ANALYZING WORLD EVOLUTION AND ITS EFFECTS ON URBAN DESIGNING

Our society's modalities of communication and hence our cities have been rapidly changed due to emergence of several revolutions most lately the digital one. In fact, recently with emergence of the fluid, responsive, kinetic, data-driven worlds of infoscape and its combination with urban landscape, urban designing faces a radical reshuffling of a number of its principal underpinnings. It seems that once again we as urban designers in order to catch up with the current world's situation need to evolve or in better words to re-ontologize concepts of urban designing for twenty-first century. Therefore; in this paper for better understanding of the main characteristics of current changes we try to identify the effects of new actors on urban structures trough analysis of different evolution phases of our cities. To do so we make a diagram called "Evolutionary Trend" trough which we can trace world's evolution history to help us know where we are and what may happen in coming decades. This "evolutionary trend" can be used as a guideline for urban designers to help them navigate better in future.Evolutionary Trend, Urban Evolution, Infospherization, Softerial Era, Digital revolution

Motion Detecting Method And Device

In some embodiments, a motion detecting device is configured to detect whether one or more movement events have occurred. The motion detecting device can include: (a) a processing module configured to run on a computational unit; and (b) a sensing device having: (1) one or more pressure sensors configured to provide two or more pressure measurements; and (2) a transmitter electrically coupled to the one or more pressure sensors and configured to transmit the two or more pressure measurements to the computational unit. The processing module is configured to use the two or more pressure measurements to determine whether the one or more movement events have occurred. The sensing device can be configured to be placed in at least one of ductwork of a heating, ventilation, and air conditioning system or an air handler of the heating, ventilation, and air conditioning system. Other embodiments are disclosed.Georgia Tech Research Corporatio

Configurable dynamic privacy for pervasive sensor networks

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 76-79).Ubiquitous computing sensor networks have greatly augmented the functionality of interactive media systems by adding the ability to capture and store activity-related information. Analyzing the information recorded from pervasive sensor networks can provide insight about human behavior for better personalized system services, as well as richer media content and social communication. With these increased capabilities, serious concerns which create great obstacles to the deployment of such network are raised with regard to privacy and boundaries. However, there exist no real data currently about privacy in pervasive media networks and most studies that have been made so far are speculative. This thesis presents the design and implementation of a configurable infrastructure that can protect users' dynamic levels of privacy in a pervasive sensor network. Through an active badge system, users have different options to disable each type of data transmission. This work evaluates approaches for privacy protection through conducting an extensive user study in an actual ubiquitous invasive sensing environment to obtain feedback via sensor system data and questionnaires and correlates that information for future reference in the design of privacy-protected ubiquitous sensor networks. Results from the user study indicated that an active badge for on-site control, especially periodically broadcast RF beacon for privacy control, is the most effective and acceptable method.(cont.) However, it also suggested that if every occupant in the building used this approach to constantly block all data transmission, significant system blinding (on the order of 30 % or more) would be incurred. These results allow a better understanding of what value is assessed to privacy versus capabilities/awareness beyond the current assumptions.by Nan-Wei Gong.S.M

Sensor-Based Analysis of Object-Use Patterns for the Automatic Assessment of Cognitive Status.

Indications of cognitive impairments such as dementia and traumatic brain injury (TBI) are often subtle and may be frequently missed by primary care physicians. These impairments are not uncommon: approximately 0.46% of Americans are hospitalized for brain injury each year and it is estimated that by 2050 up to 13 million Americans may have Alzheimer's disease—the most common form of dementia—quadruple the number that did in 2002. This dissertation proposes and investigates ways in which machine inference and wireless sensors can be used to support the assessment of cognitive functioning. The central hypothesis is that object-usage data collected from wireless sensors during the performance of daily activities are sufficient to assess cognitive impairment. I first investigate the ability to recognize individuals based on their sensed object-usage patterns during a simple task. This experiment constitutes an initial step in understanding how well object-use patterns can be automatically observed and analyzed. A preliminary study, using the simple task of preparing a cup of coffee, demonstrated the ability to correctly recognize ten individuals with 77% accuracy based on nine trials from each individual as training data. The dissertation then directly addresses assessment of cognitive impairment with a study in which individuals with TBI made a pot of coffee. Four features were derived from the sensed data and compared to to the subjects' scores on standard neuropsychological evaluations. A key result is that Edit Distance, the most knowledge-rich feature, significantly correlates with an apparent indicator of general neuropsychological integrity, namely the first principal component of the neuropsychological assessments. Since cognitive impairments are measured along many dimensions, suggestive correlations between the computed features and individual assessments are also presented. Lastly, I present a preliminary study that investigates the possibility of differentiating impaired individuals from unimpaired individuals. Data was collected from five subjects with TBI and five matched, unimpaired subjects; analysis was done using the same set of computed features. Although the study is preliminary, it is interesting that Edit Distance is able to perfectly differentiate the impaired subjects from the unimpaired and that full results are consistent with those from the assessment study.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78894/1/hodgesm_1.pd

