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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. -
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. -
Skates and Rays Diversity, Exploration and Conservation – Case-Study of the Thornback Ray, Raja Clavata
UNIVERSIDADE DE LISBOA FACULDADE DE CIÊNCIAS DEPARTAMENTO DE BIOLOGIA ANIMAL SKATES AND RAYS DIVERSITY, EXPLORATION AND CONSERVATION – CASE-STUDY OF THE THORNBACK RAY, RAJA CLAVATA Bárbara Marques Serra Pereira Doutoramento em Ciências do Mar 2010 UNIVERSIDADE DE LISBOA FACULDADE DE CIÊNCIAS DEPARTAMENTO DE BIOLOGIA ANIMAL SKATES AND RAYS DIVERSITY, EXPLORATION AND CONSERVATION – CASE-STUDY OF THE THORNBACK RAY, RAJA CLAVATA Bárbara Marques Serra Pereira Tese orientada por Professor Auxiliar com Agregação Leonel Serrano Gordo e Investigadora Auxiliar Ivone Figueiredo Doutoramento em Ciências do Mar 2010 The research reported in this thesis was carried out at the Instituto de Investigação das Pescas e do Mar (IPIMAR - INRB), Unidade de Recursos Marinhos e Sustentabilidade. This research was funded by Fundação para a Ciência e a Tecnologia (FCT) through a PhD grant (SFRH/BD/23777/2005) and the research project EU Data Collection/DCR (PNAB). Skates and rays diversity, exploration and conservation | Table of Contents Table of Contents List of Figures ............................................................................................................................. i List of Tables ............................................................................................................................. v List of Abbreviations ............................................................................................................. viii Agradecimentos ........................................................................................................................ -
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 -
Trinity Iot Product Catalogue
IoT Devices TRINITY IOT PRODUCT CATALOGUE Teltonika Device Range 2021 TABLE OF CONTENTS 1 RUT950 27 TRB142 3 RUT955 29 TRB145 5 RUTX09 31 RUTX10 7 RUTX11 33 RUTX12 9 TRB141 35 RUTX08 11 RUT230 37 TRB255 13 RUT240 39 FMB920 15 RUT850 41 RUTXR1 17 RUT900 43 FM130 19 GH5200 45 BLUE SLIM ID 21 TRB245 47 BLUE COIN MAG 23 TSW100 49 BLUE COIN T 25 TRB140 PRODUCT SHEET / RUT950 ROUTER INTRODUCING RUT950 TRINITY APPROVED & SMART™ COMPATIBLE RUT950 is a highly reliable and secure LTE router for professional applications. Router delivers high performance, mission-critical cellular communication. RUT950 is equipped with connectivity redundancy through dual SIM failover. External antenna connectors make it possible to attach desired antennas and to easily find the best signal location. LTE LTE Cat4 Cat4 LTE Cat 4 with Dual SIM – significantly speeds up to 150 Mps reduce roaming costs WANLTE 4 LTEX failoverCat4 Cat4 Automatic switch to available 4x Ethernet ports backup connection with VLAN functionality LTE LTE Cat4 Cat4 Wireless Access Point Linux Powered with Hotspot functionality Simply order, and we’ll take care of the rest Source Import Test ICASA Management Onboarding 24/7 Platform Support www.trinity.co.za 1 PRODUCT SHEET / RUT950 ROUTER LAN Ethernet Ports WAN Ethernet Ports LTE antenna connectors Power socket WiFi antenna SIM card connectors slots Hardware Weight 256 g CPU Atheros Wasp, MIPS 74Kc, 550 MHz Memory 16 MBytes Flash, 128 MBytes DDR2 RAM Ethernet 4 x 10/100 Ethernet ports: 1 x WAN (configurable as LAN), 3 x LAN ports Power supply 9 -
Intelligent Edge Categories
2 TABLE OF CONTENTS © Copyright 2019 Daniel Sexton TABLE OF CONTENTS A TABLE OF CONTENTS Audience ...................................................................................................................................................... 1 Author’s Note ................................................................................................................................................ 2 Executive Summary ....................................................................................................................................... 5 Building An Intelligent Edge Strategy ............................................................................................................. 7 Edge Project Types .................................................................................................................................... 7 The Early Adopter’s Problem ....................................................................................................................... 9 Considering Life Cycles ........................................................................................................................... 9 The Strategy Box ..................................................................................................................................... 11 Intro to The Intelligent Edge........................................................................................................................ 13 What is The Edge? .................................................................................................................................. -
Technical Proposal for One Day Workshop on Fog and Edge
