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Internet of Things Meets Brain-Computer Interface: a Unified Deep Learning Framework for Enabling Human-Thing Cognitive Interactivity
JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 1 Internet of Things Meets Brain-Computer Interface: A Unified Deep Learning Framework for Enabling Human-Thing Cognitive Interactivity Xiang Zhang, Student Member, IEEE, Lina Yao, Member, IEEE, Shuai Zhang, Student Member, IEEE, Salil Kanhere, Member, IEEE, Michael Sheng, Member, IEEE, and Yunhao Liu, Fellow, IEEE Abstract—A Brain-Computer Interface (BCI) acquires brain signals, analyzes and translates them into commands that are relayed to actuation devices for carrying out desired actions. With the widespread connectivity of everyday devices realized by the advent of the Internet of Things (IoT), BCI can empower individuals to directly control objects such as smart home appliances or assistive robots, directly via their thoughts. However, realization of this vision is faced with a number of challenges, most importantly being the issue of accurately interpreting the intent of the individual from the raw brain signals that are often of low fidelity and subject to noise. Moreover, pre-processing brain signals and the subsequent feature engineering are both time-consuming and highly reliant on human domain expertise. To address the aforementioned issues, in this paper, we propose a unified deep learning based framework that enables effective human-thing cognitive interactivity in order to bridge individuals and IoT objects. We design a reinforcement learning based Selective Attention Mechanism (SAM) to discover the distinctive features from the input brain signals. In addition, we propose a modified Long Short-Term Memory (LSTM) to distinguish the inter-dimensional information forwarded from the SAM. To evaluate the efficiency of the proposed framework, we conduct extensive real-world experiments and demonstrate that our model outperforms a number of competitive state-of-the-art baselines. -
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Designing transparent display experience through the use of kinetic interaction A Master’s Thesis by Interaction Design Master’s Programme Rafael Rybczyński School of Arts and Communication (K3) Malmö University, Sweden August 2017 MSwedenugust 2017 Designing transparent display experience through the use of kinetic interaction Interaction Design Master’s Programme School of Arts and Communication (K3) Malmö University, Sweden August 2017 Author: Rafael Rybczyński Supervisor: Susan Kozel Examiner: Clint Heyer Thesis Project I 15 credits 2017 Acknowledgements Over the lengths of this thesis project I have received support and encouragement from a many people. First of all, I would like to thank my supervisor Susan Kozel for advising me to trust my own instinct. Moreover I would like humbly to thank all the participants without whom this project would not have been possible. Also humbly I thank Alvar, Sanna, and Susanne for shelter and feedback. For proofreading my thanks goes to Jan Felix Rybczyński and Sanna Minkkinen. Finally, my deepest gratitude is reserved to my father Dr. med. Jerzy Antoni Rybczyński. Rest in peace. I would have wished for you reading this paper. Author’s notes Often during the process of doing this study I was asked why transparent displays. What’s the point? Probably I would say this goes way back to my childhood when enjoying my father reading novel stories to us as good night stories. A good example of great stories was Scheerbart’s utopian architectural vision The Gray Cloth who told about the great Swiss architect who traveled by an airship. Wherever he went, he designed buildings made from brightly colored glass, including the roof. -
The Zeitgeist Movement Defined
THE ZEITGEIST MOVEMENT DEFINED REALIZING A NEW TRAIN OF THOUGHT ”The tremendous and still accelerating development of science and technology has not been accompanied by an equal development in social, economic, and political patterns...We are now...only beginning to explore the potentialities which it offers for developments in our culture outside technology, particularly in the social, political and economic fields. It is safe to predict that...such social inventions as modern-type Capitalism, Fascism, and Communism will be regarded as primitive experiments directed toward the adjustment of modern society to modern technology” - Dr. Ralph Linton www.thezeitgeistmovement.com The Zeitgeist Movement Defined Realizing a New Train of Thought 1st Edition, January, 2014 Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) The content in this text may be reproduced only for non-commercial purposes and may not be resold in any form. Any other interests require direct approval by TZM Global. Contact: [email protected] This is a 100% non-profit text. Any price paid is only for the physical publishing. Any exploitation of this work for profit will not be tolerated. Acknowledgments: The material authored here is the product of many forms of contribution, specifically the research of The Zeitgeist Movement's expanding lecture team. An enormous thanks extends to all who have contributed news, sources, tips and other forms of research. If you would like to help in translating this text, please contact TZM's linguistics team: [email protected] ISBN-13: 978-1495303197 ISBN-10: 1495303195 Contents Preface ................................................................................................... 1 Part I: Introduction Essay 1: Overview .................................................................................. -
