Lotte Hotel aims to be a "smart hotel up to the latest date" by utilizing smartphone technology. They plan to develop a smartphone application that allows guests to access services like room control, customized information, and contactless payment. This "smart multi-purpose ubiquitous" system is meant to provide customers with convenience through features like keyless entry and a total solution interface. The goal is to offer high technology, reasonable prices, and customized service for a convenient and informative experience that encourages return visits.
This document discusses the role of compliance in security audits. It covers information security compliance and its relationship to reputation, regulation, revenue, resilience, and recession proofing. It provides an overview of ISO 27001, including its family of standards and steps for implementing an information security management system. Finally, it discusses common myths about ISO 27001 and memory techniques for quick revision like mnemonics, sentence aids, workflow diagrams, and color coding.
Presentation deck prepared for the paper 'Object Recognition-based Mnemonics Mobile App for Senior Adults Communication' to be presented during ICCCNT'15 conference
The document describes a project to develop smart glasses that help visually impaired people identify obstacles and recognize people using a Raspberry Pi, camera, and ultrasonic sensor. The glasses would take photos and compare them to a database to identify people by name or label them as unknown. An ultrasonic sensor would detect obstacles and their distance. The project aims to assist visually impaired people in daily tasks through a wearable device using computer vision techniques.
This document outlines Nicola Beddall-Hill's PhD research which uses mobile ethnographic methods to study student learning on higher education field trips. The research uses tools like head-mounted cameras and iPhones to collect video, photos, audio and other data on student interactions and technology use in the field. Challenges included the mobile setting and large amounts of qualitative data collected. Data was analyzed through storytelling, thematic analysis and mapping interactions over time and space. The research considers ethical issues in using these mobile methods and technologies for data collection and analysis.
Lifelogging, egocentric vision and health: how a small wearable camera can he...Petia Radeva
Petia Radeva discusses how lifelogging and wearable cameras can help improve health. Computer vision and deep learning techniques can be applied to extract useful information from large amounts of egocentric image data. Key information that can be derived includes what a person eats, where and with whom they eat, and how active they are. This type of quantified self-data has the potential to help manage health conditions like obesity, diabetes and migraines by identifying triggers and monitoring lifestyle factors and habits over time. Lifelogging also shows promise for cognitive treatment of patients with amnesia or mild cognitive impairment.
This document provides an overview of digital image processing (DIP) and discusses various topics related to it. It begins with welcoming remarks and introductions. It then discusses key areas of application for image processing like optical character recognition, security, compression, and medical imaging. Some main techniques covered include image acquisition, pre-processing, enhancement, segmentation, feature extraction, classification, and understanding. Application areas like remote sensing, astronomy, security, and OCR are also summarized. The document provides examples and illustrations of different image processing concepts.
Survey on Human Behavior Recognition using CNNIRJET Journal
This document discusses human behavior recognition using convolutional neural networks (CNNs). It first introduces the importance of human behavior recognition and some commonly used datasets. It then discusses related works that have used techniques like CNNs, LSTM networks, and R-CNN to recognize behaviors. The document proposes using the YOLOv3 algorithm to recognize behaviors in real-time video data. It describes the YOLOv3 algorithm and how it divides images into grids to predict boundary boxes and confidence scores for object detection. The goal is to automatically recognize human behaviors from video data using a CNN-based approach like YOLOv3 without manual annotation of training data.
Lotte Hotel aims to be a "smart hotel up to the latest date" by utilizing smartphone technology. They plan to develop a smartphone application that allows guests to access services like room control, customized information, and contactless payment. This "smart multi-purpose ubiquitous" system is meant to provide customers with convenience through features like keyless entry and a total solution interface. The goal is to offer high technology, reasonable prices, and customized service for a convenient and informative experience that encourages return visits.
This document discusses the role of compliance in security audits. It covers information security compliance and its relationship to reputation, regulation, revenue, resilience, and recession proofing. It provides an overview of ISO 27001, including its family of standards and steps for implementing an information security management system. Finally, it discusses common myths about ISO 27001 and memory techniques for quick revision like mnemonics, sentence aids, workflow diagrams, and color coding.
