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dc.contributor.authorHIMEL, GALIB MUHAMMAD SHAHRIAR
dc.date.accessioned2019-02-20T08:45:57Z
dc.date.available2019-02-20T08:45:57Z
dc.date.issued2019-02-16
dc.identifier.urihttp://dspace.uiu.ac.bd/handle/52243/823
dc.description.abstractThe purpose of the research is to design a new drone architecture which will be capable of moving autonomously through most of the environments by interacting with the server itself. The main feature is that it will be able to move through air, land and water. Nowadays various drones are available. But a drone which can move through any environment is never seen before. The main motive is to use the drone in rescue mission and get accuracy in rescue missions in the cases of environmental & natural calamities and make it easier than previous times. Besides this drone will use the environmental data and bio information as a method of communication while interacting with the environment. Environmental data learning can be used to communicate with the nature and gather bio-information and environmental data from the environment and living beings. We hope this drone will be also able to move under water. For communicating with the environment and learning about the environment this drone will use two kinds of database: temporary database and online database. This research paper proposes a new design and modest algorithm which will help to move the drone autonomously avoiding most of the obstacles in its way. By gathering bio-information and environmental data the proposed ALW (Air, Land, and Water) drone will be able to communicate with the environment and adapt the changes in the environment and communicate with the server to act properly to be successful in its rescue mission. In this paper we used R Studio & R programming language to compare the accuracy results among several Machine Learning algorithms for several datasets. Based on the simulation results we can say that the drone will be able to predict the disaster accurately and recognize animal correctly.en_US
dc.language.isoen_USen_US
dc.publisherUnited International Universityen_US
dc.subjectdroneen_US
dc.subjectAnimal Recognitionen_US
dc.subjectDeep Learningen_US
dc.subjectImage Recognitionen_US
dc.titleA Design of an Autonomous Drone for Animal Recognitionen_US
dc.typeThesisen_US


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