The Internet of Things (Iot): an Overview
Updated February 12, 2020 The Internet of Things (IoT): An Overview The Internet of Things (IoT) is a system of interrelated incorporation of IIoT and analytics is viewed by experts as devices connected to a network and/or to one another, the Fourth Industrial Revolution, or 4IR. exchanging data without necessarily requiring human-to- machine interaction. In other words, IoT is a collection of Internet of Medical Things (IoMT): The healthcare field electronic devices that can share information among has begun incorporating IoT, creating the Internet of themselves. Examples include smart factories, smart home Medical Things (IoMT). These devices, such as heart devices, medical monitoring devices, wearable fitness monitors and pace makers, collect and send patient health trackers, smart city infrastructures, and vehicular statistics over various networks to healthcare providers for telematics. Potential issues for Congress include regulation, monitoring, analysis, and remote configuration. At a digital privacy, and data security as discussed below. personal health level, wearable IoT devices, such as fitness trackers and smart watches, can track a user’s physical IoT Characteristics activities, basic vital data, and sleeping patterns. According IoT devices are often called “smart” devices because they to a 2019 survey by Pew Research, about one-in-five have sensors and can conduct complex data analytics. IoT Americans uses a smart watch or fitness tracker. devices collect data using sensors and offer services to the user based on the analyses of that data and according to Smart Cities: IoT devices and systems in the utilities, user-defined parameters. For example, a smart refrigerator transportation, and infrastructure sectors may be grouped uses sensors (e.g., cameras) to inventory stored items and under the category of “smart city.” Utilities can use IoT to can alert the user when items run low based on image create “smart” grids and meters for electricity, water, and recognition analyses. -
Fog Computing: a Platform for Internet of Things and Analytics
Fog Computing: A Platform for Internet of Things and Analytics Flavio Bonomi, Rodolfo Milito, Preethi Natarajan and Jiang Zhu Abstract Internet of Things (IoT) brings more than an explosive proliferation of endpoints. It is disruptive in several ways. In this chapter we examine those disrup- tions, and propose a hierarchical distributed architecture that extends from the edge of the network to the core nicknamed Fog Computing. In particular, we pay attention to a new dimension that IoT adds to Big Data and Analytics: a massively distributed number of sources at the edge. 1 Introduction The “pay-as-you-go” Cloud Computing model is an efficient alternative to owning and managing private data centers (DCs) for customers facing Web applications and batch processing. Several factors contribute to the economy of scale of mega DCs: higher predictability of massive aggregation, which allows higher utilization with- out degrading performance; convenient location that takes advantage of inexpensive power; and lower OPEX achieved through the deployment of homogeneous compute, storage, and networking components. Cloud computing frees the enterprise and the end user from the specification of many details. This bliss becomes a problem for latency-sensitive applications, which require nodes in the vicinity to meet their delay requirements. An emerging wave of Internet deployments, most notably the Internet of Things (IoTs), requires mobility support and geo-distribution in addition to location awareness and low latency. We argue that a new platform is needed to meet these requirements; a platform we call Fog Computing [1]. We also claim that rather than cannibalizing Cloud Computing, F. Bonomi R. -
The Internet of Things: Impact on Public Safety Communications
Cybersecurity and Infrastructure Security Agency The Internet of Things March 2019 The Internet of Things: Impact on Public Safety Communications The Internet of Things (IoT) is the network of physical devices and connectivity that enables objects to connect to one another, to the Internet, and exchange data amongst themselves.1, 2 IoT allows connected devices to be sensed or controlled remotely across network infrastructures, creating opportunities for more direct, cross-platform integration and improved efficiencies for the transfer of data between devices. IoT presents undeniable implications for public safety IoT goes beyond simply connecting communications. In turn, comprehensively addressing the objects to the Internet; it allows ever-growing IoT environment presents a unique challenge to physical objects to intelligently self- service providers, equipment manufacturers, and consumers. identify and communicate with other Harnessing network architecture changes and equipping devices, creating a new model of everyday objects to be IoT-enabled will allow public safety information sharing with a variety of stakeholders to maximize existing infrastructure investments potential applications. and provide near-real time decision support experiences that can change how they operate. IoT Benefits IoT-enabled devices can provide numerous benefits to public safety, as shown in Table 1. For example, a traffic accident response team could use the data collected from a variety of Internet-connected devices ― such as the involved vehicles (e.g., -