The design of a portable kit of wireless sensors for naturalistic data collection

Abstract. In this paper, we introduce MITes, a flexible kit of wireless sensing devices for pervasive computing research in natural settings. The sensors have been optimized for ease of use, ease of installation, affordability, and robustness to environmental conditions in complex spaces such as homes. The kit includes six environmental sensors: movement, movement tuned for object-usage-detection, light, temperature, proximity, and current sensing in electric appliances. The kit also includes five wearable sensors: onbody acceleration, heart rate, ultra-violet radiation exposure, RFID reader wristband, and location beacons. The sensors can be used simultaneously with a single receiver in the same environment. This paper describes our design goals and results of the evaluation of some of the sensors and their performance characteristics. Also described is how the kit is being used for acquisition of data in non-laboratory settings where real-time multi-modal sensor information is acquired simultaneously from several sensors worn on the body and up to several hundred sensors distributed in an environment.

人間の行為選好と信頼感に対応したホームエージェントの設計と実効的評価に関する研究

人間の生活の利便性や操作性などの向上を目的として，家庭で使われる機器（家電機器）が開発されてきた．一方，多機能な家電機器が住宅内にあふれ，住民（ユーザ）による操作量が増えてしまった．そこで，近年，ユーザに代わって家電操作を実行するホームエージェントが提案されている．従来のホームエージェントの研究では，主に「家電機器の状態，ユーザの状態，ユーザの行動履歴から，ユーザの行動パターンを学習し，家電機器を自動操作（操作代行）すること」を目指している．また，ホームエージェントによる操作代行は，実際にホームエージェントシステムを組み込んだ住宅を用意した実証実験が行われている．しかし，ユーザのためにホームエージェントが操作代行を行うにも関わらず，ユーザ目線が欠けたホームエージェントが多い．ホームエージェントは学習した行動パターンに沿って一方的に操作代行を行い，ユーザの都合を無視している．また，ホームエージェントの評価では様々な被験者での実験が必要であるが，実験では実証実験の環境に被験者が数か月に渡って実際に住む必要があり，多くの評価実験が行えない．本論文は，ホームエージェントによる操作代行に対するユーザの捉え方を重視し，ユーザの行為選好と信頼感に対応したホームエージェントの設計と実効的な評価方法を提案する．ユーザの行為選好とは，家電操作には，ユーザが操作代行を望む操作だけではなく，ユーザ自身の楽しみなどの理由により操作代行を望まない操作があるということである．そのため，ユーザ自身が楽しむための家電操作の存在に着目したホームエージェントの設計が必要である。また，ホームエージェントの操作代行の信頼性に対するユーザの信頼感とは，ホームエージェントの操作代行の性能をユーザが見極めることで，ホームエージェントへの信頼感を持つことにあたる．ホームエージェントはユーザの行動を完ぺきに予測することができないため，ホームエージェントによる操作代行に対してユーザが信頼感を抱くことは重要である．本論文は以下のように構成されている．まず第1章で本論文の目的を述べる．ホームエージェントが操作代行を行うときに，ユーザ目線を考慮することが重要であり，また，ホームエージェントを評価する際には様々な被験者で行うことが必要である．本論文では，ユーザ目線としてユーザの行為選好と信頼感に着目し，それらに対応したホームエージェントの設計を示し，さらにホームエージェントの実効的な評価方法を提案する．本論文では，従来のホームエージェントに対して3つの問題点を示した．1つ目は，家電操作には，操作代行を望む操作だけではなく，ユーザ自身の楽しみなどの理由により操作代行を望まない操作があることに注意していなかったことである．2つ目はホームエージェントの操作代行の信頼性に対するユーザの信頼感を考慮していなかったことである．3つ目は評価実験に時間がかかることである．第2章ではホームエージェントに関する研究について述べ，第1章で挙げた3つの問題点の分析を行う．第3章では，1つ目の問題点に対して，ユーザ自身が楽しむための操作の存在に着目し，ユーザの行為選好の推測方法を提案する．ただし，ユーザの行為選好はユーザの考え方のため，ホームエージェントは知り得ない．そのため，ユーザが行為選好をホームエージェントに指示する必要があるが，ユーザが必ず行為選好を指示するとは限らない．そこで，ホームエージェントがユーザの行為選好を推測する方法を示す．さらに，ユーザの行為選好の推測方法については，ホームエージェントへの適用事例を示す．第4章では，2つ目の問題点に対して，ホームエージェントに対するユーザの信頼性の醸成方法について述べる．従来研究では，ユーザがホームエージェントの性能を見極め，ユーザから指示を出すという過程を通じて信頼感を醸成していくことが提案されている．しかし，ユーザがホームエージェントの予測内容を監視する必要があった．