本文選題：體域網(wǎng) + 數(shù)據(jù)預(yù)測��； 參考：《哈爾濱工業(yè)大學(xué)》2017年碩士論文

【摘要】：無線通信技術(shù)的發(fā)展徹底改變了我們的日常生活,其技術(shù)應(yīng)用涉及自動化控制、跟蹤與監(jiān)控。隨著無線傳感器網(wǎng)絡(luò)(Wireless Sensor Network,WSN)技術(shù)的發(fā)展改進(jìn),出現(xiàn)了體域網(wǎng)(Wireless Body Area Network,WBAN),通過將低成本的、能量受限的、微小的異構(gòu)傳感器節(jié)點穿戴甚至植入人體,形成一個特殊的型無線傳感器網(wǎng)絡(luò),采集生理信息,通過無線通信到中央基站,實現(xiàn)了對人體各個指標(biāo)的實時監(jiān)測。WBAN傳感器設(shè)備提供實時反饋,對人體不會造成任何不適,從而為用戶提供更大靈活性和流動性,可以代替復(fù)雜有線醫(yī)療設(shè)備,能夠連續(xù)監(jiān)測人體的重要生理信號和娛樂信號。與所有其他電子系統(tǒng)相同,WBAN也需要適當(dāng)?shù)碾娫幢ＷC其正常運作。目前,WBAN大都采用電池供電系統(tǒng)。但相比較其他WSN系統(tǒng),由于傳感器網(wǎng)絡(luò)設(shè)計及應(yīng)用的特殊性,WBAN電池難以及時更換,所以應(yīng)用各種節(jié)能技術(shù),為WBAN提供一個非常長的網(wǎng)絡(luò)壽命,是研究的重點領(lǐng)域之一。一般來講,WBAN節(jié)能主要采用使用更加節(jié)能的電子器件、減少能源消耗的設(shè)備數(shù)量以及采用更加有效的算法,使得對于一個給定的電池容量,提高在系統(tǒng)的操作過程中的能量使用效率。WBAN能量的消耗可以分為三個部分:感知、無線通信和數(shù)據(jù)處理,其中無線通信是最耗電的。體域網(wǎng)所收集的信息一般都具有較高的時間冗余和空間冗余。通過數(shù)據(jù)融合技術(shù),減少WBAN中的無線通信量可以達(dá)到節(jié)省能量的目的。根據(jù)以上分析本文進(jìn)行了以下工作:(1)本文提出了一種基于小波分析和最小二乘支持向量機(jī)的時間序列數(shù)據(jù)預(yù)測技術(shù)的數(shù)據(jù)融合算法。通過在感知節(jié)點和匯聚節(jié)點處分別建立一個相同的輕量級數(shù)據(jù)預(yù)測模型,當(dāng)預(yù)測結(jié)果在誤差范圍之內(nèi)則不進(jìn)行數(shù)據(jù)的傳輸,從而降低了網(wǎng)內(nèi)冗余數(shù)據(jù)的傳輸,減少傳輸能耗。(2)本文研究了預(yù)測模型的參數(shù)優(yōu)化的方法,并根據(jù)理論分析提出了一種改進(jìn)的粒子群算法,該算法通過對基本粒子群算法中的參數(shù)進(jìn)行改進(jìn)以及結(jié)合遺傳算法思想對算法迭代過程進(jìn)行改進(jìn)克服了原算法的一些不足。(3)本文基于對人體基本生理數(shù)據(jù)進(jìn)行健康監(jiān)測出發(fā)設(shè)計了一種WBAN系統(tǒng),對系統(tǒng)的應(yīng)用場景及功能進(jìn)行了分析,設(shè)計了其架構(gòu),并對傳感器節(jié)點以及網(wǎng)關(guān)節(jié)點進(jìn)行了軟硬件設(shè)計。最后將本文提出的算法在該實驗平臺上進(jìn)行了驗證分析。
[Abstract]:The development of wireless communication technology has completely changed our daily life, its technical application involves automation control, tracking and monitoring. With the development and improvement of Wireless Sensor Network (WSN) technology, Wireless body Area Network (WBAN) has emerged, by wearing or even implanting low-cost, energy-constrained, tiny heterogeneous sensor nodes into the human body. A special type of wireless sensor network is formed, which collects physiological information and wirelessly communicates to the central base station, which provides real-time feedback to the real-time monitoring of every index of the human body. WBAN sensor equipment does not cause any discomfort to the human body. Thus, it can provide more flexibility and mobility for users, can replace complex wired medical equipment, and can continuously monitor important physiological and entertainment signals of human body. WBAN, like all other electronic systems, also requires proper power supply to ensure its proper operation. At present, most of WBAN use battery power supply system. However, compared with other WSN systems, because of the particularity of sensor network design and application, WBAN battery is difficult to be replaced in time, so the application of various energy-saving technologies to provide a very long network life for WBAN is one of the key areas of research. In general, WBAN uses more energy efficient electronic devices, reduces the number of energy consuming devices, and uses more efficient algorithms, so that for a given battery capacity, The energy consumption of WBAN can be divided into three parts: perception, wireless communication and data processing, among which wireless communication is the most power consuming. The information collected by body area network generally has high time redundancy and space redundancy. By using data fusion technology, the energy saving can be achieved by reducing the wireless traffic in WBAN. Based on the above analysis, the following works have been done: (1) this paper proposes a data fusion algorithm based on wavelet analysis and least squares support vector machine (LS-SVM) for time series data prediction. By establishing the same lightweight data prediction model at the perceptual node and the convergence node respectively, when the prediction results are within the error range, the data transmission is not carried out, thus reducing the transmission of redundant data in the network. (2) the method of parameter optimization of prediction model is studied in this paper, and an improved particle swarm optimization algorithm is proposed according to theoretical analysis. The algorithm overcomes some shortcomings of the original algorithm by improving the parameters in the basic particle swarm optimization algorithm and the iterative process of the algorithm with the idea of genetic algorithm. (3) based on the basic physiological data of human body, this paper is based on the basic physiological data. A WBAN system is designed for Kang Monitoring. The application scene and function of the system are analyzed, the structure of the system is designed, and the hardware and software of the sensor node and the gateway node are designed. Finally, the proposed algorithm is verified and analyzed on the platform.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP212.9;TN929.5

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