{"id":"https://openalex.org/W4409342570","doi":"https://doi.org/10.32604/cmc.2025.061954","title":"A UAV Path-Planning Approach for Urban Environmental Event Monitoring","display_name":"A UAV Path-Planning Approach for Urban Environmental Event Monitoring","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409342570","doi":"https://doi.org/10.32604/cmc.2025.061954"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.061954","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061954","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.061954","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037097079","display_name":"Huiru Cao","orcid":"https://orcid.org/0000-0002-0125-6273"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Huiru Cao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011923446","display_name":"Shaoxin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaoxin Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023008238","display_name":"Xiaomin Li","orcid":"https://orcid.org/0000-0001-6083-6510"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaomin Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100765918","display_name":"Yongxin Liu","orcid":"https://orcid.org/0000-0003-1832-9835"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yongxin Liu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037097079"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.3258,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.97031769,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"83","issue":"3","first_page":"5575","last_page":"5593"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9739999771118164,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9739999771118164,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.929099977016449,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9204000234603882,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5439245104789734},{"id":"https://openalex.org/keywords/environmental-planning","display_name":"Environmental planning","score":0.4987645149230957},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.49110886454582214},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4733272194862366},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.43609267473220825},{"id":"https://openalex.org/keywords/environmental-resource-management","display_name":"Environmental resource management","score":0.429935097694397},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4165861904621124},{"id":"https://openalex.org/keywords/urban-planning","display_name":"Urban planning","score":0.41261938214302063},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.34702175855636597},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1750735342502594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1506710946559906},{"id":"https://openalex.org/keywords/civil-engineering","display_name":"Civil engineering","score":0.14666974544525146}],"concepts":[{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5439245104789734},{"id":"https://openalex.org/C91375879","wikidata":"https://www.wikidata.org/wiki/Q15473274","display_name":"Environmental planning","level":1,"score":0.4987645149230957},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.49110886454582214},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4733272194862366},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.43609267473220825},{"id":"https://openalex.org/C107826830","wikidata":"https://www.wikidata.org/wiki/Q929380","display_name":"Environmental resource management","level":1,"score":0.429935097694397},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4165861904621124},{"id":"https://openalex.org/C49545453","wikidata":"https://www.wikidata.org/wiki/Q69883","display_name":"Urban planning","level":2,"score":0.41261938214302063},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.34702175855636597},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1750735342502594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1506710946559906},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.14666974544525146},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.061954","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061954","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.061954","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061954","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5199999809265137},{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1969483458","https://openalex.org/W2013205100","https://openalex.org/W2036868494","https://openalex.org/W2169