Presentation deck prepared for the paper 'Object Recognition-based Mnemonics Mobile App for Senior Adults Communication' to be presented during ICCCNT'15 conference
The document describes a project to develop smart glasses that help visually impaired people identify obstacles and recognize people using a Raspberry Pi, camera, and ultrasonic sensor. The glasses would take photos and compare them to a database to identify people by name or label them as unknown. An ultrasonic sensor would detect obstacles and their distance. The project aims to assist visually impaired people in daily tasks through a wearable device using computer vision techniques.
This document outlines Nicola Beddall-Hill's PhD research which uses mobile ethnographic methods to study student learning on higher education field trips. The research uses tools like head-mounted cameras and iPhones to collect video, photos, audio and other data on student interactions and technology use in the field. Challenges included the mobile setting and large amounts of qualitative data collected. Data was analyzed through storytelling, thematic analysis and mapping interactions over time and space. The research considers ethical issues in using these mobile methods and technologies for data collection and analysis.
Lifelogging, egocentric vision and health: how a small wearable camera can he...Petia Radeva
Petia Radeva discusses how lifelogging and wearable cameras can help improve health. Computer vision and deep learning techniques can be applied to extract useful information from large amounts of egocentric image data. Key information that can be derived includes what a person eats, where and with whom they eat, and how active they are. This type of quantified self-data has the potential to help manage health conditions like obesity, diabetes and migraines by identifying triggers and monitoring lifestyle factors and habits over time. Lifelogging also shows promise for cognitive treatment of patients with amnesia or mild cognitive impairment.
This document provides an overview of digital image processing (DIP) and discusses various topics related to it. It begins with welcoming remarks and introductions. It then discusses key areas of application for image processing like optical character recognition, security, compression, and medical imaging. Some main techniques covered include image acquisition, pre-processing, enhancement, segmentation, feature extraction, classification, and understanding. Application areas like remote sensing, astronomy, security, and OCR are also summarized. The document provides examples and illustrations of different image processing concepts.
Survey on Human Behavior Recognition using CNNIRJET Journal
This document discusses human behavior recognition using convolutional neural networks (CNNs). It first introduces the importance of human behavior recognition and some commonly used datasets. It then discusses related works that have used techniques like CNNs, LSTM networks, and R-CNN to recognize behaviors. The document proposes using the YOLOv3 algorithm to recognize behaviors in real-time video data. It describes the YOLOv3 algorithm and how it divides images into grids to predict boundary boxes and confidence scores for object detection. The goal is to automatically recognize human behaviors from video data using a CNN-based approach like YOLOv3 without manual annotation of training data.
The MOBISERV project developed an integrated intelligent home system to provide health, nutrition, and mobility services for older adults. The system included a robot, smart home automation, sensors in a smart garment, and communication with medical experts and caregivers. Extensive user research was conducted to develop the system requirements. The final prototype was tested with older adults, caregivers, and medical professionals. While acceptance of the technologies was good, the testing revealed issues with voice recognition, complex situation interpretation, and safety that require further work.
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We leverage neuroscientific algorithms and machine vision (initially in AR/VR and later in telemedical devices) to enable the early detection of:
- neurodevelopmental diseases like Alzheimer's, Parkinson's
- neurodegenerative diseases like autism and ADHD
... by building a “pulse watch for the brain”
The MOBISERV project developed an integrated intelligent home environment system to provide health, nutrition, and mobility services for older adults. The system included a robot, smart home automation and communication unit, smart garments for monitoring vital signs, and optical recognition. It was tested in homes and care facilities in several European countries. The results showed good system integration and functionality but also issues with voice recognition, complex situation interpretation, and safety that require further work.
This document discusses cyber-physical systems and the Internet of Things. It outlines Tata Consultancy Services' research programs in areas like mobile phone sensing, camera sensing, signal and image processing, and human activity detection using sensors. The goals are to develop an IoT platform for affordable healthcare and wellness solutions using mobile phones to detect physiological parameters. Research is also described on indoor localization, cognitive load detection using EEG, and emotion recognition using cameras. TCS has several innovation labs conducting exploratory research on mobile interactive remote sensing applications.
