臺灣博碩士論文加值系統

現代人對於生活舒適度的條件越來越多樣化，適宜的溫度、柔和的光線、綠化的裝飾等等，經研究發現舒適的家居環境不僅能令人壓力舒緩使心情輕鬆愉快，更能預防疾病產生並增強體魄，對於大部分人來說一整天時間至少有三分之一的時間處在居家環境當中，如果居家舒適度差，或者雜亂的家居環境，這些都可能會誘發各種疾病的產生。

然而現有文獻對於不同方向的多組百葉窗並沒有提出相關的解決辦法，因為不同方向代表著光線的差異度極大，此實驗也架設了新的實驗環境個別包含東面南面西面百葉窗，例如早上太陽東邊升起東面的百葉窗會受到光線的直射，而西面的百葉窗只會被環境光源影響等等，代表東面百葉窗的解不一定能讓西面百葉窗學習。所以這邊我們承襲PSO的互相學習的習性，並且新增加參考解可以用來判斷各個百葉窗學習的方向是否正確，做了一連串的實驗發現確實解決了不同方向的百葉窗甚麼時候該學習，甚麼時候該自行搜索。

Modern conditions for the comfort of living more and more diverse, suitable temperature, soft light, green decoration, etc., the comfortable home environment by the study found that not only can make the pressure to ease the mood relaxed and happy, more prevent the disease Produce and enhance the body, for most people for a whole day at least one-third of the time in the home environment, if the home comfort is poor, or messy home environment which may induce dozens of diseases.
Comfort conditions include temperature, humidity, light, ventilation, green, etc. For the control temperature using air conditioning, humidity dehumidification humidifier, light curtains, ventilation on the use of doors and windows design, but each environment Although the factors are controlled by different appliances, in fact each of the environmental factors are closely related, such as light intensity affect the temperature, light intensity affect the humidity, ventilation affect the humidity and so on. So we will design a set of three parameters temperature, humidity and light, you can use the blinds to do control, to adjust the current most reasonable comfort of the environment, and save a lot of electrical energy consumption to achieve energy saving The effect of reducing carbon

摘 要 I
Abstract II
目錄 III
圖索引 IV
表目錄 V
第一章 緒論 1
1.1 簡介 1
1.2 文獻回顧 3
1.3 系統架構 4
第二章 電動窗簾之系統硬體架構 5
2.1 系統原理 5
2.2 控制主機(Raspberry Pi) 7
2.3 收集感測器訊息主機(Arduino) 8
2.4 感測器設備 9
2.4.1 IRremote 9
2.4.2 DHT-11溫濕度感測器 11
2.4.3 GY-30數位光強度檢測模組 12
2.4.4 GY-291 ADXL345數字三軸重力加速度傾斜模組 12
2.4.5 步進馬達 14
2.5 RaspberryPi開發語言 17
2.6 Arduino 開發語言 18
第三章 以PSO演算法做為室內舒適度之光照及溫濕度控制 19
3.1 PSO簡介 19
3.2 PSO基本概念 21
3.3 PSO參數在實務上的設置、調控 25
3.4 百葉窗PSO設計 26
3.5 參考解設計 30
第四章 實驗結果與討論 33
4.1 三組百葉窗PSO環境設計 33
4.2 三組百葉窗PSO實驗設計 34
4.3 三組百葉窗PSO訓練實驗結果比較 35
4.4 PSO訓練後之單一百葉窗數據結果 43
第五章 結論 45
參考文獻 46

[1].Lee, A., Angeles, C., Talampas, M., Sison, L., and Soriano, M., “MotesArt: Wireless Sensor Network for Monitoring Relative Humidity and Temperature in an Art Gallery”, IEEE International Conference on Networking, Sensing and Control (ICNSC 2008), April 2008, pp. 1263-1268.
[2].Jayavardhana Gubbi, Rajkumar Buyya, Slaven Marusic, Marimuthu Palaniswami”A vision, architectural elements, and future directions” , January 2013,pp.1645-1660.
[3].Rodríguez, L., Brito, L., and Gouveia, B., “The WISE-MUSE Project: Environmental Monitoring and Controlling of Museums based on Wireless Sensors Networks. Electronic Journal of Structural Engineering (EJSE), Special Issue on Sensor Network for Building Monitoring: From Theory to Real Application”, October 2009, pp. 46 –57.
[4].Brito, L., Rodríguez, L., Santos, F., and Fernandes, R., “Environmental Monitoring of Museums Based on Wireless Sensor Networks”, Proc. 4th International Conference on Wireless and Mobile Communications (ICWMC 2008), IEEE Computer Society Press, Athens, Greece, August, 2008, pp. 364-369.
[5].W. He, G. Yan, and Li Da Xu, ” Developing Vehicular Data Cloud Services in the IoT Environment” IEEE Transactions on Industrial Informatics, May 2014, pp.1551-3203.
[6].J. Kennedy, and R. C. Eberhart, “Particle swarm optimization”, Proc. IEEE International Conf Center, Piscataway, November 1995, pp. IV: 1942-1948.
[7].R. C. Eberhart, and J. Kennedy, “new optimizer using particle swarm theory”, Proc. Sixth International Symposium on Nagoya, Japan, May 1995, pp.39-43.
[8].Q. M. Ashraf, M. I. M. Yusoff, A. A. Azman, N. M. Nor, N. A. A. Fuzi, M. S. Saharedan, N. A. Omar, “Energy monitoring prototype for Internet of Things: Preliminary results,” Internet of Things (WF-IoT), 2015 IEEE 2nd World Forum on, Milan, Dec. 2015, pp. 1–5
[9].交通部中央氣象局
http://www.cwb.gov.tw/V7/knowledge/encyclo pedia/me005.htm
[10].Qian Zhu, Ruicong Wang, Qi Chen, Yan Liu and Weijun Qin, ” IOT Gateway: BridgingWireless Sensor Networks into Internet of Things” , Embedded and Ubiquitous Computing (EUC),Dec 2010 ,pp. 347 - 352.
[11].Xinchen Lyu., Wei Ni., Hui Tain., "Optimal Schedule of Mobile Edge Computing for Internet of Things Using Partial Information," IEEE Journal on Selected Areas in Communications, vol. 35, no. 11, Nov. 2017, pp. 2606-2615.
[12].J.-Y. Son, J.-H. Park, K.-D. Moon and Y.-H. Lee,"Resource-aware smart home management system byconstructing resource relation graph," IEEE Transactionson Consumer lectronics ,Oct 2011, pp. 1112-1119.
[13].O. Elma and U. S. Selamogullari, "A new home energymanagement algorithm with voltage control in a smarthome environment," ,August 2015, pp. 720-731
[14].M.J. Chae, H.S. Yoo, J.Y. Kim, and M.Y. Cho, “Development of a Wireless Sensor Network System for Suspension Bridge Health Monitoring,” Automation in Construction, January 2012, Vol. 21, pp. 237–252.
[15].O. Salman, I. Elhajj, A. Kayssi and A. Chehab,”Edge Computing Enabling the Internet of Things,” Proceedings of the 2nd IEEE International Conference on World Forum on Internet of Things (IEEE WF-IoT 2015), Dec 2015, pp. 603-608.
[16].Particle Swarm Optimization
http://jeremy.fix.free.fr/Softwares/pso.html