Related papers: Application of Data Stream Processing Technologies…
The rapid growth of Industry 4.0 technologies such as big data, cloud computing, smart sensors, machine learning (ML), radio-frequency identification (RFID), robotics, 3D-printing, and Internet of Things (IoT) offers Small and Medium…
Industry is part of an economy that produces highly mechanized and automated material goods. Since the beginning of industrialization, there have been several stages and paradigm shifts that today are ex-post-so-called industrial…
Parallel computing is very important to accelerate the performance of software systems. Additionally, considering that a recurring challenge is to process high data volumes continuously, stream processing emerged as a paradigm and software…
The massive streams of Internet of Things (IoT) data require a timely analysis to retain data usefulness. Stream processing systems (SPSs) enable this task, deriving knowledge from the IoT data in real-time. Such real-time analytics…
Industry 4.0 offers many possibilities for creating highly efficient and flexible manufacturing. To create such advantages, highly automated and thus digitized processes and systems are required. Here, most technologies known from the…
In recent years, with the rapid development of sensing technology and the Internet of Things (IoT), sensors play increasingly important roles in traffic control, medical monitoring, industrial production and etc. They generated high volume…
Information may be accessed from a distance thanks to computer networks. Wireless or wired networks are also possible. Due to recent developments in wireless infrastructure, wireless sensor networks (WSNs) were developed. Activities or…
The following work addresses the problem of frameworks for data stream processing that can be used to evaluate the solutions in an environment that resembles real-world applications. The definition of structured frameworks stems from a need…
The concept of Industry 4.0 brings a disruption into the processing industry. It is characterised by a high degree of intercommunication, embedded computation, resulting in a decentralised and distributed handling of data. Additionally,…
Many different worldwide initiatives are promoting the transformation from machine dominant manufacturing to digital manufacturing. Thus, to achieve a successful transformation to Industry 4.0 standard, manufacturing enterprises are…
The Industrial Internet of Things (IIoT) paradigm has emerged as a transformative force, revolutionizing industrial processes by integrating advanced wireless technologies into traditional procedures to enhance their efficiency. The…
An essential part of building a data-driven organization is the ability to handle and process continuous streams of data to discover actionable insights. The explosive growth of interconnected devices and the social Web has led to a large…
Over the past thirty years, logistics has undergone tremendous change from a purely operational performance that led to sales or production and focused on securing supply and delivery lines to customers, with the transformation of…
Software as a service (SaaS) has recently enjoyed much attention as it makes the use of software more convenient and cost-effective. At the same time, the arising of users' expectation for high quality service such as real-time information…
Contemporary software systems, such as the Internet of Things, Industry 4.0 and Intelligent Cities, present challenges for their engineering, since they question our traditional form of software development. They represent a promising…
The concept of Industry 4.0 is a newly emerging focus of research throughout the world. However, it has lots of challenges to control data, and it can be addressed with various technologies like Internet of Things (IoT), Big Data,…
Due to recent advances in data collection techniques, massive amounts of data are being collected at an extremely fast pace. Also, these data are potentially unbounded. Boundless streams of data collected from sensors, equipments, and other…
LoraWAN has turned out to be one of the most successful frameworks in IoT devices. Real world scenarios demand the use of such networks along with a robust stream processing application layer. To maintain the exactly once processing…
Transactional stream processing (TSP) strives to create a cohesive model that merges the advantages of both transactional and stream-oriented guarantees. Over the past decade, numerous endeavors have contributed to the evolution of TSP…
In the era of Industry 4.0, system reliability engineering faces both challenges and opportunities. On the one hand, the complexity of cyber-physical systems, the integration of novel numerical technologies, and the handling of large…