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IRJET- Assistant Systems for the Visually ImpairedIRJET Journal
This document describes a proposed system to assist the visually impaired using computer vision and audio assistance. It discusses how the system would use a camera on glasses or a cane to detect obstacles in the environment. The camera would capture images and use image processing techniques to identify foreground objects as obstacles. It would then generate audio commands through headphones to notify the user and guide them around obstacles. The document reviews several existing assistive technologies for the visually impaired and proposes a system that integrates object recognition, computer vision, and auditory assistance to help the blind navigate independently without external help.
Empowering People with Deafblindness - The SUITCEYES H2020 ProjectStratos Kontopoulos
Keynote presentation at the 7th ICEVI European Conference on Psychology and Visual Impairment, which took place 1-2 November 2018 in Thessaloniki, Greece.
The presentation introduces the 3-year H2020 project SUITCEYES, which is aimed at developing a garment that will appropriate smart textiles and IoT technologies in order to act as a communication interface for people with deafblindness.
Embedded Sensing and Computational Behaviour ScienceDaniel Roggen
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This document discusses using unobtrusive sensing to discover personal context through mobile phone sensors, 3D cameras, wearable devices, and online data. It describes sensing location, proximity, activity, identity, cognitive load, and physiological parameters to understand physical, individual, and community context. Example applications include customer behavior studies, crowdedness monitoring, wellness tracking, and organizational behavior analysis. The approach involves multimodal fusion of smartphone sensors, Kinect-style cameras, wearable EEG devices, and social media/email data to provide context discovery services while preserving user privacy.
This document discusses using unobtrusive sensing to discover personal context through mobile phone sensors, 3D cameras, wearable devices, and online data. It describes sensing location, proximity, activity, identity, cognitive load, and physiological parameters to understand physical, individual, and community context. Example applications include customer behavior studies, crowdedness monitoring, wellness tracking, and organizational behavior analysis. The approach uses smartphone sensors, Kinect-style cameras, and wearable EEGs, fusing data from multiple modalities while ensuring privacy.
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[EUC2014] cODA: An Open-Source Framework to Easily Design Context-Aware Andro...Matteo Ferroni
Mobile devices take an important part in everyday life. They are now cheaper and widespread, but still a lot of time is spent by the users to configure them: users adapt to their own device, not vice versa. Can our smartphones do something smarter? In this work, we propose a framework to support the development of context-aware applications for Android devices: the goal of such applications is to reduce as much as possible the interaction with the user, making use of automatic and intelligent components. Moreover, these components should consume as less power and computational resources as possible, being them part of a mobile ecosystem whose battery and hardware are highly constrained. The work implies the study of a methodology that fits the Android framework and the design of a highly extensible software architecture. An open-source framework based on the proposed methodology is then described. Some use cases are finally presented, analyzing the performances and the limitations of the proposed methodology.
Full paper: http://ieeexplore.ieee.org/abstract/document/6962264
Location aware apps: patterns and solutions - Ben Butchart - Jisc Digital Fes...Jisc
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This document outlines presentations on computer vision, robotics, and an image analysis paper. It discusses what computer vision and robotics are, provides examples of applications and challenges. It also summarizes a paper on using image analysis to classify Ethiopian coffee varieties by region. Key topics include face recognition, types of robots and their purposes, and examples like Shakey and wall-climbing robots. The future directions discussed include developing universal robots and improving visual recognition and manipulation abilities.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
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The MOBISERV project developed an integrated intelligent home system to provide health, nutrition, and mobility services for older adults. The system included a robot, smart home automation, sensors in a smart garment, and communication with medical experts and caregivers. Extensive user research was conducted to develop the system requirements. The final prototype was tested with older adults, caregivers, and medical professionals. While acceptance of the technologies was good, the testing revealed issues with voice recognition, complex situation interpretation, and safety that require further work.
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... by building a “pulse watch for the brain”
The MOBISERV project developed an integrated intelligent home environment system to provide health, nutrition, and mobility services for older adults. The system included a robot, smart home automation and communication unit, smart garments for monitoring vital signs, and optical recognition. It was tested in homes and care facilities in several European countries. The results showed good system integration and functionality but also issues with voice recognition, complex situation interpretation, and safety that require further work.
