Concept Of System Architecture Research Articles

Intelligent Information System for Monitoring the Quality of Drinking Water

The article explores the global issue of water scarcity. Methods are being applied to eliminate water pollution, which can lead to water shortages. Azerbaijan is also one of the countries suffering from this problem. A global approach to the issue is required. Considering the complexity of the problem, a prototype is being developed, and potential solutions are demonstrated on it. The JWR is taken as the prototype object. The conceptual model, functional model, and system architecture have been presented.

Battery-electric powertrain system design for the HorizonUAM multirotor air taxi concept

AbstractThe work presented herein has been conducted within the DLR internal research project HorizonUAM, which encompasses research within numerous areas related to urban air mobility. One of the project goals was to develop a safe and certifiable onboard system concept. This paper aims to present the conceptual propulsion system architecture design for an all-electric battery-powered multirotor electric Vertical Takeoff and Landing (eVTOL) vehicle. Therefore, a conceptual design method was developed that provides a structured approach for designing the safe multirotor propulsion architecture. Based on the concept of operation the powertrain system was initially predefined, iteratively refined based on the safety assessment and validated through component sizing and simulations. The analysis was conducted within three system groups that were developed in parallel: the drivetrain, the energy supply and the thermal management system. The design process indicated that a pure quadcopter propulsion system can merely be designed reasonably for meeting the European Union Aviation Safety Agency (EASA) reliability specifications. By adding two push propellers and implementing numerous safety as well as passivation measures the reliability specifications defined by EASA could finally be fulfilled. The subsequent system simulations also verified that the system architecture is capable of meeting the requirements of the vehicle concept of operations. However, further work is required to extend the safety analysis to additional system components as the thermal management system or the battery management system and to reduce propulsion system weight.

Enabling the use of digital calibration certificates in industrial calibration management systems

Abstract. Metrology has been a slowly digitalizing field in which a significant part of the handling of data has been dependent on paper-based processes. Due to the need for the improved efficiency and reliability of these processes, digitalization has become a major topic of interest in the metrology community. Data formats such as the digital calibration certificate (DCC) have an essential role as an enabler of further digitalization, acting as the harmonized data format for calibration data. Naturally, introducing these data formats into industrial usage sets new requirements with respect to the calibration management and associated systems. Diversity of metrology also means that the systems need to be flexible and scalable to fulfill the needs of actors in the global calibration infrastructure with very different requirements. This paper presents a conceptual approach for enhancing the communications between the existing systems in a calibration ecosystem and enabling DCC-based data exchange with third-party systems using the Beamex calibration ecosystem as an example. Thus, the presented system architecture concept that introduces data and DCC exchange services would provide a solution to enable the use of DCCs on Beamex systems.

General Overview and Proof of Concept of a Smart Home Energy Management System Architecture

This paper proposes and implements a smart architecture for Home Energy Management Systems (HEMS) that enables interoperability among devices from different manufacturers. This is achieved through the use of standardized elements and the design of an innovative middleware. The system comprises a control unit that communicates with smart outlets using the Wireless Smart Ubiquitous Network (WI-SUN) Home Area Network (HAN) specification, while smart metering is achieved using the WI-SUN Field Area Network (FAN) specification. To manage important data, a web platform and mobile app were created. Additionally, machine learning techniques are utilized to identify energy consumption of individual appliances when only the aggregate energy consumption of the house is available. The architecture presented here supports real-time control of energy use and generation through HEMS, and new devices can be added transparently. Finally, a comparison of the proposed system with similar systems in literature highlights its many advantages in terms of functionality.

Design rules to establish a credible More‐Electric Engine baseline power architecture concept

AbstractThe More‐Electric Engine (MEE), with its electrified engine auxiliary systems and increased multi‐shaft power offtake, is likely to become an increasingly central aspect of future More‐Electric Aircraft. Consequently, lightweight but resilient electrical power architectures are needed for these future MEE applications. However, whilst a range of MEE architectures exist in the research literature, no effective baseline architecture or standardised feature identification has been proposed to specifically address their unique design requirements. Accordingly, any underpinning technology‐focused research for critical MEE subsystems may ultimately have a reduced effectiveness without this credible baseline. Based on comprehensive design analyses, preliminary design requirements and anticipated operational modes, this article proposes key design rules for the formation of the first generic baseline MEE electrical power system architecture concept. Guidance is provided on features such as the number of power generation systems, the number and topologies of distribution channels, type of power conversion, essential load redundancy, and the location of emergency power supply. This article also provides full transparency of the design process so that key decision points can be revisited to capture application‐specific requirements and updates to certification requirements.

