{"title":"车载户外广告大数据分析系统","authors":"Emmanuel Kayode Akinshola Ogunshile","doi":"10.5220/0005900303190328","DOIUrl":null,"url":null,"abstract":"Outdoor advertising is an old industry and the only reliably growing advertising sector other than online \n \nadvertising. However, for it to sustain this growth, media providers must supply a comparable means of \n \ntracking an advertisementâs effectiveness to online advertising. The problem is a continual and emerging area \n \nof research for large outdoor advertising corporations, and as a result of this, smaller companies looking to \n \njoin the market miss out on providing clients with valuable metrics due to a lack of resources. In this paper, \n \nwe discuss the processes undertaken to develop software to be used as a means of better understanding the \n \npotential effectiveness of a fleet of private car, taxi or bus advertisements. Each of the steps present unique \n \nchallenges including big data visualisation, performance data aggregation and the inherent inconsistencies \n \nand unreliabilities produced by tracking fleets using GPS. We cover how we increased the metric aggregation \n \nalgorithm performance by roughly 20x, built an algorithm and process to render data heat maps on the server \n \nside and how we built an algorithm to clean unwanted GPS âjitterâ.","PeriodicalId":230522,"journal":{"name":"Proceedings of the 6th International Conference on Cloud Computing and Services Science","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Big Data Analysis System for Use in Vehicular Outdoor Advertising\",\"authors\":\"Emmanuel Kayode Akinshola Ogunshile\",\"doi\":\"10.5220/0005900303190328\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Outdoor advertising is an old industry and the only reliably growing advertising sector other than online \\n \\nadvertising. However, for it to sustain this growth, media providers must supply a comparable means of \\n \\ntracking an advertisementâs effectiveness to online advertising. The problem is a continual and emerging area \\n \\nof research for large outdoor advertising corporations, and as a result of this, smaller companies looking to \\n \\njoin the market miss out on providing clients with valuable metrics due to a lack of resources. In this paper, \\n \\nwe discuss the processes undertaken to develop software to be used as a means of better understanding the \\n \\npotential effectiveness of a fleet of private car, taxi or bus advertisements. Each of the steps present unique \\n \\nchallenges including big data visualisation, performance data aggregation and the inherent inconsistencies \\n \\nand unreliabilities produced by tracking fleets using GPS. We cover how we increased the metric aggregation \\n \\nalgorithm performance by roughly 20x, built an algorithm and process to render data heat maps on the server \\n \\nside and how we built an algorithm to clean unwanted GPS âjitterâ.\",\"PeriodicalId\":230522,\"journal\":{\"name\":\"Proceedings of the 6th International Conference on Cloud Computing and Services Science\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th International Conference on Cloud Computing and Services Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0005900303190328\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Cloud Computing and Services Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005900303190328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Big Data Analysis System for Use in Vehicular Outdoor Advertising
Outdoor advertising is an old industry and the only reliably growing advertising sector other than online
advertising. However, for it to sustain this growth, media providers must supply a comparable means of
tracking an advertisementâs effectiveness to online advertising. The problem is a continual and emerging area
of research for large outdoor advertising corporations, and as a result of this, smaller companies looking to
join the market miss out on providing clients with valuable metrics due to a lack of resources. In this paper,
we discuss the processes undertaken to develop software to be used as a means of better understanding the
potential effectiveness of a fleet of private car, taxi or bus advertisements. Each of the steps present unique
challenges including big data visualisation, performance data aggregation and the inherent inconsistencies
and unreliabilities produced by tracking fleets using GPS. We cover how we increased the metric aggregation
algorithm performance by roughly 20x, built an algorithm and process to render data heat maps on the server
side and how we built an algorithm to clean unwanted GPS âjitterâ.