This document discusses cyber-physical systems and the Internet of Things. It outlines Tata Consultancy Services' research programs in areas like mobile phone sensing, camera sensing, signal and image processing, and human activity detection using sensors. The goals are to develop an IoT platform for affordable healthcare and wellness solutions using mobile phones to detect physiological parameters. Research is also described on indoor localization, cognitive load detection using EEG, and emotion recognition using cameras. TCS has several innovation labs conducting exploratory research on mobile interactive remote sensing applications.
This document discusses different types of sensors that can be used for wearable computing applications. It describes sensors for measuring physical context like location, activity, and environment as well as internal states like emotions and cognition. Both software sensors from data on devices and hardware sensors are covered. Specific sensor technologies discussed include accelerometers, gyroscopes, inertial measurement units, GPS, radio fingerprints, capacitive sensing, electrooculography, and skin conductance sensors. Examples are given of how sensor data can be fused and analyzed to infer higher level context and activities. Challenges of using sensors on the body are also addressed.
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This document describes a proposed system to assist the visually impaired using computer vision and audio assistance. It discusses how the system would use a camera on glasses or a cane to detect obstacles in the environment. The camera would capture images and use image processing techniques to identify foreground objects as obstacles. It would then generate audio commands through headphones to notify the user and guide them around obstacles. The document reviews several existing assistive technologies for the visually impaired and proposes a system that integrates object recognition, computer vision, and auditory assistance to help the blind navigate independently without external help.
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The presentation introduces the 3-year H2020 project SUITCEYES, which is aimed at developing a garment that will appropriate smart textiles and IoT technologies in order to act as a communication interface for people with deafblindness.
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This document discusses how crowdsourcing and smartphone technology can be used for environmental monitoring. It notes that while citizens can help with monitoring, issues around quality, coverage and sustainability must be addressed. The convergence of cheap sensors and social networks allows citizens to both consume and generate environmental data. However, there are concerns about "bad smart" technologies that limit autonomy through social engineering rather than enhance decision making. The document advocates for "good smart" crowdsourcing applications that promote problem solving and participation in environmental science.
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This document discusses using unobtrusive sensing to discover personal context through mobile phone sensors, 3D cameras, wearable devices, and online data. It describes sensing location, proximity, activity, identity, cognitive load, and physiological parameters to understand physical, individual, and community context. Example applications include customer behavior studies, crowdedness monitoring, wellness tracking, and organizational behavior analysis. The approach involves multimodal fusion of smartphone sensors, Kinect-style cameras, wearable EEG devices, and social media/email data to provide context discovery services while preserving user privacy.
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22. Father, don’t for
get your medicin
e
You looked good
! Thanks for the
great dinner!
It was nice to se
e you.
MESSAGES FROM PEOPLE IS EMBEDDED ON THE PICTURES
25. Issues on Triggering Photo(1)
• Option
– 1. Context Based snapshot
– 2. Periodical snapshot
• Trades off between options
– Personal Big data problem
• Storage Problem
• Too much data for person with dementia
– Sensor cost for capturing Context
• Energy consumption
• Device wearability
• Product price
26. Issues on Triggering Photo(2)
• Our solution
– Context Based snapshot with existing resources
• Key Idea
– To snapshot based on context information
– To utilize pre-existing resource such as smart phone
and snapshot device
28. Selective Snapshot
Based on Context Information(1)
• Snapshot trigger
– 1. Social Connection
• To log human social interaction
• Bluetooth connection using predefined contact
information
29. Selective Snapshot
Based on Context Information(2)
• Snapshot Trigger
– 2. Human Movement
• To log human location in the form of spatial
coordinates information and related snapshot
• To snapshot when there is change of the location
• Method to detect the location change in energy
efficient manner
– Predictive Location concept using predefined threshold
value
Youssef, Moustafa, Mohamed Amir Yosef, and Mohamed El-Derini.
"Gac: Energy-efficient hybrid gps-accelerometer-compass gsm
localization." Global Telecommunications Conference
(GLOBECOM 2010), 2010 IEEE. IEEE, 2010.
30. Life Log Data Management
• Auto diary App service for public and person with
dementia
• Auto backup service using cloud storage and Wi-Fi