{"id":"https://openalex.org/W4410697714","doi":"https://doi.org/10.1051/shsconf/202521601024","title":"AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction","display_name":"AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410697714","doi":"https://doi.org/10.1051/shsconf/202521601024"},"language":"en","primary_location":{"id":"doi:10.1051/shsconf/202521601024","doi":"https://doi.org/10.1051/shsconf/202521601024","is_oa":true,"landing_page_url":"https://doi.org/10.1051/shsconf/202521601024","pdf_url":"https://www.shs-conferences.org/articles/shsconf/pdf/2025/07/shsconf_iciaites2025_01024.pdf","source":{"id":"https://openalex.org/S4210202797","display_name":"SHS Web of Conferences","issn_l":"2261-2424","issn":["2261-2424","2416-5182"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319748","host_organization_name":"EDP Sciences","host_organization_lineage":["https://openalex.org/P4310319748","https://openalex.org/P4310319982"],"host_organization_lineage_names":["EDP Sciences","Science Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SHS Web of Conferences","raw_type":"journal-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.shs-conferences.org/articles/shsconf/pdf/2025/07/shsconf_iciaites2025_01024.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122389966","display_name":"Priya Vij","orcid":"https://orcid.org/0009-0005-4629-3413","observed_orcids":["https://orcid.org/0009-0005-4629-3413"]},"institutions":[{"id":"https://openalex.org/I2800614057","display_name":"Kalinga University","ror":"https://ror.org/03afg5j45","country_code":"IN","type":"education","lineage":["https://openalex.org/I2800614057"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Priya Vij","raw_affiliation_strings":["Department of CS & IT, Kalinga University, Raipur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CS & IT, Kalinga University, Raipur, India","institution_ids":["https://openalex.org/I2800614057"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076768486","display_name":"Ankita Tiwari","orcid":"https://orcid.org/0000-0001-6433-7831","observed_orcids":["https://orcid.org/0000-0001-6433-7831","https://orcid.org/0009-0006-2117-8766"]},"institutions":[{"id":"https://openalex.org/I2800614057","display_name":"Kalinga University","ror":"https://ror.org/03afg5j45","country_code":"IN","type":"education","lineage":["https://openalex.org/I2800614057"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankita Tiwari","raw_affiliation_strings":["Research Scholar, Department of CS & IT, Kalinga University, Raipur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Scholar, Department of CS & IT, Kalinga University, Raipur, India","institution_ids":["https://openalex.org/I2800614057"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800614057"],"apc_list":null,"apc_paid":null,"fwci":7.3664,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.96902107,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"216","issue":null,"first_page":"01024","last_page":"01024"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9779999852180481,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9779999852180481,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.01979999989271164,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drought-monitoring","display_name":"drought monitoring","score":0.9919999837875366},{"id":"https://openalex.org/keywords/drought-forecasting","display_name":"drought forecasting","score":0.7369999885559082},{"id":"https://openalex.org/keywords/early-warning","display_name":"early warning","score":0.621999979019165},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9150000214576721},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":1.0},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"satellite imagery","score":0.859000027179718},{"id":"https://openalex.org/keywords/meteorological-observations","display_name":"meteorological observations","score":0.8650000095367432},{"id":"https://openalex.org/keywords/soil-properties","display_name":"soil properties","score":0.9300000071525574},{"id":"https://openalex.org/keywords/water-resources-management","display_name":"water resources management","score":0.8550000190734863},{"id":"https://openalex.org/keywords/agricultural-planning","display_name":"agricultural planning","score":0.7110000252723694},{"id":"https://openalex.org/keywords/climate-resilience","display_name":"climate resilience","score":0.8740000128746033},{"id":"https://openalex.org/keywords/sustainable-agriculture","display_name":"sustainable agriculture","score":0.6330000162124634},{"id":"https://openalex.org/keywords/real-time-alerts","display_name":"real-time alerts","score":0.6510000228881836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47171729803085327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4677961468696594},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44772839546203613}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1051/shsconf/202521601024","doi":"https://doi.org/10.1051/shsconf/202521601024","is_oa":true,"landing_page_url":"https://doi.org/10.1051/shsconf/202521601024","pdf_url":"https://www.shs-conferences.org/articles/shsconf/pdf/2025/07/shsconf_iciaites2025_01024.pdf","source":{"id":"https://openalex.org/S4210202797","display_name":"SHS Web of Conferences","issn_l":"2261-2424","issn":["2261-2424","2416-5182"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319748","host_organization_name":"EDP