A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

Evaluating a Personal Stress Monitoring System

Now-a-days, Life is generally much more stressful than in the past. Stress is the word that we use when we feel that we are overloaded mentally in our thoughts and wonder whether we can really cope with those placed upon us. Sometimes, stress gets us going and they are good for us but at other times, it could be the cause to undermine both our mental and physical health. The way we respond to a challenge can be considered as a kind of stress. Part of our response to a challenge is physiological and affects our own physical state. When we are faced with a challenge or a threat, our body releases some resources to protect us against them - either to get away as fast as we can, or to fight against them. This fight-or-flight response is our body\u27s sympathetic nervous system reacting to a stressful event. During this response, our body produces larger quantities of the chemicals such as cortisol, adrenaline and noradrenaline, which triggers a higher heart rate, heightened muscle preparedness, sweating, and alertness. All these factors help us to protect ourselves in a dangerous or challenging situation. But based on the frequency of stress facing by a person, these changes may affect his or her health negatively. In order to evaluate an individual\u27s stress, I worked on this thesis in developing a personal stress monitoring system to capture the stress undergoing by an individual in his or her daily life

LookBook: pioneering Inclusive beauty with artificial intelligence and machine learning algorithms

Technology's imperfections and biases inherited from historical norms are crucial to acknowledge. Rapid perpetuation and amplification of these biases necessitate transparency and proactive measures to mitigate their impact. The online visual culture reinforces Eurocentric beauty ideals through prioritized algorithms and augmented reality filters, distorting reality and perpetuating unrealistic standards of beauty. Narrow beauty standards in technology pose a significant challenge to overcome. Algorithms personalize content, creating "filter bubbles" that reinforce these ideals and limit exposure to diverse representations of beauty. This cycle compels individuals to conform, hindering the embrace of their unique features and alternative definitions of beauty. LookBook counters prevalent narrow beauty standards in technology. It promotes inclusivity and representation through self-expression, community engagement, and diverse visibility. LookBook comprises three core sections: Dash, Books, and Community. In Dash, users curate their experience through personalization algorithms. Books allow users to collect curated content for inspiration and creativity, while Community fosters connections with like-minded individuals. Through LookBook, users create a reality aligned with their unique vision. They control consumed content, nurturing individualism through preferences and creativity. This personalization empowers individuals to break free from narrow beauty standards and embrace their distinctiveness. LookBook stands out with its algorithmic training and data representation. It offers transparency on how personalization algorithms operate and ensures a balanced and diverse representation of physicalities and ethnicities. By addressing biases and embracing a wide range of identities, LookBook sparks a conversation for a technology landscape that amplifies all voices, fostering an environment celebrating diversity and prioritizing inclusivity

Active aging in place supported by caregiver-centered modular low-cost platform

Aging in place happens when people age in the residence of their choice, usually their homes because is their preference for living as long as possible. This research work is focused on the conceptualization and implementation of a platform to support active aging in place with a particular focus on the caregivers and their requirements to accomplish their tasks with comfort and supervision. An engagement dimension is also a plus provided by the platform since it supports modules to make people react to challenges, stimulating them to be naturally more active. The platform is supported by IoT, using low-cost technology to increment the platform modularly. Is a modular platform capable of responding to specific needs of seniors aging in place and their caregivers, obtaining data regarding the person under supervision, as well as providing conditions for constant and more effective monitoring, through modules and tools that support decision making and tasks realization for active living. The constant monitoring allows knowing the routine of daily activities of the senior. The use of machine learning techniques allows the platform to identify, in real-time, situations of potential risk, allowing to trigger triage processes with the older adult, and consequently trigger the necessary actions so that the caregiver can intervene in useful time.O envelhecimento no local acontece quando as pessoas envelhecem na residência da sua escolha, geralmente nas suas próprias casas porque é a sua preferência para viver o máximo de tempo possível. Este trabalho de investigação foca-se na conceptualização e implementação de uma plataforma de apoio ao envelhecimento ativo no local, com particular enfoque nos cuidadores e nas suas necessidades para cumprir as suas tarefas com conforto e supervisão. Uma dimensão de engajamento também é um diferencial da plataforma, pois esta integra módulos de desafios para fazer as pessoas reagirem aos mesmos, estimulando-as a serem naturalmente mais ativas. A plataforma é suportada por IoT, utilizando tecnologia de baixo custo para incrementar a plataforma de forma modular. É uma plataforma modular capaz de responder às necessidades específicas do envelhecimento dos idosos no local e dos seus cuidadores, obtendo dados relativos à pessoa sob supervisão, bem como fornecendo condições para um acompanhamento constante e mais eficaz, através de módulos e ferramentas que apoiam a tomada de decisões e realização de tarefas para a vida ativa. A monitorização constante permite conhecer a rotina das atividades diárias do idoso, permitindo que, com a utilização de técnicas de machine learning, a plataforma seja capaz de detetar em tempo real situações de risco potencial, permitindo desencadear um processo de triagem junto do idoso, e consequentemente despoletar as ações necessárias para que o prestador de cuidados possa intervir em tempo útil

Exploring user-defined gestures for alternate interaction space for smartphones and smartwatches

