藉由無線感測網路來設計與實做一套智慧型生活空間

Abstract

近年來，無線感測網路已廣泛被運用在許多方面，而智慧型生活空間是其中一項很重要的應用。本篇論文共包含四項關於智慧型生活空間的研究主題。第一項研究主題是一套智慧型的省電系統，其建構出一套智慧型生活空間的架構，而在這套架構裡，我們提出了兩項靜態的服務與一項動態的服務，此兩項靜態的服務包含了燈源控制系統與空調控制系統，此兩項系統能夠滿足使用者需求並達到節能的目的，而動態服務方面則是提供一套以地理資訊為基礎之服務平台。

在第一個研究主題方面，我們利用無線感測網路提出了一套智慧型個人化節能系統，此系統包含了無線感測網路與家電控制來提供個人化的節能服務。藉由遍佈在環境中的無線感測器來監控室內環境，用以決定何時可關閉該電器，來達到省電的效益。此套系統可以根據使用者的個別需求來自動的調整電器，藉以滿足使用者個人化的需求。

在第二個研究主題方面，我們提出了一套自主式燈光調控系統，此系統藉由使用者所攜帶的光度感測器，來回報目前光度值，用以做為調控燈具之依據。本系統主要是以考量使用者需求與節能為目標，在燈源方面，同時考慮到了全區與局部燈源，而在使用者需求方面，考量了兩種模型，分別以最小化用電量為目標或是以最大化使用者滿意度為目標兩種。我們提出了兩種控制全區燈源的演算法，與一套表面追蹤的演算法用於局部燈源。相較於其他燈源控制系統，當環境改變時，我們的系統可以動態的自動調整所需的光源，並且無需追蹤使用者位置。而在系統驗證方面，除了模擬之外，我們還實作出整套系統，驗證本系統之可行性。

而在第三個研究主題裡，我們提出了一套智慧型的空調控制系統，此系統藉由環境中的溫度感測器，來回報環境中的溫度，用以做為調控的依據。本系統主要是以考量使用者需求與節能為目標，對此我們考量兩種模型，分別以最小化用電量為目標或是以最大化使用者滿意度為目標兩種。對此兩種目標，我們建構出一套溫度模型，與兩套空調控制演算法，用以快速的調整空調系統，來滿足使用者溫度需求。

在最後一個研究主題裡，我們對於居家或辨公環境裡，建構了一套低成本的移動平台。此移動平台可自主式的移動並決定其所在位置，用以提供以地理位置為基礎之相關服務。對於此移動與定位方式，我們提出了一套兩層式架構，讓此移動平台可以達到公分級與公尺級的位置精確度，故此移動平台可以移動到環境中的任意點，來提供使用者所需的服務。我們利用iRobot來實做出整套系統，並驗證其可行性。

Recently, wireless sensor and actuator networks (WSANs) have been widely discussed in many applications. The smart living space is one of the most important application of WSANs. In this dissertation, we propose four works for a smart living space. The first work is an intelligent energy-conservation system which constructs a framework of the smart living space. Under this framework, we propose two static services and one mobile service in this environment. Two static services can control lighting devices and air conditioners automatically to achieve energy saving and satisfy users' requirements. One mobile service provides a location-based services platform in our environment.

In the first work, we propose an iPower (intelligent and personalized energy-conservation system by wireless sensor networks) system which combines WSNs and appliance control devices to provide personalized energy conservation services. A WSN is deployed in each room to monitor the usage of electric appliances and to help determine if there are electric appliances that can be turned off for energy conservation. The iPower system is quite intelligent and can adapt to personal need by automatically adjusting electric appliances to satisfy users' requirements.

In the second work, we propose an autonomous light control system based on the feedback from light sensors carried by users. Our design focuses on meeting users' preferences and energy efficiency. Both whole and local lighting devices are considered. Users' preferences may depend on their activities and profiles and two requirement models are considered: binary satisfaction and continuous satisfaction models. For controlling whole lighting devices, two decision algorithms are proposed. For controlling local lighting devices, a surface-tracking scheme is proposed. Our solutions are autonomous because, as opposed to existing solutions, they can dynamically adapt to environment changes and do not need to track users' current locations. Simulations and prototyping results are presented to verify the effectiveness of our designs.

Similar to the previous work, we propose an intelligent air conditioners control system based on the feedback from temperature sensors in the environment. Our design focuses on meeting users' requirements and energy efficiency. We define two models as users' requirements: binary satisfaction and continuous satisfaction models. For these two models, we propose the temperature model and two control mechanisms to adjust the air conditioners quickly and satisfy all users' temperature requirements.

In the last work, we consider building an indoor low-cost mobile robot that can be used in home applications. Due to the complicated nature of home environments, it is essential for such a robot to be self-guided in the sense that it is able to determine its current location as well as navigate to locations where it is commanded to. We propose a two-tier architecture to achieve this goal at centimeter-to-meter-level accuracy. The robot can even roam into an area which is new to it. We demonstrate a prototyping system based on an extended iRobot and the results have important implications on intelligent homes.