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A hybrid mobile environmental and population density management system for smart poultry farms

机译:智能家禽场的混合移动环境和人口密度管理系统

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Due to advances in technology and size reduction of portable mechanical and electronic devices, sensors have been involved in many sectors, including in agriculture, where sensors and their unique functionalities are extremely useful for both productivity gains and reducing operating costs. These benefits are attained by utilizing their real-time sensing capability over environmental stages affecting the animal breed to enable on-time decision support but with some limitations, i.e., mobility, coverage, ubiquitous access, and energy. Thus, this research focuses on the integration of wireless sensor and mobile system networks with a well-known sensor integration platform toward cloud offloading scalability services via a hybrid architecture used to collect sensing data, such as temperature, humidity, light intensity, and population density, for data analytics and then issuing on-time decisions to adjust the environmental behavior accordingly. Based on a smart poultry farm concept for evaporative cooling environments, the instrument and components of the system design are discussed in detail with the experienced selection criteria, including a discussion of practical topology and deployments, enhanced transmission logics, external environmental tuning control logics integrating mobile user management interfaces, and image processing units. Aside from the proposed prototype of the integration of mobile phones, sensors, and controllers, an experimental investigation was also performed on data sensing and transmission procedures regarding power consumption characteristics, especially on high-cost image data transmissions, including an illustration of the outstanding performance, i.e., 80% in accuracy with low computational complexity, of the image filter over other well-known image classification techniques. (C) 2014 Elsevier B.V. All rights reserved.
机译:由于技术的进步和便携式机械和电子设备尺寸的减小,传感器已涉足许多领域,包括农业领域,在这些领域,传感器及其独特功能对于提高生产率和降低运营成本都极为有用。这些好处是通过在影响动物品种的环境阶段利用其实时感测能力来实现按时决策支持的,但具有一定的局限性,即移动性,覆盖范围,无处不在的访问和能源。因此,这项研究的重点是通过用于收集感测数据(例如温度,湿度,光强度和人口密度)的混合体系结构,将无线传感器和移动系统网络与著名的传感器集成平台集成,以实现云卸载可扩展性服务。 ,用于数据分析,然后发布准时决策以相应地调整环境行为。基于针对蒸发冷却环境的智能家禽场概念,以经验丰富的选择标准详细讨论了系统设计的仪器和组件,包括对实用拓扑和部署,增强的传输逻辑,集成了移动设备的外部环境调整控制逻辑的讨论用户管理界面和图像处理单元。除了提议的集成手机,传感器和控制器的原型外,还针对功耗特性进行了数据传感和传输过程的实验研究,特别是在高成本图像数据传输方面,包括了出色的性能说明。图像过滤器的准确度(即80%的精度和较低的计算复杂度)超过其他众所周知的图像分类技术。 (C)2014 Elsevier B.V.保留所有权利。

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