Smart Things im Internet der Dinge — ein Klassifikationsansatz

2017 ◽  
Vol 9 (2) ◽  
pp. 54-61 ◽  
Author(s):  
Louis Püschel ◽  
Maximilian Röglinger ◽  
Helen Schlott
Keyword(s):  
Internet Der Dinge ◽  
Smart Things

kma und WGKT gründen Kooperation: kma freut sich über weitere Vernetzung mit den Krankenhaustechnikern

2017 ◽  
Vol 22 (01) ◽  
pp. 9-9 ◽  
Keyword(s):  
Internet Der Dinge

Ob Medizin- oder Betriebstechnik, Hygiene oder Internet der Dinge – die Krankenhaustechnik ist ein Bereich, in dem Innovation und Pionierleistung auf der Tagesordnung stehen. Umso mehr freut sich die kma, die Wissenschaftliche Gesellschaft für Krankenhaustechnik (WGKT) als Kooperationspartner gewonnen zu haben.

Internet der Dinge: Wie schütze ich meinen Fahrstuhl vor Cyberpiraten?

2018 ◽  
Vol 23 (06) ◽  
pp. 49-51
Author(s):  
Michael Thoss
Keyword(s):  
Internet Der Dinge

Die Versorgungstechnik des Krankenhauses digitalisiert sich gerade. Ob Schranken, Heizungen, Jalousien oder Fahrstühle – alles wird perspektivisch online gesteuert. Das „Internet der Dinge“ bietet viele Chancen, aber auch Angriffsflächen: Fallen etwa Aufzüge einer Klinik durch eine Cyberattacke zwei Stunden aus, steht der Krankenhausbetrieb teilweise still.

Mit MindSphere die digitale Transformation vorantreiben

Controlling ◽  
2019 ◽  
Vol 31 (6) ◽  
pp. 63-65
Author(s):  
Carsten Speckmann ◽  
Péter Horváth
Keyword(s):  
Digitale Transformation ◽  
Internet Der Dinge ◽  
End To End

MindSphere ist das cloudbasierte, offene IoT-Betriebssystem von Siemens. Es verbindet Produkte, Anlagen, Systeme und Maschinen und ermöglicht es so, die Fülle von Daten aus dem Internet der Dinge (IoT) mit umfangreichen Analysen zu nutzen. Als eine sichere, skalierbare End-to-End-Lösung für die Industrie sorgt MindSphere für die Konnektivität von Anlagen und liefert somit handlungsrelevante Geschäftserkenntnisse, die zur Steigerung der Produktivität und Effizienz im gesamten Unternehmen nutzbar gemacht werden können. MindSphere ist weltweit verfügbar.

Smart toys, smart tangibles, robots and other smart things for children

2020 ◽  
Author(s):  
Alejandro Catala ◽  
Cristina Sylla ◽  
Arzu Guneysu Ozgur ◽  
Pirita Ihamäki ◽  
Katriina Heljakka
Keyword(s):  
Smart Things

Datenschutz im Internet der Dinge

2021 ◽  
Vol 45 (2) ◽  
pp. 114-119
Author(s):  
Marco Müller-ter Jung
Keyword(s):  
Internet Der Dinge

Deep learning based Blockchain solution for preserving privacy in future vehicles

2020 ◽  
pp. 1-14
Author(s):  
Varsha R ◽  
Meghna Manoj Nair ◽  
Siddharth M. Nair ◽  
Amit Kumar Tyagi
Keyword(s):  
Deep Learning ◽  
Autonomous Vehicles ◽  
Recommendation System ◽  
Privacy Preserving ◽  
Smart Devices ◽  
The Road ◽  
Blockchain Technology ◽  
Technological Advances ◽  
Previous Decade ◽  
Smart Things

The Internet of Things (smart things) is used in many sectors and applications due to recent technological advances. One of such application is in the transportation system, which is of primary use for the users to move from one place to another place. The smart devices which were embedded in vehicles are useful for the passengers to solve his/her query, wherein future vehicles will be fully automated to the advanced stage, i.e. future cars with driverless feature. These autonomous cars will help people a lot to reduce their time and increases their productivity in their respective (associated) business. In today’s generation and in the near future, privacy preserving and trust will be a major concern among users and autonomous vehicles and hence, this paper will be able to provide clarity for the same. Many attempts in previous decade have provided many efficient mechanisms, but they all work only with vehicles along with a driver. However, these mechanisms are not valid and useful for future vehicles. In this paper, we will use deep learning techniques for building trust using recommender systems and Blockchain technology for privacy preserving. We also maintain a certain level of trust via maintaining the highest level of privacy among users living in a particular environment. In this research, we developed a framework that could offer maximum trust or reliable communication to users over the road network. With this, we also preserve privacy of users during traveling, i.e., without revealing identity of respective users from Trusted Third Parties or even Location Based Service in reaching a destination. Thus, Deep Learning based Blockchain Solution (DLBS) is illustrated for providing an efficient recommendation system.