Siamese Temporal Convolutional Networks for Driver Identification Using Driver Steering Behavior Analysis

Driver identification has shown sustainable development in recent years in a wide variety of applications including but not limited to security, personalization, fleet management, insurance telematics, or ride-hailing. However, the current progress suffers from several challenges such as costly data collections and the need for a huge amount of data from each individual for both driver identification and impostor detection. Therefore, more novel and efficient solutions are required to mitigate the existing challenges. In this paper, we address driver identification and impostor detection tasks using driving behavior analysis of the drivers. We design a deep learning-based system architecture that analyzes windows of 30 seconds of driving data to capture the unique underlying characteristics of the individuals steering behavior based on which it further distinguishes the drivers. We also develop a novel strategy to tackle driver verification and impostor detection tasks based on the combination of the proposed system architecture and Siamese networks concepts. We map the steering behavior of the drivers into latent representations which can be later used to train a similarity function. The performance of the proposed systems is tested over a real-world dataset of 95 drivers. The evaluation results indicate that our system outperforms well-established benchmarks and baseline methodologies.

Reviewing the intellectual structure of product modularization: Toward a common view and future research agenda

AbstractProduct modularization in new product development has attracted considerable interest among scholars and practitioners from diverse fields of specialization. This has resulted in cross‐disciplinary diversity in the field, diverting attention from its overall intellectual structure and hindering the development of a common view and shared concepts. Extant research lacks an integrative review, transcending a focal discipline that could identify gaps and ambiguities while making recommendations to advance the field. Considering a period of 30 years (1990–2020), we generate a data set of 2988 citing publications to which we apply a co‐citation analysis. Thereby, we uncover the intellectual structure of the field and find three research perspectives that represent key knowledge bases: (1) product system, (2) production system, and (3) organizational system. Delimiting the data set into four periods, we can track developments over time, where we notice an increasing disintegration of the product system perspective, which is rooted in the discipline of engineering design. Within the two other perspectives, we document extensive dynamism in terms of publications, especially in the two most recent periods, indicating an active discussion and a potential receptivity to new trends. For these periods, we also identify an emerging cluster of fundamental publications and an increasing emphasis on the concept of system architecture. Leveraging the synthesis of these results, we forge links between neighboring disciplines and recommend avenues for further research, ideally to develop a more common view.

High-temperature superconductor-based power and propulsion system architectures as enablers for high power missions

The increasing competitiveness of electric propulsion systems (EPS) for primary spacecraft propulsion has paved the way for higher payload mass fractions by offering significantly higher specific impulses than chemical systems. Concurrently, High-Temperature Superconductors (HTS) have reached an unprecedented level of industrial maturity in recent years, and considering their low masses, compactness, and high current densities, they offer the potential to act as a disruptive technology in several spaceflight applications such as power management systems, re-entry and radiation shielding as investigated in the EU-funded MEESST project, as well as EPS. In the latter case, efforts are already ongoing to develop an HTS-enhanced Applied-Field Magnetoplasmadynamic (AF-MPD) thrusters for high power mission applications. The Tsiolkovsky equation infers that the payload mass fraction increases indefinitely with increased Specific Impulse (Isp), however, in the case of electric propulsion, the dependence of thrust on the available power complicates this issue when transfer time is a primary driver. Here, the Tsiolkovsky equation becomes inadequate and considering a non-dimensional version of the Tsiolkovsky equation in terms of the mission ΔV and transfer time, the EPS thrust efficiency, and the specific mass of the power system becomes necessary. This paper first discusses the recent advances in HTS and their suitability for spaceflight, before reviewing The development of power system technologies is reviewed and a conceptual power system architecture incorporating HTS is presented. These technologies are analysed using a non-dimensional Tsiolkovsky approach and their impacts on the overall payload mass fraction are assessed. For high-power missions (>100 kW), the use of HTS is shown to have a highly beneficial impact on the mass of the power system. Correspondingly, this enables higher payload mass fractions achievable at increased specific impulse operation, thus strengthening the case for high-power, high-Isp EPS technologies such as AF-MPDT.

Cloud based AI approach for predictive maintenance and failure prevention

Every industry has utilized machines of various types for many functions. The manufacturing industry has utilized machines since the industrial revolution for mass manufacturing. Operating machines continuously can lead to faults and require maintenance and repairs. As computing power increased and various technologies such as embedded systems, artificial intelligence, deep learning, cloud computing etc. were developed, new systems were implemented to perform diagnostics on machines. In this paper, A conceptual system architecture of a cloud based AI system to predict potential failure of a component by analyzing data collected from various sources and develop inspection and maintenance schedules is proposed. The application of technologies such as Artificial Intelligence, Cloud computing and process mining in the system is discussed in detail. The operation of the system in a real world condition is discussed by developing a system architecture for maintenance and failure prediction of aircraft fan blades of an aircraft engine. The future application of the system with potential increase in capability is discussed.

