P. Tripicchio, Massimo Satler, Giacomo Dabisias, E. Ruffaldi, C. Avizzano
{"title":"用无人机实现智能农业和可持续农业","authors":"P. Tripicchio, Massimo Satler, Giacomo Dabisias, E. Ruffaldi, C. Avizzano","doi":"10.1109/IE.2015.29","DOIUrl":null,"url":null,"abstract":"The use of drones in agriculture is becoming more and more popular. The paper presents a novel approach to distinguish between different field's plowing techniques by means of an RGB-D sensor. The presented system can be easily integrated in commercially available Unmanned Aerial Vehicles (UAVs). In order to successfully classify the plowing techniques, two different measurement algorithms have been developed. Experimental tests show that the proposed methodology is able to provide a good classification of the field's plowing depths.","PeriodicalId":228285,"journal":{"name":"2015 International Conference on Intelligent Environments","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"207","resultStr":"{\"title\":\"Towards Smart Farming and Sustainable Agriculture with Drones\",\"authors\":\"P. Tripicchio, Massimo Satler, Giacomo Dabisias, E. Ruffaldi, C. Avizzano\",\"doi\":\"10.1109/IE.2015.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of drones in agriculture is becoming more and more popular. The paper presents a novel approach to distinguish between different field's plowing techniques by means of an RGB-D sensor. The presented system can be easily integrated in commercially available Unmanned Aerial Vehicles (UAVs). In order to successfully classify the plowing techniques, two different measurement algorithms have been developed. Experimental tests show that the proposed methodology is able to provide a good classification of the field's plowing depths.\",\"PeriodicalId\":228285,\"journal\":{\"name\":\"2015 International Conference on Intelligent Environments\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"207\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Intelligent Environments\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IE.2015.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Intelligent Environments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IE.2015.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards Smart Farming and Sustainable Agriculture with Drones
The use of drones in agriculture is becoming more and more popular. The paper presents a novel approach to distinguish between different field's plowing techniques by means of an RGB-D sensor. The presented system can be easily integrated in commercially available Unmanned Aerial Vehicles (UAVs). In order to successfully classify the plowing techniques, two different measurement algorithms have been developed. Experimental tests show that the proposed methodology is able to provide a good classification of the field's plowing depths.