2016 Spring.Includes bibliographical references.In smartphones and smartwatches, the input space is limited due to their small form factor. Although many studies have highlighted the possibility of expanding the interaction space for these devices, limited work has been conducted on exploring end-user preferences for gestures in the proposed interaction spaces. In this dissertation, I present the results of two elicitation studies that explore end-user preferences for creating gestures in the proposed alternate interaction spaces for smartphones and smartwatches. Using the data collected from the two elicitation studies, I present gestures preferred by end-users for common tasks that can be performed using smartphones and smartwatches. I also present the end-user mental models for interaction in proposed interaction spaces for these devices, and highlight common user motivations and preferences for suggested gestures. Based on the findings, I present design implications for incorporating the proposed alternate interaction spaces for smartphones and smartwatches

Personal State and Emotion Monitoring by Wearable Computing and Machine Learning

One of the major scientific undertakings over the past few years has been exploring the interaction between humans and machines in mobile environments. Wearable computers, embedded in clothing or seamlessly integrated into everyday devices, have an incredible advantage to become the main gateway to personal health management. Current state of the art devices are capable in monitoring basic physical or physiological parameters. Traditional health systems procedures depend on the physical presence of the patient and a medical specialist that not only is a reason of overall costs but also reduces the quality of patients' lives, particularly elderly patients. Usually, patients have to go through the following steps for the traditional procedure: Firstly, patients need to visit the clinic, get registered at reception, wait for the turn, go to the lab for the physiological measurement, wait for the medical experts call, to finally receive feedback from the medical expert. In this work, we examined how to utilize existing technology in order to develop an e-health monitoring system especially for heart patients. This system should support the interaction between the patient and the physician even when the patient is not in the clinic. The supporting wearable health monitoring system WHMS should recognize physical activities, emotional states and transmit this information to the physician along with relevant physiological data; in this way patients do not need to visit the clinic every time for the physician's feed-back. After the discussion with medical experts, we identified relevant physical activities, emotional states and physiological data needed for the patients' examinations. A prototype of this concept for a health monitoring system of the proposed solution was implemented taking into account physical activities, emotional states and physiological data

IoT Platform for COVID-19 Prevention and Control: A Survey

As a result of the worldwide transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has evolved into an unprecedented pandemic. Currently, with unavailable pharmaceutical treatments and vaccines, this novel coronavirus results in a great impact on public health, human society, and global economy, which is likely to last for many years. One of the lessons learned from the COVID-19 pandemic is that a long-term system with non-pharmaceutical interventions for preventing and controlling new infectious diseases is desirable to be implemented. Internet of things (IoT) platform is preferred to be utilized to achieve this goal, due to its ubiquitous sensing ability and seamless connectivity. IoT technology is changing our lives through smart healthcare, smart home, and smart city, which aims to build a more convenient and intelligent community. This paper presents how the IoT could be incorporated into the epidemic prevention and control system. Specifically, we demonstrate a potential fog-cloud combined IoT platform that can be used in the systematic and intelligent COVID-19 prevention and control, which involves five interventions including COVID-19 Symptom Diagnosis, Quarantine Monitoring, Contact Tracing & Social Distancing, COVID-19 Outbreak Forecasting, and SARS-CoV-2 Mutation Tracking. We investigate and review the state-of-the-art literatures of these five interventions to present the capabilities of IoT in countering against the current COVID-19 pandemic or future infectious disease epidemics.Comment: 12 pages; Submitted to IEEE Internet of Things Journa

Assisting Human Motion-Tasks with Minimal, Real-time Feedback

Teaching physical motions such as riding, exercising, swimming, etc. to human beings is hard. Coaches face difficulties in communicating their feedback verbally and cannot correct the student mid-action; teaching videos are two dimensional and suffer from perspective distortion. Systems that track a user and provide him real-time feedback have many potential applications: as an aid to the visually challenged, improving rehabilitation, improving exercise routines such as weight training or yoga, teaching new motion tasks, synchronizing motions of multiple actors, etc. It is not easy to deliver real-time feedback in a way that is easy to interpret, yet unobtrusive enough to not distract the user from the motion task. I have developed motion feedback systems that provide real-time feedback to achieve or improve human motion tasks. These systems track the user\u27s actions with simple sensors, and use tiny vibration motors as feedback devices. Vibration motors provide feedback that is both intuitive and minimally intrusive. My systems\u27 designs are simple, flexible, and extensible to large-scale, full-body motion tasks. The systems that I developed as part of this thesis address two classes of motion tasks: configuration tasks and trajectory tasks. Configuration tasks guide the user to a target configuration. My systems for configuration tasks use a motion-capture system to track the user. Configuration-task systems restrict the user\u27s motions to a set of motion primitives, and guide the user to the target configuration by executing a sequence of motion-primitives. Trajectory tasks assume that the user understands the motion task. The systems for trajectory tasks provide corrective feedback that assists the user in improving their performance. This thesis presents the design, implementation, and results of user experiments with the prototype systems I have developed

Beware the Pitfalls. A short guide to Avoiding Common Errors in Systems Analysis

The interest in systems analysis, which is now worldwide, is not hard to understand. Analyzing systems of various kinds has helped to solve some important social, economic, and environmental problems, and it has thrown light on others that must eventually be solved. As an aid to establishing policy, systems analysis has been particularly useful where matters are complex, where objectives conflict, and where future planning is difficult. Analysts tend to evaluate their studies on technical adequacy; decision makers stress practical results. The editors of "Pitfalls of Analysis" saw both types of standards as important and related. They organized their material to present first some common pitfalls of technical adequacy and then some common pitfalls of effectiveness