scholarly journals A DHT-Based Discovery Service for the Internet of Things

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Federica Paganelli ◽  
David Parlanti
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
Future Internet ◽  
Peer To Peer ◽  
The Internet ◽  
Dangerous Goods ◽  
Discovery Service ◽  
Single Attribute ◽  
Smart Things ◽  
The Internet Of Things

Current trends towards the Future Internet are envisaging the conception of novel services endowed with context-aware and autonomic capabilities to improve end users’ quality of life. The Internet of Things paradigm is expected to contribute towards this ambitious vision by proposing models and mechanisms enabling the creation of networks of “smart things” on a large scale. It is widely recognized that efficient mechanisms for discovering available resources and capabilities are required to realize such vision. The contribution of this work consists in a novel discovery service for the Internet of Things. The proposed solution adopts a peer-to-peer approach for guaranteeing scalability, robustness, and easy maintenance of the overall system. While most existing peer-to-peer discovery services proposed for the IoT support solely exact match queries on a single attribute (i.e., the object identifier), our solution can handle multiattribute and range queries. We defined a layered approach by distinguishing three main aspects: multiattribute indexing, range query support, peer-to-peer routing. We chose to adopt an over-DHT indexing scheme to guarantee ease of design and implementation principles. We report on the implementation of a Proof of Concept in a dangerous goods monitoring scenario, and, finally, we discuss test results for structural properties and query performance evaluation.

Durchgängiges Anforderungsmanagement und Engineering für Smart Grid Lösungen

2020 ◽  
Vol 68 (9) ◽  
pp. 711-719
Author(s):  
Mathias Uslar
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Cyber Physical Systems ◽  
Industrie 4.0 ◽  
Internet Der Dinge ◽  
Physical Systems

ZusammenfassungIn diesem Beitrag wird die Notwendigkeit einer sinnvollen Definition und Klarstellung der Disziplin Energieinformatik aufgezeigt. Der Beitrag diskutiert verschiedene bestehende Definitionen und stellt sie in den Kontext des Anforderungsmanagements und der Lösungsfindung. Er motiviert die Notwendigkeit eines strukturierten disziplinären Ansatzes in der Energieinformatik auf der Grundlage bestehender Probleme und skizziert den aktuellen Stand des Stands der Wissenschaft und Technik, der hauptsächlich den systemtechnischen Anwendungsbereich für Smart Grids umfasst. Synergien mit anderen aktuellen Schwerpunktthemen wie Internet der Dinge (IoT), Industrie 4.0 (Digitalisierung der Produktion) und Cyber-Physical Systems (CPS) werden aus Anforderungssicht motiviert. Auf der Grundlage der aufgeworfenen Fragen und Herausforderungen werden neue sinnvolle Forschungsthemen für ein durchgängiges Anforderungsmanagement im Kontext Smart Grid diskutiert.

A Fuzzy Logic-Based Method for Incorporating Ethics in the Internet of Things

2021 ◽  
Vol 12 (3) ◽  
pp. 98-122
Author(s):  
Sahil Sholla ◽  
Roohie Naaz Mir ◽  
Mohammad Ahsan Chishti
Keyword(s):  
Fuzzy Logic ◽  
Wide Spectrum ◽  
Research Direction ◽  
Smart Devices ◽  
Learning Mechanisms ◽  
Ethical Considerations ◽  
Smart Transportation ◽  
Smart Healthcare ◽  
Human Ethics ◽  
Smart Things

IoT is expected to have far-reaching consequences on society due to a wide spectrum of applications like smart healthcare, smart transportation, smart agriculture, smart home, etc. However, ethical considerations of AI-enabled smart devices have not been duly considered from a design perspective. In this paper, the authors propose a novel fuzzy logic-based method to incorporate ethics within smart things of IoT. Ethical considerations relevant to a machine context are represented in terms of fuzzy ethics variables (FEVs) and ethics rules. For each ethics rule, a value called scaled ethics value (SEV) is used to indicate its ethical desirability. In order to model flexibility in ethical response, the authors employ the concept of ethics modes that selectively allow scenarios depending on the value of SEV. The method offers a viable mechanism for smart devices to imbue ethical sensitivity that can pave the way for a technology society amenable to human ethics. However, the method does not account for varying ethics, as such incorporating learning mechanisms represent a promising research direction.

Sign in / Sign up

Export Citation Format

Share Document