528473","https://openalex.org/W2503583061","https://openalex.org/W2613927007","https://openalex.org/W2743056029","https://openalex.org/W2792856158","https://openalex.org/W2793263498","https://openalex.org/W2911976185","https://openalex.org/W2977524887","https://openalex.org/W3089893234","https://openalex.org/W3165816055","https://openalex.org/W3200562307","https://openalex.org/W3206795908","https://openalex.org/W3215177902","https://openalex.org/W4280496735","https://openalex.org/W4284894552","https://openalex.org/W4319265558","https://openalex.org/W4388010306","https://openalex.org/W4389321430","https://openalex.org/W4399679443"],"related_works":["https://openalex.org/W3049557657","https://openalex.org/W3150915502","https://openalex.org/W2111158727","https://openalex.org/W2359600231","https://openalex.org/W2380019117","https://openalex.org/W3138952546","https://openalex.org/W1987886368","https://openalex.org/W1660309994","https://openalex.org/W2369187583","https://openalex.org/W3197207153"],"abstract_inverted_index":{"Efficient":[0],"flight":[1,191,272,287],"path":[2,29,58,108,150,166,343],"design":[3],"for":[4,35,106,338],"unmanned":[5],"aerial":[6],"vehicles":[7],"(UAVs)":[8],"in":[9,19,42,210,269,286,303,323,345],"urban":[10,25,86,332,347],"environmental":[11,36,96,130,333],"event":[12],"monitoring":[13,90],"remains":[14],"a":[15,56,78,279,296],"critical":[16],"challenge,":[17],"particularly":[18],"prioritizing":[20],"high-risk":[21],"zones":[22],"within":[23,219,224,230],"complex":[24,346],"landscapes.":[26],"Current":[27],"UAV":[28,138,342],"planning":[30,59,344],"methodologies":[31],"often":[32],"inadequately":[33],"account":[34],"risk":[37,97,127,185,213],"factors":[38],"and":[39,45,110,193,229,240,250,253,274,284,295,301],"exhibit":[40],"limitations":[41],"balancing":[43],"global":[44,107],"local":[46,119,165],"optimization":[47],"efficiency.":[48],"To":[49],"address":[50],"these":[51],"gaps,":[52],"this":[53,177],"study":[54],"proposes":[55],"hybrid":[57],"framework":[60],"integrating":[61],"an":[62,70],"improved":[63,101,122,205],"Ant":[64],"Colony":[65],"Optimization":[66,247,260],"(ACO)":[67],"algorithm":[68,103,113,124,207,249,265],"with":[69,88,142,235],"Orthogonal":[71],"Jump":[72],"Point":[73],"Search":[74],"(OJPS)":[75],"algorithm.":[76,262],"Firstly,":[77],"two-dimensional":[79],"grid":[80],"model":[81],"is":[82,104,114,133,153],"constructed":[83],"to":[84,116,135,139,155,170,290,309,328,331],"simulate":[85],"environments,":[87],"key":[89],"nodes":[91],"selected":[92],"based":[93],"on":[94],"grid-specific":[95],"values.":[98],"Subsequently,":[99],"the":[100,111,118,126,137,140,146,149,156,161,172,175,180,183,188,190,194,203,211,216,220,225,231,244,257,291,304,310,317,320,325,339],"ACO":[102,123,206],"used":[105,134],"planning,":[109],"OJPS":[112,147,264],"integrated":[115],"optimize":[117],"path.":[120],"The":[121,198,263],"introduces":[125],"value":[128,186,214],"of":[129,164,174,182,187,196,215,237,271,276,281,298,306,319,341],"events,":[131,334],"which":[132,159],"direct":[136],"area":[141],"higher":[143],"risk.":[144],"In":[145,168],"algorithm,":[148],"search":[151],"direction":[152],"restricted":[154],"orthogonal":[157],"direction,":[158],"improves":[160],"computational":[162],"efficiency":[163],"optimization.":[167],"order":[169],"evaluate":[171],"performance":[173,268],"model,":[176],"paper":[178],"utilizes":[179],"metrics":[181],"average":[184,212],"path,":[189],"time,":[192],"number":[195,275,305],"turns.":[197],"experimental":[199],"results":[200,315],"demonstrate":[201],"that":[202],"proposed":[204,321],"performs":[208],"well":[209],"paths":[217],"traveled":[218],"first":[221,226,232],"5":[222],"min,":[223,228,234],"8":[227],"10":[233],"improvements":[236],"48.33%,":[238],"26.10%,":[239],"6.746%,":[241],"respectively,":[242,255],"over":[243,256],"Particle":[245],"Swarm":[246],"(PSO)":[248],"70.33%,":[251],"19.08%,":[252],"10.246%,":[254],"Artificial":[258],"Rabbits":[259],"(ARO)":[261],"demonstrates":[266],"superior":[267],"terms":[270],"time":[273,288],"turns,":[277],"exhibiting":[278],"reduction":[280,297],"40%,":[282],"40%":[283],"57.1%":[285],"compared":[289,308],"other":[292,311],"three":[293,312],"algorithms,":[294],"11.1%,":[299],"11.1%":[300],"33.8%":[302],"turns":[307],"algorithms.":[313],"These":[314],"highlight":[316],"effectiveness":[318],"method":[322],"improving":[324],"UAV\u2019s":[326],"ability":[327],"respond":[329],"efficiently":[330],"offering":[335],"significant":[336],"implications":[337],"future":[340],"settings.":[348]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}