本文選題：物聯(lián)網(wǎng) + SVM��； 參考：《北京交通大學(xué)》2017年碩士論文

【摘要】：蔬菜是我國(guó)重要的農(nóng)產(chǎn)品,也是我國(guó)城鄉(xiāng)居民不可缺少的食物來(lái)源。隨著我國(guó)經(jīng)濟(jì)的不斷發(fā)展和人們生活水平的不斷體高、蔬菜食用量不斷增加,傳統(tǒng)的以數(shù)量為追求的食品欲望已經(jīng)不是現(xiàn)在人們的目標(biāo)了,人們對(duì)食品的品質(zhì)、衛(wèi)生狀況、質(zhì)量、營(yíng)養(yǎng)、健康和營(yíng)養(yǎng)均衡等性能越來(lái)越注重。然而,一些商家為了追求眼前的利益,對(duì)蔬菜質(zhì)量把關(guān)不嚴(yán),導(dǎo)致了大量食品安全事件的發(fā)生。近年來(lái)頻頻曝光的毒豇豆、毒韭菜、毒豆芽等事件,嚴(yán)重影響了人們?nèi)罕姷娘嬍辰】?食品質(zhì)量安全問(wèn)題已成為人們?nèi)粘Ｉ顡?dān)心的問(wèn)題。在這種蔬菜質(zhì)量安全十分嚴(yán)峻的環(huán)境下,蔬菜質(zhì)量追溯系統(tǒng)應(yīng)運(yùn)而生。本文以"首都農(nóng)業(yè)集團(tuán)農(nóng)產(chǎn)品全產(chǎn)業(yè)鏈物流信息服務(wù)平臺(tái)建設(shè)"項(xiàng)目為基礎(chǔ),應(yīng)用物聯(lián)網(wǎng)技術(shù)進(jìn)行蔬菜質(zhì)量追溯系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)。本文將每種蔬菜種植過(guò)程作為一個(gè)工藝流進(jìn)行了規(guī)劃。在每批蔬菜的種植前,根據(jù)蔬菜的工藝流制定了生產(chǎn)計(jì)劃,對(duì)蔬菜的種植過(guò)程中的每個(gè)農(nóng)事操作的時(shí)間點(diǎn)和操作步驟都進(jìn)行了嚴(yán)格設(shè)定。在農(nóng)事操作工具上貼上RFID標(biāo)簽,應(yīng)用RFID技術(shù)、傳感技術(shù)再根據(jù)蔬菜的生產(chǎn)計(jì)劃則可以實(shí)現(xiàn)蔬菜種植過(guò)程中農(nóng)事操作信息的自動(dòng)采集。蔬菜生產(chǎn)工藝的制定以及蔬菜生產(chǎn)計(jì)劃的制定都有益于蔬菜質(zhì)量追溯的進(jìn)行以及蔬菜種植過(guò)程的標(biāo)準(zhǔn)化。本文應(yīng)用GSP技術(shù)、溫濕度傳感器以及無(wú)線(xiàn)傳感技術(shù),對(duì)蔬菜物流過(guò)程中的位置信息、溫度和濕度進(jìn)行了采集,應(yīng)用二維碼技術(shù),將采集的信息以二維碼的形式向消費(fèi)者提供查詢(xún)途徑。為了更好的控制菜的質(zhì)量,本文應(yīng)用支持向量機(jī)的分類(lèi)回歸預(yù)測(cè)模型對(duì)蔬菜的生產(chǎn)地塊進(jìn)行分類(lèi)預(yù)測(cè),以蔬菜種植地塊的"土壤污染度"和地塊中蔬菜的"農(nóng)藥殘留量"作為分類(lèi)指標(biāo),將地塊分為"重點(diǎn)關(guān)注"和"非重點(diǎn)關(guān)注"兩類(lèi)。對(duì)于預(yù)測(cè)結(jié)果為"重點(diǎn)關(guān)注"的地塊,生產(chǎn)基地管理員可對(duì)這類(lèi)地塊進(jìn)行重點(diǎn)關(guān)注。本文研究的基于物聯(lián)網(wǎng)的蔬菜質(zhì)量追溯系統(tǒng)能夠?qū)崿F(xiàn)蔬菜的種植到銷(xiāo)售整個(gè)過(guò)程質(zhì)量信息的自動(dòng)采集與溯源功能。本文研究的蔬菜質(zhì)量追溯系統(tǒng)不僅能實(shí)現(xiàn)消費(fèi)對(duì)蔬菜質(zhì)量信息的需求而且可以提高蔬菜生產(chǎn)基地的管理效率,為蔬菜生產(chǎn)基地的標(biāo)準(zhǔn)化作業(yè)提供參考。
[Abstract]:Vegetable is an important agricultural product and an indispensable food source for urban and rural residents in China. With the continuous development of our economy and the continuous improvement of people's living standards, the amount of vegetables consumed has been increasing. The traditional desire for food with quantity as the pursuit is no longer the goal of people now. People have a sense of food quality and hygiene. Quality, nutrition, health and nutritional balance are more and more important. However, in order to pursue the immediate benefits, some businesses are not strict on the quality of vegetables, leading to a large number of food safety incidents. In recent years, the frequent exposure of toxic cowpea, poisonous leek, toxic bean sprouts and other incidents seriously affected the people's diet health, food quality and safety has become a daily concern of people. In this kind of vegetable quality safety environment, vegetable quality traceability system arises at the historic moment. Based on the project of "Construction of Logistics Information Service platform for the whole Industry chain of Agricultural products of Capital Agricultural Group", the design and implementation of vegetable quality traceability system based on Internet of things technology is presented in this paper. In this paper, each vegetable growing process is planned as a process flow. Before each batch of vegetables was planted, the production plan was worked out according to the technological flow of vegetables, and the time points and operation steps of each agricultural operation in the process of planting vegetables were strictly set. Attaching RFID label to agricultural operation tools, applying RFID technology and sensing technology can realize the automatic collection of agricultural operation information in vegetable planting process according to vegetable production plan. The establishment of vegetable production process and vegetable production plan are beneficial to the traceability of vegetable quality and the standardization of vegetable planting process. In this paper, GSP technology, temperature and humidity sensor and wireless sensor technology are used to collect the position information, temperature and humidity in vegetable logistics process. The collected information is provided to consumers in the form of two-dimensional code. In order to control vegetable quality better, this paper uses the support vector machine (SVM) classification regression prediction model to forecast vegetable production plots. The soil pollution degree of vegetable planting plots and the pesticide residues of vegetables in plots were taken as the classification indexes, and the plots were divided into two categories: "focus attention" and "non-key concern". For the sites where the forecast result is "focus", the production base administrator can focus on this kind of land. The vegetable quality traceability system based on the Internet of things in this paper can realize the automatic collection and tracing function of the quality information in the whole process of planting and selling vegetables. The vegetable quality traceability system studied in this paper can not only meet the demand of consumption for vegetable quality information but also improve the management efficiency of vegetable production base and provide a reference for the standardized operation of vegetable production base.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP391.44;TN929.5;F322

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