在智慧家庭、智慧城市、或智慧建築的趨勢下，越來越多感測器裝置在人類生活周遭。若採用無線感測網路(Wireless Sensor Network, WSN)架構，每個感測器(Sensor Node)將把收集的資料傳送到附近的閘道器結點(Gateway Node)上，此閘道器結點具有一般網際網路連結能力，可再將資料傳送到中央伺服器上進行分析。然而，許多感測器收集的資料均具有個人隱私問題，從感測器到閘道器這段過程因常在內部網路內，資料安全性可稍低，但閘道器到中央伺服器段的資料傳送安全性要求則常較高，直接將原始資料送出不但有安全疑慮，且也因資料量大將對伺服器造成負荷。
本研究提出分散式感測資料之自動聚合統計報表系統，著眼於一般報表常只需要觀看各資料的平均值與標準差，開發出從中央伺服器自動聚合各閘道器內的資料，透過數學公式計算合併後的平均值與標準差，讓整體傳送過程無原始資料，卻又能觀察所有原始數據聚合後的準確平均值與標準差。本研究使用了Apache Tomcat作為網頁Server並利用Java Server Page來建立出UI網頁介面，此頁面能讓使用者查詢自身家戶的感測器的數值並繪製成分散報表的形式，同時能管理上萬筆資料，資料庫部份採用了MySQL資料庫，並利用MySQL開放原始碼能針對不同應用來修改的特性，新增了能方便查詢資料的功能。應用在防災監測領域，可預期未來許多系統若遵循WSN建議的架構，則可透過本系統自動彙整各感測器的資料與統計結果，同時保存資料的隱密性。

In the trend of smart home, smart city or smart building, many sensors have been deployed in such environments. From the theoretical background of Wireless Sensor Network (WSN), each sensor node should transmit a measured value to its gateway node. Each gateway node can be a computer with better processing power and should aggregate the data sets received in order to transmit to a final central server. However, since sensor data sets have personal privacy problems, in an intranet environment the transmission data between sensors and gateway nodes may have lower security concerns while the transmission data between gateway nodes and the final server may have higher security concerns. In addition, a large data set may cause degradation of network performance for gateway nodes.
This research presents distributed, aggregated sensor data collection and analysis for power consumption data sets. Focusing on peer reviews, the power consumption data analytics will display each average value and standard deviation. Apache Tomcat Server was utilized to build Web Server and run Java Server Pages to provide Web UI interface. MySQL database was also employed to store the power consumption data sets. Applications in the field of disaster monitoring can be expected to provide the aggregated data and statistics for each sensor through the system.

[1] Rabindra Bista, & Jae-Woo Chang ,(2010), Privacy-Preserving Data Aggregation Protocols for Sensor Networks: A Survey, Sensors, 10, No. 5, 4577 – 4601.
[2] Jian XU, Geng YANG, Zhengyu CHEN, & Qianqian WANG, (2015), A Survey on the Privacy-Preserving Data Aggregation in Wireless Sensor Networks, China Communications, 12, No. 5, 162-180.
[3] Conti Mauro, Zhang Lei, Roy Sankardas, Roberto Di-Pietro, Jajodia Sushil, Luigi Vincenzo Mancini, (2009), Privacy-preserving robust data aggregation in wireless sensor networks, Security and Communication Networks, 2, No. 2, 195-213.
[4] Gelareh Taban, & Virgil D. Gligor, (2009), Privacy-preserving integrity-assured data aggregation in sensor networks, IEEE Computational Science and Engineering, 3, 168-175.
[5] W. He, X. Liu, H. Nguyen, K. Nahrstedt, T. Abdelzaher, (2011), PDA: Privacy-Preserving Data Aggregation for Information Collection, ACM Transactions on Sensor Networks, 8, No. 6.
[6] JFreeChart,(July 31, 2014), JFreeChart API Documentation, JFreeChart 1.0.19 API Documentation, Retrieved from http://www.jfree.org/jfreechart/api.html (June 14,2015).
[7] Google,(October 14,2014), Google Security Blog ,This POODLE bites: exploiting the SSL 3.0 fallback ,Retrieved from https://security.googleblog.com/2014/10/this-poodle-bites-exploiting-ssl-30.html (December 8, 2015).
[8] Heartbleed,(April 29, 2014), The Heartbleed Bug, Retrieved from http://heartbleed.com (December 13,2015).
[9] CVE,(n. d.),CVE List Master Copy, CVE-2014-0160, Retrieved from https://cve.mitre.org/cgi-bin/cvename.cgi?name=cve-2014-0160 (December 13, 2015).