基于物联网与机器学习的智能农业温室控制系统
Intelligent Agricultural Greenhouse Control System Based on Internet of Things and Machine Learning
AI总结：
针对传统温室农业依赖经验规则、调控缺乏个性化导致资源低效的问题，本研究融合物联网与机器学习技术，构建智能温室控制系统，通过实时监测环境参数精准调控，提升农业生产效率与可持续性。
摘要：
本研究致力于构思并实现一套以物联网（IoT）与机器学习融合为基础的先进农业温室控制系统。通过对温室内在环境参数的精细化监测，结合机器学习算法，可对温室内的条件进行适宜调控，预期目标是提升作物生长效率与产量，同时减少资源浪费。\n在全球人口数量持续攀升、气候变化带来的紧迫需求日益加剧的背景下，农业正面临前所未有的挑战。传统农业模式已被证明无法满足食品安全与生产效率的迫切要求。在此背景下，温室农业作为一种可行解决方案应运而生，它能为作物种植提供可控环境，从而提高产量、改善品质并降低对自然资源的依赖[b1]。\n然而，温室农业也面临一系列挑战。传统温室管理策略往往基于经验知识与预设规则，缺乏针对性的个性化调控，进而导致资源利用效率低下。随着农业规模不断扩大，对温室内环境进行实时监测与精准控制的需求变得至关重要。为解决这一挑战，本研究将物联网技术与机器学习算法引入温室农业，旨在构建一套智能农业温室控制系统，助力提升农业生产的效率与可持续性。
英文摘要：
This study endeavors to conceptualize and execute a sophisticated agricultural greenhouse control system grounded in the amalgamation of the Internet of Things (IoT) and machine learning. Through meticulous monitoring of intrinsic environmental parameters within the greenhouse and the integration of machine learning algorithms, the conditions within the greenhouse are aptly modulated. The envisaged outcome is an enhancement in crop growth efficiency and yield, accompanied by a reduction in resource wastage. In the backdrop of escalating global population figures and the escalating exigencies of climate change, agriculture confronts unprecedented challenges. Conventional agricultural paradigms have proven inadequate in addressing the imperatives of food safety and production efficiency. Against this backdrop, greenhouse agriculture emerges as a viable solution, proffering a controlled milieu for crop cultivation to augment yields, refine quality, and diminish reliance on natural resources [b1]. Nevertheless, greenhouse agriculture contends with a gamut of challenges. Traditional greenhouse management strategies, often grounded in experiential knowledge and predefined rules, lack targeted personalized regulation, thereby resulting in resource inefficiencies. The exigencies of real-time monitoring and precise control of the greenhouse's internal environment gain paramount importance with the burgeoning scale of agriculture. To redress this challenge, the study introduces IoT technology and machine learning algorithms into greenhouse agriculture, aspiring to institute an intelligent agricultural greenhouse control system conducive to augmenting the efficiency and sustainability of agricultural production.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