そこで，従来よりもホームエージェントの性能理解とユーザからの指示を容易にするために，人間同士での対話をまねることと，客観的な指標を取り入れ，信頼感の醸成方法の高度化と効率化を示す．第5章では，3つ目の問題点に対して，シミュレーションを用いた実効的な評価手法を提案する．評価実験にシミュレーションを用いることで，評価実験の短時間化ができる．しかし，シミュレーションでは実験者が想定できる典型ユーザでの評価になってしまう点とホームエージェントごとに評価環境を構築しなければならない点という問題があった．まず，被験者の多様性を拡大するためにアンケートに基づいたシミュレーションによる評価方法を示す．次に，一部の修正や追加によって評価環境を作成できるように，ホームエージェントの評価環境に必要な基本構造とする共通プラットフォームを示す．また，アンケートを取り入れることで様々な被験者で評価実験を行える評価方法を示す．第6章では，第5章で提案した評価方法を用いて行った第3章で示したユーザの行為選好の推測方法と第4章で示したホームエージェントの信頼感の醸成方法の高度化と効率化の検証について述べる．第7章では，本研究の成果をまとめ，今後の展望を述べる．以上のように，ユーザ目線を取り入れたホームエージェントの重要性を示し，複雑化するホームエージェントを効率的に評価する手法を提供した．電気通信大学201

Using machine learning for real-time activity recognition and estimation of energy expenditure

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 481-493).Obesity is now considered a global epidemic and is predicted to become the number one preventive health threat in the industrialized world. Presently, over 60% of the U.S. adult population is overweight and 30% is obese. This is of concern because obesity is linked to leading causes of death, such as heart and pulmonary diseases, stroke, and type 2 diabetes. The dramatic rise in obesity rates is attributed to an environment that provides easy access to high caloric food and drink and promotes low levels of physical activity. Unfortunately, many people have a poor understanding of their own daily energy (im)balance: the number of calories they consume from food compared with what they expend through physical activity. Accelerometers offer promise as an objective measure of physical activity. In prior work they have been used to estimate energy expenditure and activity type. This work further demonstrates how wireless accelerometers can be used for real-time automatic recognition of physical activity type, intensity, and duration and estimation of energy expenditure. The parameters of the algorithms such as type of classifier/regressor, feature set, window length, signal preprocessing, sensor set utilized and their placement on the human body are selected by performing a set of incremental experiments designed to identify sets of parameters that may balance system usability with robust, real-time performance in low processing power devices such as mobile phones. The algorithms implemented are evaluated using a dataset of examples of 52 activities collected from 20 participants at a gymnasium and a residential home. The algorithms presented here may ultimately allow for the development of mobile phone-based just-in-time interventions to increase self-awareness of physical activity patterns and increases in physical activity levels in real-time during free-living that scale to large populations.(cont.) KEYWORDS: Activity recognition, context awareness, energy expenditure, physical activity, wearable sensors, obesity, mobile phone, pattern recognition, machine learning, ubiquitous, pervasive, just-in-time.by Emmanuel Munguia Tapia.Ph.D