FM-Based Outdoor Fingerprint Location Using DNN Algorithm for Large-Scale Internet of Things

Recent advances in wireless communication technologies and automobile industry have triggered a significant research interest in the field of Internet of Vehicles over the past few years.The advanced period of the Internet of Things is guiding the development of conventional Vehicular Networks to the Internet of Vehicles.In the days of Internet connectivity there is need to be in safe and problem-free environment.The Internet of Vehicles (IoV) is normally a mixing of three networks: an inter-vehicleNetwork, an intra-vehicle network, and a vehicle to vehicle network.Based on idea of three networks combining into one, we define Internet of Vehicles as a large-scale distributed system to wireless communication and information exchange between vehicle2X (X: vehicle, road, human and internet).It is a combined network for supporting intelligent traffic management, intelligent dynamic information service, and intelligent vehicle control, representation of an application of the Internet of Things (IoT) technology for intelligent transportation system (ITS).

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Analysis and Enhancement of IEEE 802.15.4e DSME Beacon Scheduling Model

Journal of Applied Mathematics ◽

10.1155/2014/934610 ◽

2014 ◽

Vol 2014 ◽

pp. 1-15 ◽

Cited By ~ 6

Author(s):

Kwang-il Hwang ◽

Sung-wook Nam

Keyword(s):

Internet Of Things ◽

Large Scale ◽

Ieee 802.15.4 ◽

Design Model ◽

Abstract Model ◽

Modes Of Operation ◽

Network Construction ◽

Scheduling Model ◽

And Performance ◽

Ieee 802.15.4E

In order to construct a successful Internet of things (IoT), reliable network construction and maintenance in a sensor domain should be supported. However, IEEE 802.15.4, which is the most representative wireless standard for IoT, still has problems in constructing a large-scale sensor network, such as beacon collision. To overcome some problems in IEEE 802.15.4, the 15.4e task group proposed various different modes of operation. Particularly, the IEEE 802.15.4e deterministic and synchronous multichannel extension (DSME) mode presents a novel scheduling model to solve beacon collision problems. However, the DSME model specified in the 15.4e draft does not present a concrete design model but a conceptual abstract model. Therefore, in this paper we introduce a DSME beacon scheduling model and present a concrete design model. Furthermore, validity and performance of DSME are evaluated through experiments. Based on experiment results, we analyze the problems and limitations of DSME, present solutions step by step, and finally propose an enhanced DSME beacon scheduling model. Through additional experiments, we prove the performance superiority of enhanced DSME.

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A DHT-Based Discovery Service for the Internet of Things

Journal of Computer Networks and Communications ◽

10.1155/2012/107041 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 39

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.

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Recommendation Based on Large-Scale Many-Objective Optimization for the Intelligent Internet of Things System

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3104661 ◽

2021 ◽

pp. 1-1

Author(s):

Bin Cao ◽

Yatian Zhang ◽

Jianwei Zhao ◽

Xin Liu ◽

Lukasz Skonieczny ◽

...

Keyword(s):

Internet Of Things ◽

Large Scale

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The future of the Internet of Things: toward heterarchical ecosystems and service business models

Journal of Business and Industrial Marketing ◽

10.1108/jbim-10-2015-0206 ◽

2018 ◽

Vol 33 (6) ◽

pp. 749-767 ◽

Cited By ~ 19

Author(s):

Seppo Leminen ◽

Mervi Rajahonka ◽

Mika Westerlund ◽

Robert Wendelin

Keyword(s):

Internet Of Things ◽

Business Model ◽

Value Chain ◽

Large Scale ◽

Business Models ◽

The Internet ◽

Content Type ◽

Industry Collaboration ◽

New Business ◽

The Internet Of Things

Purpose This study aims to understand their emergence and types of business models in the Internet of Things (IoT) ecosystems. Design/methodology/approach The paper builds upon a systematic literature review of IoT ecosystems and business models to construct a conceptual framework on IoT business models, and uses qualitative research methods to analyze seven industry cases. Findings The study identifies four types of IoT business models: value chain efficiency, industry collaboration, horizontal market and platform. Moreover, it discusses three evolutionary paths of new business model emergence: opening up the ecosystem for industry collaboration, replicating the solution in multiple services and return to closed ecosystem as technology matures. Research limitations/implications Identifying business models in rapidly evolving fields such as the IoT based on a small number of case studies may result in biased findings compared to large-scale surveys and globally distributed samples. However, it provides more thorough interpretations. Practical implications The study provides a framework for analyzing the types and emergence of IoT business models, and forwards the concept of “value design” as an ecosystem business model. Originality/value This paper identifies four archetypical IoT business models based on a novel framework that is independent of any specific industry, and argues that IoT business models follow an evolutionary path from closed to open, and reversely to closed ecosystems, and the value created in the networks of organizations and things will be shareable value rather than exchange value.

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