wara na ol mita bilong wara i stap daunbilo, dispela inap long skelim hamas wara ol i yusim long wok gaden. Maski long 'transboundary river management', ol kantri antap na daunstrim i ken toktok long kisim wankain raits long wara long rot bilong serim ol mita data long ol ki node.
Moa yet, wok bilong bungim ol data bilong wara mita wantaim ol teknoloji olsem ol 'geographic information systems' (GIS) na 'meteorological satellite remote sensing' i wok long kamapim wanpela nupela tingting long saiens bilong ol wara risos. Ol risetsa i yusim ol 'machine learning algorithms' long prosesim bikpela namba bilong ol data bilong wara mita, na ol i save toksave stret long wanem taim ol manmeri i save yusim planti wara long ol narapela narapela taun eria na stretim gut sediul bilong wara saplai long daunim yusim bilong eneji. Taim ol i bungim wantaim ol data bilong ol 'soil moisture sensor', ol i ken kamapim tu wanpela 'joint surface water-groundwater simulation model bilong givim 'scientific early warning' long 'groundwater levels' we i wok long go daun. Ol dispela aplikesen i no helpim tasol long yusim gut ol wara risos tasol tu i givim teknikel sapot long winim ol global Sastenebel Divelopmen Gol (olsem SDG 6: Klin Wara na Senitesen).
Wanpela Bris Namel long Sosel Gavenens na Saientifik Disisen-Meking
Mining bilong ol wara mita long sait bilong saiens i kamap ples klia tu long strong bilong ol long pasin bilong ol manmeri. Taim ol yusa i ken lukim wara ol i yusim long taim stret long rot bilong ol smat divais, dispela lukluk i ken senisim tru pasin bilong ol long yusim wara. Ol stadi i soim olsem sapos yu putim wanpela wara mita wantaim 'real-time display functionality, dispela inap long daunim wara yu save yusim long olgeta de long 10%-15%. Dispela 'micro-level behavioral intervention' i save senisim ol 'scientific data' i kamap olsem wanpela samting we i save kirapim pablik long insait long en, na i save kamapim wanpela tingting long "save long wara, lukautim wara, na lukautim wara."
Long makro-level, ol data bilong wara mita em i as tingting bilong gavman long wokim ol polisi bilong wara risos. Taim ol i skelim gut yusim bilong wara long ol narapela narapela sekta (olsem indastri, egrikalsa, na sevis), ol lain i mekim disisen i ken putim ol gutpela mak long hamas wara ol i yusim. Taim ol i skelim ol data bilong bipo wantaim ol samting i kamap long populesen, ol i ken plenim ol projek bilong skruim wara saplai pastaim. Maski long ol pablik imejensi (olsem ol paip i bruk na wara i bagarap), ol data alet we i no stret long wara mita netwok inap long givim bekim long wanpela minit-long-minit. Dispela saientifik disisen-meking model, we i kamap long ol empirikel data, i daunim tru ol kos bilong traim-na-error bilong menesim ol wara risos na i strongim strong na sastenebiliti bilong sistem.
Stat long stretpela 'meshing' bilong ol 'mechanical gears' i go inap long 'wireless transmission' bilong ol dijitel signal, ol wara mita i bin stap olsem wanpela tul bilong ol manmeri long painimaut ol tok hait bilong ol wara risos. Moa long wanpela instramen bilong skelim wara i ron, ol i wok olsem wanpela link namel long save bilong saiens na wok bilong mekim. Long rot bilong rekodim stret rot bilong olgeta drop wara, ol wara mita i helpim yumi long kliagut long ol lo bilong nature, stretim gut ol risos alokesen, na kamapim wanpela gutpela sindaun namel long ol manmeri na wara. Long bihain taim, wantaim dip integresen bilong Intenet bilong ol samting, bikpela data, na ol 'artificial intelligence' teknoloji, ol wara mita bai go het long skruim ol saientifik baundri bilong ol na kamap wanpela bikpela intelijen node long sastenebel menesmen bilong ol wara risos long wol.