{"title":"最适合在云上降落API的机场","authors":"S. Ayhan, I. Wilson","doi":"10.1109/ICNSURV.2018.8384879","DOIUrl":null,"url":null,"abstract":"Finding a most suitable landing site for manned or unmanned aircraft in case of emergency or search & rescue efforts or for providing disaster relief aids has been a question of interest for some time in the aviation community. Obviously the most suitable landing site is an airport, if it is accommodating, available, and reachable. Although most of today's avionics systems provide a list of nearest airports and a map of the region in case of extraordinary landing situations, critical factors to decide which airport to land is left to the pilot's decision. Selecting one of the listed runways may be risky if the current conditions make it unfeasible. Hence, in this paper, we present a novel Decision Support Tool (DST) in the form of an Application Programming Interface (API) that is deployed on the Microsoft Azure cloud. The API continuously builds a big table with a real-time content by invoking a number of services such as airports, runways, flights data, METAR, and aircraft features. Once, the API has been invoked, top-k airports meeting the specified criteria are presented to the client to enable the decision maker to make informed decisions. The API leverages the cloud technology to deliver a secure, scalable, and highly available service. The service can be used for both manned and unmanned aircraft.","PeriodicalId":112779,"journal":{"name":"2018 Integrated Communications, Navigation, Surveillance Conference (ICNS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Most suitable airport to land API on the cloud\",\"authors\":\"S. Ayhan, I. Wilson\",\"doi\":\"10.1109/ICNSURV.2018.8384879\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Finding a most suitable landing site for manned or unmanned aircraft in case of emergency or search & rescue efforts or for providing disaster relief aids has been a question of interest for some time in the aviation community. Obviously the most suitable landing site is an airport, if it is accommodating, available, and reachable. Although most of today's avionics systems provide a list of nearest airports and a map of the region in case of extraordinary landing situations, critical factors to decide which airport to land is left to the pilot's decision. Selecting one of the listed runways may be risky if the current conditions make it unfeasible. Hence, in this paper, we present a novel Decision Support Tool (DST) in the form of an Application Programming Interface (API) that is deployed on the Microsoft Azure cloud. The API continuously builds a big table with a real-time content by invoking a number of services such as airports, runways, flights data, METAR, and aircraft features. Once, the API has been invoked, top-k airports meeting the specified criteria are presented to the client to enable the decision maker to make informed decisions. The API leverages the cloud technology to deliver a secure, scalable, and highly available service. The service can be used for both manned and unmanned aircraft.\",\"PeriodicalId\":112779,\"journal\":{\"name\":\"2018 Integrated Communications, Navigation, Surveillance Conference (ICNS)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Integrated Communications, Navigation, Surveillance Conference (ICNS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNSURV.2018.8384879\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Integrated Communications, Navigation, Surveillance Conference (ICNS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNSURV.2018.8384879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finding a most suitable landing site for manned or unmanned aircraft in case of emergency or search & rescue efforts or for providing disaster relief aids has been a question of interest for some time in the aviation community. Obviously the most suitable landing site is an airport, if it is accommodating, available, and reachable. Although most of today's avionics systems provide a list of nearest airports and a map of the region in case of extraordinary landing situations, critical factors to decide which airport to land is left to the pilot's decision. Selecting one of the listed runways may be risky if the current conditions make it unfeasible. Hence, in this paper, we present a novel Decision Support Tool (DST) in the form of an Application Programming Interface (API) that is deployed on the Microsoft Azure cloud. The API continuously builds a big table with a real-time content by invoking a number of services such as airports, runways, flights data, METAR, and aircraft features. Once, the API has been invoked, top-k airports meeting the specified criteria are presented to the client to enable the decision maker to make informed decisions. The API leverages the cloud technology to deliver a secure, scalable, and highly available service. The service can be used for both manned and unmanned aircraft.