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An efficient framework for data aggregation in smart agriculture
Author(s) -
Yuan Jiangjun,
Liu Weinan,
Wang Jie,
Shi Jiawen,
Miao Ling
Publication year - 2020
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.6160
Subject(s) - scalability , computer science , aggregate (composite) , resource (disambiguation) , data aggregator , data center , the internet , control (management) , wireless sensor network , computer network , distributed computing , real time computing , database , artificial intelligence , world wide web , materials science , composite material
Summary With the advanced development of smart devices and network technique, Internet of Things has seen a large number of popular applications, among which, smart agriculture is a good example. The sensor nodes collect some parameters in the greenhouse, and send them to the control center. Then the control center can conduct some operations according to the analysis of the collected parameters. In this paper, we discuss how to efficiently aggregate and collect data with features of privacy protection in smart agricultural system. We propose an effective and scalable framework. The genetic algorithm is used to obtain the optimized data collection route for the agricultural system. The use of unmanned aerial vehicle also greatly improves the communication efficiency of resource‐constrained sensors in the system, which further increases the use time of the entire agricultural system. The experimental analysis shows that our framework has good efficiency and enjoys good scalability.