基于遗传算法的智能农业财务成本优化

Xu Gaofeng
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引用次数: 0

摘要

智能农业是一种新兴的应用,主要基于物联网(IoT)的到来。智能农业系统包含许多组件,底层是无线设备网络。无线传感器节点感测到的时间序列数据通过跳-跳通信传递,这可以简化用于智能农业的无线传感器网络的框架,因为它不再需要网络中的多层或集群。这种简单类型的无线传感器网络也可以在没有昂贵移动设备的帮助下很好地工作,这降低了财务成本。通过遗传算法优化覆盖所有温室的路径,可以大大降低啤酒花配送产生的能源成本,这可以大大降低投资成本,并将进一步使智能农业更适合财政投资。
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Optimise financial cost for smart agriculture based on genetic algorithm
Smart agriculture is an emerging application which is largely based on the incoming of the Internet of Things (IoTs). Smart agricultural system contains a lot of components and the lower layer is wireless device network. The time-serials data sensed by wireless sensor nodes is delivered by hop-hop communication which can simplify the framework of the wireless sensor network for smart agriculture, as it no longer needs multiple layers or cluster in the network. And this simple type of wireless sensor network can also work well without the help of expensive mobile devices, which reduces the financial cost. The energy cost generated by the hop-hop delivery can be greatly reduced with the optimisation of the path covering all greenhouses by genetic algorithm, which can largely decrease the investment cost and will further make smart agriculture more suitable for financial investment.
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来源期刊
International Journal of Wireless and Mobile Computing
International Journal of Wireless and Mobile Computing Computer Science-Computer Science (all)
CiteScore
0.80
自引率
0.00%
发文量
76
期刊介绍: The explosive growth of wide-area cellular systems and local area wireless networks which promise to make integrated networks a reality, and the development of "wearable" computers and the emergence of "pervasive" computing paradigm, are just the beginning of "The Wireless and Mobile Revolution". The realisation of wireless connectivity is bringing fundamental changes to telecommunications and computing and profoundly affects the way we compute, communicate, and interact. It provides fully distributed and ubiquitous mobile computing and communications, thus bringing an end to the tyranny of geography.
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