基于生物质原料生产信息系统的自动化农业机器人和传感器数据采集与分析

Konstantinos Domdouzis
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引用次数: 0

摘要

使用不可再生的矿物燃料所造成的日益严重的环境污染,以及由于缺乏这类燃料而导致各国之间经济依赖的发展,都突出表明迫切需要使用可持续形式的能源。生物质衍生的生物燃料提供了这样一种选择。生物质原料生产的主要任务是种植栽培、收获、储存和运输。每一项任务都有许多复杂的决策。这些决定与监测作物健康、利用创新技术提高作物生产力以及审查与生物质原料生产有关的现有工艺和技术的局限性有关。其他关键问题是在保持产品质量的同时开发可持续的生物质输送方法。有必要开发一种基于弹性和可持续性的自动化综合研究工具,它将允许不同研究领域的协调,但也可以自己进行研究。具体的工具应以优化不同的参数为目标,这些参数指定了所做的研究和生物质原料生产的情况;这些参数是生物质从野外到生物精炼厂的运输、使用的设备和生物质储存条件。这种优化将提高生物能源生产领域的决策能力。基于对这种自动化集成研究工具的需求,本文提出了一种基于农业机器人和传感器数据的收集和分析,为生物能源生产领域更好地决策提供自动化功能的信息系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Agricultural Robot and Sensor Data Collection and Analysis through a Biomass Feedstock Production Information System
The increasing environmental pollution resulting from the use of non-renewable fossil fuels as well as the development of economic dependencies among countries because of the lack of such types of fuels underline the intense need for the use of sustainable forms of energy. Biomass derived biofuels provide such an alternative. The main tasks of biomass feedstock production are planting and cultivation, harvest, storage, and transportation. A number of complex decisions characterize each of these tasks. These decisions are related to the monitoring of crop health, the improvement of crop productivity using innovative technologies, and the examination of limitations in existing processes and technologies associated with biomass feedstock production. Other critical issues are the development of sustainable methods for the delivery of the biomass while maintaining product quality. There is the need for the development of an automated integrated research tool based on resilience and sustainability which will allow the coordination of different research fields but also perform research on its own. The specific tool should aim in the optimization of different parameters which specify the research done and in the case of biomass feedstock production; such parameters are the transportation of biomass from the field to the biorefinery, the equipment used, and the biomass storage conditions. This optimization would enhance decision making in the field of bioenergy production. Based on the need for such an automated integrated research tool, this paper presents an information system that provides automated functionalities for better decision making in the bioenergy production field based on the collection and analysis of agricultural robot and sensor data.
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