Home Automation System Using Google Assistant
© 2021 JETIR June 2021, Volume 8, Issue 6 www.jetir.org (ISSN-2349-5162) HOME AUTOMATION SYSTEM USING GOOGLE ASSISTANT MUDASIR M, NEHA V, NIHAAL THATHIR K, PAVAN YADAV M, POLLARPU SREERAMULU, SMITHA PATIL B.Tech. Student, Department of Computer Science and Engineering, Presidency University, Bangalore, India B.Tech. Student, Department of Computer Science and Engineering, Presidency University, Bangalore, India B.Tech. Student, Department of Computer Science and Engineering, Presidency University, Bangalore, India B.Tech. Student, Department of Computer Science and Engineering, Presidency University, Bangalore, India B.Tech. Student, Department of Computer Science and Engineering, Presidency University, Bangalore, India Assistant Professor, Department of Computer Science and Engineering, Presidency University, Bangalore, India Abstract: Nowadays Technology keeps on upgrading. The idea behind Google assistant-controlled Home automation is to control home devices with voice. On the market there are many devices available to do that, but making our own is awesome. In this project, the Google assistant requires voice commands. Adafruit account which is a cloud based free IoT web server used to create virtual switches, is linking to IFTTT website abbreviated as “If This Than That” which is used to create if else conditional statements. The voice commands for Google assistant have been added through IFTTT website. In this home automation, as the user gives commands to the Google assistant, Home appliances like Bulb, Fan and Motor etc., can be controlled accordingly. The commands given through the Google assistant are decoded and then sent to the microcontroller, the microcontroller in turn control the relays connected to it. The device connected to the respective relay can be turned ON or OFF as per the users request to the Google Assistant. -
Openfog Reference Architecture for Fog Computing
OpenFog Reference Architecture for Fog Computing Produced by the OpenFog Consortium Architecture Working Group www.OpenFogConsortium.org February 2017 1 OPFRA001.020817 © OpenFog Consortium. All rights reserved. Use of this Document Copyright © 2017 OpenFog Consortium. All rights reserved. Published in the USA. Published February 2017. This is an OpenFog Consortium document and is to be used in accordance with the terms and conditions set forth below. The information contained in this document is subject to change without notice. The information in this publication was developed under the OpenFog Consortium Intellectual Property Rights policy and is provided as is. OpenFog Consortium makes no representations or warranties of any kind with respect to the information in this publication, and specifically disclaims implied warranties of fitness for a particular purpose. This document contains content that is protected by copyright. Copying or distributing the content from this document without permission is prohibited. OpenFog Consortium and the OpenFog Consortium logo are registered trademarks of OpenFog Consortium in the United States and other countries. All other trademarks used herein are the property of their respective owners. Acknowledgements The OpenFog Reference Architecture is the product of the OpenFog Architecture Workgroup, co-chaired by Charles Byers (Cisco) and Robert Swanson (Intel). It represents the collaborative work of the global membership of the OpenFog Consortium. We wish to thank these organizations for contributing -
Swarm Robotics Applications Using Argos and Mavproxy |
WHITE PAPER Autonomous Swarms in Active Services Abstract Robotics has evolved across multiple industry segments, from manufacturing to advanced technology, surveillance, and disaster management. Typically, robotics-driven processes are characterized by a set of pre-defined requirements and operations, carried out by individual robots (bots), and performed at an accelerated pace. However, collective decision making by autonomous intelligent robots, leveraging the concepts of machine learning and artificial intelligence (AI), is becoming increasingly important for agile operations. Technological advances have helped realize swarm operations, in which autonomous bots work in a coordinated manner to effectively execute tasks. In this paper, we propose the approach, design, and implementation of a robot swarm ecosystem that enables: n Active servicing: Collective decision making and execution to solve problems n Collaboration: Automated swarm response to priority services, without external directives n Automaticity: Leveraging blockchain for real- time processing of services being advertised as well as exchange of information WHITE PAPER Autonomous Swarms: Current Trends and Challenges The robotics landscape is rapidly evolving, with bots already being deployed for enterprise operations, commercial purposes, home automation and industrial applications. Robot swarms are being leveraged across segments including retail, travel, healthcare, manufacturing and semiconductors, for a variety of use cases. These swarms are being enabled with the autonomy to operate independently once a preset task or a passive service is assigned, leading to an evolved ecosystem of autonomous nodes or swarms. However, autonomous nodes/swarms executing passive services have two specific failure points. One is central management and the other is a non-configurable preset task. De-centralized management is a viable option, but it only scales down the risk and does not eliminate the point of failure. -