Sciences","host_organization_lineage":["https://openalex.org/P4310319748","https://openalex.org/P4310319982"],"host_organization_lineage_names":["EDP Sciences","Science Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SHS Web of Conferences","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1ea234fc692546cc9680d215899a751b","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/1ea234fc692546cc9680d215899a751b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"SHS Web of Conferences, Vol 216, p 01024 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1051/shsconf/202521601024","doi":"https://doi.org/10.1051/shsconf/202521601024","is_oa":true,"landing_page_url":"https://doi.org/10.1051/shsconf/202521601024","pdf_url":"https://www.shs-conferences.org/articles/shsconf/pdf/2025/07/shsconf_iciaites2025_01024.pdf","source":{"id":"https://openalex.org/S4210202797","display_name":"SHS Web of Conferences","issn_l":"2261-2424","issn":["2261-2424","2416-5182"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319748","host_organization_name":"EDP Sciences","host_organization_lineage":["https://openalex.org/P4310319748","https://openalex.org/P4310319982"],"host_organization_lineage_names":["EDP Sciences","Science Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SHS Web of Conferences","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":1.0,"display_name":"Climate action"},{"id":"https://metadata.un.org/sdg/2","score":0.6735000014305115,"display_name":"Zero hunger"},{"id":"https://metadata.un.org/sdg/6","score":0.6618000268936157,"display_name":"Clean water and sanitation"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410697714.pdf","grobid_xml":"https://content.openalex.org/works/W4410697714.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W2039049978","https://openalex.org/W2116632035","https://openalex.org/W2140449910","https://openalex.org/W2801677017","https://openalex.org/W2914732891","https://openalex.org/W3034984396","https://openalex.org/W3127987408","https://openalex.org/W3147559761","https://openalex.org/W3173762788","https://openalex.org/W4225117625","https://openalex.org/W4251031578","https://openalex.org/W4296785401","https://openalex.org/W4312802238","https://openalex.org/W4315647710","https://openalex.org/W4389273790","https://openalex.org/W4389511473","https://openalex.org/W4389752470","https://openalex.org/W4391182560","https://openalex.org/W4401068957"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Amid":[0],"the":[1,112,125,138,150,197,207],"escalating":[2],"impacts":[3],"of":[4,118,142,152,200,210],"climate":[5,156],"change,":[6],"droughts":[7],"are":[8],"becoming":[9],"increasingly":[10],"frequent":[11],"and":[12,17,29,38,49,60,70,79,85,99,108,133,140,155,165,181,205],"severe,":[13],"necessitating":[14],"advanced":[15],"monitoring":[16,59,204],"predictive":[18],"strategies":[19],"to":[20,75,90,123,149,177],"mitigate":[21],"their":[22],"adverse":[23],"effects":[24],"on":[25],"agriculture,":[26],"water":[27,103],"resources,":[28],"ecosystems.":[30],"This":[31,194],"research":[32,113,159],"leverages":[33],"state-of-the-art":[34],"machine":[35,120],"learning":[36,121],"techniques":[37],"an":[39,54],"extensive":[40],"multi-source":[41],"dataset\u2014including":[42],"satellite":[43],"imagery,":[44],"meteorological":[45],"data,":[46],"soil":[47],"characteristics,":[48],"historical":[50],"drought":[51,58,87,143],"records\u2014to":[52],"develop":[53],"AI-driven":[55],"framework":[56,168],"for":[57,129,186],"early":[61],"prediction.":[62],"The":[63,93,158,174],"study":[64,147],"employs":[65],"Convolutional":[66],"Neural":[67,72],"Networks":[68,73],"(CNNs)":[69],"Recurrent":[71],"(RNNs)":[74],"capture":[76],"complex":[77],"spatial":[78],"temporal":[80],"patterns,":[81],"enabling":[82],"more":[83],"accurate":[84],"timely":[86],"forecasting":[88],"compared":[89],"traditional":[91],"approaches.":[92],"proposed":[94],"system":[95],"offers":[96],"real-time":[97],"alerts":[98],"forecasts,":[100],"facilitating":[101],"proactive":[102],"resource":[104],"management,":[105],"agricultural":[106,192],"planning,":[107],"disaster":[109],"preparedness.":[110],"Moreover,":[111],"conducts":[114],"a":[115,162,190],"comparative":[116],"evaluation":[117],"various":[119],"models":[122],"identify":[124],"most":[126],"effective":[127],"algorithms":[128],"different":[130],"climatic":[131],"zones":[132],"crop":[134],"types.":[135],"By":[136],"enhancing":[137],"precision":[139],"reliability":[141],"prediction":[144],"systems,":[145],"this":[146],"contributes":[148],"promotion":[151],"sustainable":[153,211],"agriculture":[154],"resilience.":[157],"culminates":[160],"in":[161,202],"scalable,":[163],"adaptable,":[164],"institutionalized":[166],"AI":[167,201],"that":[169],"addresses":[170],"urgent":[171],"environmental":[172,203,212],"challenges.":[173],"outcomes":[175],"aim":[176],"empower":[178],"policymakers,":[179],"farmers,":[180],"researchers":[182],"with":[183],"data-driven":[184],"insights":[185],"informed":[187],"decision-making,":[188],"fostering":[189],"resilient":[191],"ecosystem.":[193],"work":[195],"underscores":[196],"transformative":[198],"potential":[199],"supports":[206],"broader":[208],"goal":[209],"development.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-09-27T08:07:27.782135","created_date":"2025-10-10T00:00:00"}