IoT Based Image Processing Filters

Internet of things (IoT) becomes the backbone of the advanced countries and it has a real contribute to exchange the traditional style or way of practical life, even personal life into smart style, with (IoT) technology the life become more and more easy and professional. internet of things achieves various applications coordinate with sensors and standard protocols to apply what is called machine -to- machine connection (M2M), in this paper we will talk more about the concept of (M2M), the main component of internet of things and finally the common protocols that is used in network, in addition to that this work present an IOT operation with processing system using camera for capturing image and Xilinx system generator(XSG)models for designing  image processing algorithms and the result of  the processing is an image with black and white for edge detection and Thresholding models  and gray color image for gray enhancement model

Underlay Drone Cell for Temporary Events: Impact of Drone Height and Aerial Channel Environments

Providing seamless connection to a large number of devices is one of the biggest challenges for the Internet of Things (IoT) networks. Using a drone as an aerial base station (ABS) to provide coverage to devices or users on ground is envisaged as a promising solution for IoT networks. In this paper, we consider a communication network with an underlay ABS to provide coverage for a temporary event, such as a sporting event or a concert in a stadium. Using stochastic geometry, we propose a general analytical framework to compute the uplink and downlink coverage probabilities for both the aerial and the terrestrial cellular system. Our framework is valid for any aerial channel model for which the probabilistic functions of line-of-sight (LOS) and non-line-of-sight (NLOS) links are specified. The accuracy of the analytical results is verified by Monte Carlo simulations considering two commonly adopted aerial channel models. Our results show the non-trivial impact of the different aerial channel environments (i.e., suburban, urban, dense urban and high-rise urban) on the uplink and downlink coverage probabilities and provide design guidelines for best ABS deployment height.Comment: This work is accepted to appear in IEEE Internet of Things Journal Special Issue on UAV over IoT. Copyright may be transferred without notice, after which this version may no longer be accessible. arXiv admin note: text overlap with arXiv:1801.0594

Diseño de un Modelo Predictivo en el Contexto Industria 4.0

The Internet of Things (IoT), the development and installation of advanced sensors for data collection, computer solutions for remote connection and other disruptive technologies are marking a transformation process in the industry; giving rise to what various sectors have called the fourth industrial revolution or Industry 4.0. With this process of change, organizations face both new opportunities and challenges. This article focuses on the modeling and integration of industrial data, generated by sensors installed in machines. The extraction of patterns is proposed, using data fusion techniques that allow the design of a predictive maintenance model. Finally, a case study is presented with a database that is applied to the Naive Bayes Algorithm to obtain predictions.Keywords: Industry 4.0, Sensors, Internet of Things, Pattern Extraction, Omnibus Models.

Longitudinal Segmented Analysis of Internet Usage and Well-Being Among Older Adults

The connection between digital literacy and the three core dimensions of psychological well-being is not yet well understood, and the evidence is controversial. We analyzed a sample of 2,314 individuals, aged 50 years and older, that participated in the English Longitudinal Study of Aging. Participants were clustered according to drivers of psychological well-being using Self-Organizing Maps. The resulting groups were subsequently studied separately using generalized estimating equations fitted on 2-year lagged repeated measures using three scales to capture the dimensions of well-being and Markov models. The clustering analysis suggested the existence of four different groups of participants. Statistical models found differences in the connection between internet use and psychological well-being depending on the group. The Markov models showed a clear association between internet use and the potential for transition among groups of the population characterized, among other things, by higher levels of psychological well-being

Exploiting the Capture Effect to Enhance RACH Performance in Cellular-Based M2M Communications

Cellular-based machine-to-machine (M2M) communication is expected to facilitate services for the Internet of Things (IoT). However, because cellular networks are designed for human users, they have some limitations. Random access channel (RACH) congestion caused by massive access from M2M devices is one of the biggest factors hindering cellular-based M2M services because the RACH congestion causes random access (RA) throughput degradation and connection failures to the devices. In this paper, we show the possibility exploiting the capture effects, which have been known to have a positive impact on the wireless network system, on RA procedure for improving the RA performance of M2M devices. For this purpose, we analyze an RA procedure using a capture model. Through this analysis, we examine the effects of capture on RA performance and propose an Msg3 power-ramping (Msg3 PR) scheme to increase the capture probability (thereby increasing the RA success probability) even when severe RACH congestion problem occurs. The proposed analysis models are validated using simulations. The results show that the proposed scheme, with proper parameters, further improves the RA throughput and reduces the connection failure probability, by slightly increasing the energy consumption. Finally, we demonstrate the effects of coexistence with other RA-related schemes through simulation results

Matroid Online Bipartite Matching and Vertex Cover

The Adwords and Online Bipartite Matching problems have enjoyed a renewed attention over the past decade due to their connection to Internet advertising. Our community has contributed, among other things, new models (notably stochastic) and extensions to the classical formulations to address the issues that arise from practical needs. In this paper, we propose a new generalization based on matroids and show that many of the previous results extend to this more general setting. Because of the rich structures and expressive power of matroids, our new setting is potentially of interest both in theory and in practice. In the classical version of the problem, the offline side of a bipartite graph is known initially while vertices from the online side arrive one at a time along with their incident edges. The objective is to maintain a decent approximate matching from which no edge can be removed. Our generalization, called Matroid Online Bipartite Matching, additionally requires that the set of matched offline vertices be independent in a given matroid. In particular, the case of partition matroids corresponds to the natural scenario where each advertiser manages multiple ads with a fixed total budget. Our algorithms attain the same performance as the classical version of the problems considered, which are often provably the best possible. We present $1-1/e$-competitive algorithms for Matroid Online Bipartite Matching under the small bid assumption, as well as a $1-1/e$-competitive algorithm for Matroid Online Bipartite Matching in the random arrival model. A key technical ingredient of our results is a carefully designed primal-dual waterfilling procedure that accommodates for matroid constraints. This is inspired by the extension of our recent charging scheme for Online Bipartite Vertex Cover.Comment: 19 pages, to appear in EC'1