1 Technical Proposal for One Day Workshop on Fog and Edge Computing for Beyond IoT Services and Opportunities IEEE 7th World Forum on Internet of Things New Orleans, Louisiana, USA Workshop Title: Fog and Edge Computing for 6G Networks/IoT Services and Opportunities 1. Preamble As we evolve toward the Internet of Things (IoT), our 5G/6G and future mobile networks must support a much wider range of applications, including vehicular networking, automated man- ufacturing, smart cities, drones, smart grids, e-health, and the many emerging AI-enabled applications such as Virtual Reality (VR) and Augmented Reality (AR). The cloud computing plus communication pipe model is no longer adequate for supporting these emerging appli- cations. Connecting every device directly to the cloud can often be impractical due to factors such as limited resources on the devices, software and management complexity, limited net- work agility and cognition, and system scalability. In such scenarios, users will desire local services. Future mobile networks will also require computing capabilities inside or close to the radio access networks (RANs) to enable advanced networking capabilities, such as estab- lishing radio connections more timely and adjusting radio channel coding dynamically in re- sponse to changing user needs and communication environments, and allow user applica- tions to be hosted in the RANs that are closer to the users. These and the many other new requirements call for a new computing paradigm – fog/edge computing and networking. Fog/Edge envisions an open and standards-based horizontal ar- chitecture for distributing functions (from computing to storage to control and to networking functions) closer to users, not just to any specific type of network edge device but anywhere along the cloud-to-thing continuum that can best meet user requirements. -
The Second ACM/IEEE Symposium on Edge Computing October 12-14, 2017, San Jose, CA, USA
SEC 2017 The Second ACM/IEEE Symposium on Edge Computing October 12-14, 2017, San Jose, CA, USA http://acm-ieee-sec.org/2017/ “Edge computing” is new paradigm in which the resources of a small data center are placed at the edge of the Internet, in close proximity to mobile devices, sensors, end users, and the emerging Internet of Things. Terms such as “cloudlets,” “micro data centers,” and “fog” have been used in the literature to refer to these small, edge- located data centers. They all represent counterpoints to the theme of consolidation and massive data centers that has dominated discourse in cloud computing. New challenges and opportunities arise as the consolidation of cloud computing meets the dispersion of edge computing. Building upon the success of inaugural SEC, the organizing committee is delighted to invite you to Symposium on Edge Computing 2017, to be held in San Jose, California. General Chair Steering Committee Junshan Zhang, Arizona State University Victor Bahl, Microsoft Research Program Chairs Flavio Bonomi, IoXWorks Mung Chiang, Princeton University Rong Chang, IBM Research Bruce Maggs, Akamai/Duke University Dejan Milojicic, HP Labs Program Committee Michael Rabinovich, Case Western Reserve Eric Anderson, NIST University Rajesh Balan, Singapore Management University Weisong Shi, Wayne State University (chair) Bharath Balasubramanian, AT&T Labs Research Tao Zhang, Cisco Suman Banerjee, University of Wisconsin-Madison Local Arrangement Chair Songqing Chen, George Mason University Jerry Gao, San Jose State University Mung Chiang, Princeton University Romit Roy Choudhury, University of Illinois at Urbana- Finance and Registration Chair Champaign Qun Li, College of William & Mary Landon Cox, Duke University Sponsorship Chair Eduardo Cuervo, Microsoft Research Rong Chang, IBM Fred Douglis, Dell EMC Publicity Chairs Schahram Dustdar, TU Wien Schahram Dustdar, TU Wien, Austria Robert J. -
Broader Impacts
Maria Gorlatova, Princeton University: Broader Impacts BROADER IMPACTS Maria Gorlatova [email protected] Associate Research Scholar Princeton University My contributions and plans related to broader impacts fall under the categories of involvement in initiatives related to diversity and inclusion, ongoing and planned industry engagements, and plans to transform organizational practices with the developments in the Internet of Things. Diversity and Inclusion Initiatives I actively promote diversity and inclusion in my research group and within the broader scientific and technical communities, contributing to and leading multiple related initiatives. Aspects of my contributions to diversity have been recognized with a Google Anita Borg USA Fellowship, which is awarded yearly to only 25 students across all levels of studies and across all computing-related disciplines nation-wide, based on academic performance, leadership, and impact on the community of women in technology. I am contributing to and leading initiatives that create strong wide-reaching support networks between the members of under-represented groups. For instance, I was an invited participant in the MIT Rising Stars in EECS event that created a network of top graduate and post-doctoral women in Electrical Engineering and Computer Science. I also participated in the Google Graduate Researchers of Diverse Backgrounds CS Forum, which brought together graduate students of diverse backgrounds from different parts of United States and Canada. I am also currently serving on the board of the field-specific Networking Networking Women (N2 Women) organization that develops and strengthens the community of female researchers in communications and computer networking. Near-term I will lead the development of networks between the members of under-represented groups who work in my core research areas, Internet of Things and fog and edge computing.