Automated Restaurant Service Management System
Proceedings of National Level E-Conference on "Science & Technology" Organized by Shahajirao Patil Vikas Pratishthan's S. B. PATIL College of Engineering Indapur, Maharashtra, India INTERNATIONAL JOURNAL OF INNOVATIONS IN ENGINEERING RESEARCH AND TECHNOLOGY [IJIERT] ISSN No.: 2394-3696, Website: ijiert.org, Held on 15th and 16th June 2020. AUTOMATED RESTAURANT SERVICE MANAGEMENT SYSTEM Kalpesh V. Joshi, Akshay P. Dhawale, Chinmay Y. Dhekane, Kshitij S. Dhone, Mugdha P. Dhopade, Vipul P. Dhopate, Aditya S. Dhotarkar Department of Engineering, Sciences and Humanities (DESH) Abstract — Today, in the era of rapid advancement in the especially in the developed and developing nations. technology, the world attempts to automate every possible task ensuring ease to human life with improved work- II. LITERATURE REVIEW efficiency and quality [1]. This report describes in detail the It is common if customers complain for not feeling satisfied design, development and functionality of a Smart On-Floor about the services offered there are many reasons leading to Service Management System developed exclusively for the feeling of dissatisfaction including being entertain late in restaurants. The system comprises of an online wireless terms of order taken by the waiter and meals serving the issue module enabling the customers to order food from the of being late entertain could be solved with the help of the comfort of their respective tables via tablet phones; and a advancement in the technologies of the communication [1]. In robot for delivering the dishes to the customers at their accordance, this study initiates an integrated a networked respective tables. The order once placed and confirmed by system, with the focus is on its ability to solve the above the customers will be directed to the kitchen on a LCD describe limitation in order taking [2]. -
Predictive Analysis of 3D Reram-Based PUF for Securing the Internet of Things
Predictive Analysis of 3D ReRAM-based PUF for Securing the Internet of Things Jeeson Kim Hussein Nili School of Engineering Electrical and Computer Engineering RMIT University University of California Santa Barbara Melbourne, Australia Santa Barbara, USA [email protected] [email protected] Gina C. Adam Nhan Duy Truong Electrical and Computer Engineering School of Engineering University of California Santa Barbara RMIT University Santa Barbara, USA Melbourne, Australia gina [email protected] [email protected] Dmitri B. Strukov Omid Kavehei Electrical and Computer Engineering Electrical and Information Engineering University of California Santa Barbara The University of Sydney Santa Barbara, USA Sydney, Australia [email protected] [email protected] Abstract—In recent years, an explosion of IoT devices challenge [2, 3]. Widely used traditional cryptographic and its use leads threats to the privacy and security solutions, for example, advanced encryption standard concerns of individual users and merchandises. As one (AES) and elliptic curve cryptography (ECC), can be of promising solutions, physical unclonable function (PUF) has been extensively studied. This paper investigates quality used for both the integrity and the authentication of of randomness in the first generation of 3D analog ReRAM exchanging data and messages. PUF primitives using measured and gathered data from IoT hardware anti-counterfeiting, integrated circuit fabricated ReRAM crossbars. This study is significant as (IC) trust and physical tampering are also critical the randomness quality of a PUF directly relates to its tasks [4]. In 2014, defense advanced research projects resilience against various model-building attacks, includ- ing machine learning attack. -
Smart Dust Technology
250, Mini-Project Report Amy Haas Smart Dust Technology Smart dust is an emerging technology with a huge potential for becoming an internationally successful commercial venture. Now is the best time to invest in smart dust – right at the point at which the scientific community is close to perfecting the technology and its applications but its potential has not yet been realized by the capitalist market. Fundamental Concept Smart dust is a theoretical concept of a tiny wireless sensor network, made up of microelectromechanical sensors (called MEMS), robots, or devices, usually referred to as motes, that have self-contained sensing, computation, communication and power1. According to the smart dust project design created by a team of UC Berkeley researchers2, within each of these motes is an integrated package of “MEMS sensors, a semiconductor laser diode and MEMS beam-steering mirror for active optical transmission, a MEMS corner-cube retroreflector for passive optical transmission, an optical receiver, signalprocessing and control circuitry, and a power source based on thick-film batteries and solar cells.” The intent is that these motes will eventually become the size of a grain of sand or a dust particle, hence the name “smart dust”, but the technology still has a long way to go to achieve its target size. In current sensor technology, the sensors are about the size of a bottle cap or small coin. As with most electronic devices or technologies, the biggest challenges in achieving actual smart dust are the power consumption issues and making the batteries small enough. Although there is a lot of work being done on solar cells to keep the motes self-sustaining, the components are just not small enough yet to actually be considered smart dust.