The internet of everything sustainable advantages and synergies in clustered retail

The Internet of Everything (IoE) is a concept introduced by Cisco as the succeeding phase of the Internet of Things (IoT), consisting in creating a network connection of objects, people, processes and data (Cisco 2013). The novelty in this concept is that instead of referring simply to the network connection of physical objects, the IoE allows for connected ‘things’ to send higher-level information back to machines, computers, and people for further evaluation and decision making (Cisco 2013). ! This dissertation aims to analyze the IoE concept’s strategic impact in clustered retails. In order to contextualize the concept and, later, perform the correct analysis of the subject, a review of the technologies at its core and Cisco’s perspective of IoE’s realization in retail is made. Furthermore, making up the core of sustainable strategic advantage analysis, a review is made regarding Resource-based View (RBV) model according to Barney’s framework and Customer Relationship Management (CRM) through Payne and Frow’s framework. In the subsequent chapter, the model of analysis is explained, incorporating the proposition that a smartphone application is, at a first phase, the optimal presentation layer for consumers. Empirical data collection is then performed through a questionnaire intended to give answer to the dissertation’s research question of sustainable competitive advantage. The results, collected from a population sample of 120 respondents, ascertained the importance of the smartphone app and its most appealing features. The strategic applicability of IoE in clustered retail is, then, confirmed through the application of both RBV and CRM models, which verify the system’s potential to generate sustained competitive advantage, confirming the dissertation’s main objective.A Internet of Everything (IoE) – ou a Internet de Tudo - é um conceito introduzido pela Cisco como fase sucessora da Internet of Things (IoT) – ou a Internet das Coisas -, caracterizada por criar uma rede de conectiva de objectos, pessoas, processos e informação (Cisco 2013). A novidade introduzida por este conceito é de que, em vez de fazer referência apenas à rede de conexões de objectos físicos, o IoE permite à rede de ‘coisas’ o envio de informação de qualidade superior de volta para máquinas, computadores, e pessoas para avaliações e decisões adicionais (Cisco 2013). O objectivo desta dissertação assenta na análise do impacto estratégico do conceito de IoE em retalho conglomerado. De modo a contextualizar o conceito e, mais tarde, proceder à correcta análise do tópico, uma revisão da tecnologia basilar e da perspectiva da Cisco em relação à implementação da IoE em retalho é realizada. Ademais, constituindo a origem da análise à vantagem estratégica sustentável, uma revisão é feita a ambos os modelo de Resource-base View (RBV), de acordo com enquadramento de Barney, e Customer Relationship Management (CRM) – ou Gestão de Relacionamento com o Cliente -, através do enquadramento de Payne e Frow. No capítulo subsequente, o modelo de análise é explicado, incluindo a proposição que uma aplicação para smartphone seria, numa primeira fase, o canal de ligação e apresentação ao consumidor ideal. A recolha de dados empíricos é, de seguida, executada através de um questionário, pretendendo dar resposta dar resposta à pergunta central da dissertação relativa à vantagem competitiva sustentável. Os resultados, recolhidos de uma amostra populacional de 120 inquiridos, determinaram a importância da aplicação para smartphones e quais as suas características mais apelativas. A aplicabilidade estratégica da IoE em retalho conglomerado é, assim, confirmada através da aplicação de ambos os modelos de RBV e CRM, que certificam o potencial do sistema em gerar vantagem competitiva sustentável, confirmando assim o objectivo principal da dissertação

Novel proposal for prediction of CO2 course and occupancy recognition in Intelligent Buildings within IoT

Many direct and indirect methods, processes, and sensors available on the market today are used to monitor the occupancy of selected Intelligent Building (IB) premises and the living activities of IB residents. By recognizing the occupancy of individual spaces in IB, IB can be optimally automated in conjunction with energy savings. This article proposes a novel method of indirect occupancy monitoring using CO2, temperature, and relative humidity measured by means of standard operating measurements using the KNX (Konnex (standard EN 50090, ISO/IEC 14543)) technology to monitor laboratory room occupancy in an intelligent building within the Internet of Things (IoT). The article further describes the design and creation of a Software (SW) tool for ensuring connectivity of the KNX technology and the IoT IBM Watson platform in real-time for storing and visualization of the values measured using a Message Queuing Telemetry Transport (MQTT) protocol and data storage into a CouchDB type database. As part of the proposed occupancy determination method, the prediction of the course of CO2 concentration from the measured temperature and relative humidity values were performed using mathematical methods of Linear Regression, Neural Networks, and Random Tree (using IBM SPSS Modeler) with an accuracy higher than 90%. To increase the accuracy of the prediction, the application of suppression of additive noise from the CO2 signal predicted by CO2 using the Least mean squares (LMS) algorithm in adaptive filtering (AF) method was used within the newly designed method. In selected experiments, the prediction accuracy with LMS adaptive filtration was better than 95%.Web of Science1223art. no. 454