Indústria 4.0 : o impacto do Big Data e internet of things

Mestrado em Ciências EmpresariaisA tecnologia possuí um papel cada vez mais importante, na economia, e por consequência nas organizações. O impacto está patente na quarta revolução industrial e nas consequências que esta tem nas organizações. É por isso considerado que a sua análise é de importante relevo. A Indústria 4.0 é considerada como um conjunto de tecnologias que estão a emergir na atualidade, estando ainda pouco estudadas, sendo estas balizadas por um conjunto de características que as definem como integrantes da quarta revolução industrial. Assim, o presente estudo procura estudar, através da análise de artigos científicos e de investigação, quais os impactos que as tecnologias Big Data e Internet of Things têm na Indústria 4.0. A revisão de literatura permitiu estabelecer seis critérios essenciais da a Indústria 4.0: interoperabilidade, virtualização, descentralização, capacidade em tempo real, orientação para o serviço e modularização. Para a análise do impacto das duas tecnologias referidas foi constituída uma amostra de vinte artigos muito citados, utilizando a métrica h-index, onde foram aplicados os seis critérios e efetuada uma análise de clusters hierárquicos. As conclusões deste estudo indicam que existe uma clara tendência de utilização de três dos critérios: virtualização, análise em tempo real e orientação para o serviço nas referidas tecnologias. Deste modo, o impacto do Big Data e da Internet of Things na definição da Indústria 4.0 é maioritariamente constituída por metade dos critérios que definem a quarta revolução industrial.Technology in the economy, and consequently in organizations, plays an increasingly role. The impact is evident in the fourth industrial revolution and the consequences it has on organizations. In this way, it is considered that its analysis is important. Industry 4.0 being a set of technologies that are emerging today, being still little studied, these are marked out in a set of characteristics that define them as part of the fourth industrial revolution. Therefore, the present study seeks to analyze, through scientific and research articles, the impacts that Big Data and Internet of Things technologies have on Industry 4.0. The literature review allowed us to classify six characteristics: interoperability, virtualization, decentralization, real-time capability, service orientation and modularization. For the analysis of the impact of the two technologies a sample of twenty articles was constituted using the h-index metric where the six criteria were applied and a hierarchical clusters analysis was performed. The conclusions of this study indicate that there is a clear tendency to use three criteria: virtualization, real-time analysis and service orientation in these technologies. Furthermore, the impact of Big data and Internet of Things on the definition of Industry 4.0 is mostly constituted by half of the criteria that define the fourth industrial revolution.info:eu-repo/semantics/publishedVersio

Adaptive Information Dissemination Control to Provide Diffdelay for the Internet of Things

Applications running on the Internet of Things, such as the Wireless Sensor and Actuator Networks (WSANs) platform, generally have different quality of service (QoS) requirements. For urgent events, it is crucial that information be reported to the actuator quickly, and the communication cost is the second factor. However, for interesting events, communication costs, network lifetime and time all become important factors. In most situations, these different requirements cannot be satisfied simultaneously. In this paper, an adaptive communication control based on a differentiated delay (ACCDS) scheme is proposed to resolve this conflict. In an ACCDS, source nodes of events adaptively send various searching actuators routings (SARs) based on the degree of sensitivity to delay while maintaining the network lifetime. For a delay-sensitive event, the source node sends a large number of SARs to actuators to identify and inform the actuators in an extremely short time; thus, action can be taken quickly but at higher communication costs. For delay-insensitive events, the source node sends fewer SARs to reduce communication costs and improve network lifetime. Therefore, an ACCDS can meet the QoS requirements of different events using a differentiated delay framework. Theoretical analysis simulation results indicate that an ACCDS provides delay and communication costs and differentiated services; an ACCDS scheme can reduce the network delay by 11.111%–53.684% for a delay-sensitive event and reduce the communication costs by 5%–22.308% for interesting events, and reduce the network lifetime by about 28.713%

Adaptive Information Dissemination Control to Provide Diffdelay for the Internet of Things

Applications running on the Internet of Things, such as the Wireless Sensor and Actuator Networks (WSANs) platform, generally have different quality of service (QoS) requirements. For urgent events, it is crucial that information be reported to the actuator quickly, and the communication cost is the second factor. However, for interesting events, communication costs, network lifetime and time all become important factors. In most situations, these different requirements cannot be satisfied simultaneously. In this paper, an adaptive communication control based on a differentiated delay (ACCDS) scheme is proposed to resolve this conflict. In an ACCDS, source nodes of events adaptively send various searching actuators routings (SARs) based on the degree of sensitivity to delay while maintaining the network lifetime. For a delay-sensitive event, the source node sends a large number of SARs to actuators to identify and inform the actuators in an extremely short time; thus, action can be taken quickly but at higher communication costs. For delay-insensitive events, the source node sends fewer SARs to reduce communication costs and improve network lifetime. Therefore, an ACCDS can meet the QoS requirements of different events using a differentiated delay framework. Theoretical analysis simulation results indicate that an ACCDS provides delay and communication costs and differentiated services; an ACCDS scheme can reduce the network delay by 11.111%–53.684% for a delay-sensitive event and reduce the communication costs by 5%–22.308% for interesting events, and reduce the network lifetime by about 28.713%