Applying cyber physical system architecture concept to the design and manufacturing of blood glucose monitoring systems to provide man-machine interactions and intelligent automation

The current design and manufacturing of blood glucose monitoring systems (BGMS) cannot resolve many current problems. Even with recent new advances on 100% non-damaging quality check and laser repair for the defective test strips found, it is still not enough. With the new internet, a new revolutionary architectural concept based on cyber physical system (CPS) is highly recommended to implement on the design and manufacturing of BGMS. This paper presents many unique benefits that can be achieved. The implementation of CPS to the design of BGMS interconnects the uses of glucose meters, test strips and control solutions with the manufacturing systems through internet to enhance the safety and performance of the BGMS, and to provide man-machine interactions and intelligent automation. Furthermore, the implementation of CPS to the manufacturing of BGMS further interconnects sensors and information feedbacks from different work stations to allow the manufacturing systems to be self-aware, self-adaptable and self-configurable, in order to reduce manpower, defective rate and production down time for better productivity. This new concept will bring in revolutionary approaches into the design and manufacturing of BGMS, in order to upgrade product performance, increase product competitiveness and create new business opportunities, by providing man-machine interactions and intelligent automation. Apart from that, the implementation of CPS architecture to the design and manufacturing of BGMS does not necessarily increase the costs of producing BGMS.

Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses

A deep understanding about a field of research is valuable for academic researchers. In addition to technical knowledge, this includes knowledge about subareas, open research questions, and social communities (networks) of individuals and organizations within a given field. With bibliometric analyses, researchers can acquire quantitatively valuable knowledge about a research area by using bibliographic information on academic publications provided by bibliographic data providers. Bibliometric analyses include the calculation of bibliometric networks to describe affiliations or similarities of bibliometric entities (e.g., authors) and group them into clusters representing subareas or communities. Calculating and visualizing bibliometric networks is a nontrivial and time-consuming data science task that requires highly skilled individuals. In addition to domain knowledge, researchers must often provide statistical knowledge and programming skills or use software tools having limited functionality and usability. In this paper, we present the ambalytics bibliometric platform, which reduces the complexity of bibliometric network analysis and the visualization of results. It accompanies users through the process of bibliometric analysis and eliminates the need for individuals to have programming skills and statistical knowledge, while preserving advanced functionality, such as algorithm parameterization, for experts. As a proof-of-concept, and as an example of bibliometric analyses outcomes, the calculation of research fronts networks based on a hybrid similarity approach is shown. Being designed to scale, ambalytics makes use of distributed systems concepts and technologies. It is based on the microservice architecture concept and uses the Kubernetes framework for orchestration. This paper presents the initial building block of a comprehensive bibliometric analysis platform called ambalytics, which aims at a high usability for users as well as scalability.

Photometric stereo-based high-speed inline battery electrode inspection

AbstractBattery technology is a key component in current electric vehicle applications and an important building block for upcoming smart grid technologies. The performance of batteries depends largely on quality control during their production process. Defects introduced in the production of electrodes can lead to degraded performance and, more importantly, to short circuits in final cells, which is highly safety-critical. In this paper, we propose an inspection system architecture that can detect defects, such as missing coating, agglomerates, and pinholes on coated electrodes. Our system is able to acquire valuable production quality control metrics, like surface roughness. By employing photometric stereo techniques (PS), a shape from shading algorithm, our system surmounts difficulties that arise while optically inspecting the black to dark gray battery coating materials. We present in detail the acquisition concept of the proposed system architecture, and analyze its acquisition-, as well as, its surface reconstruction performance in experiments. We carry these out utilizing two different implementations that can operate at a production speed of up to 2000 mm/s at a resolution of 50 µm per pixel. In this work we aim to provide a system architecture that can provide a reliable contribution to ensuring optimal performance of produced battery cells.

Innovative ecosystem for informing visual impaired person in smart shopping environment: InnIoTShop

Assistive technologies nowadays have an increasing application in overcoming the everyday needs of visually impaired persons. Going to the grocery store for groceries is a challenge for any visually impaired person who moves without a personal assistant. Creating a perception of the space in which the person is located and the possibility of orientation in such an environment is significantly reduced. The solutions and services currently available are based solely on reading products using some form of assistive technology. In this research, user needs were analyzed to define the necessary information to master the shopping process. The research aims to define a conceptual system architecture to deliver InnIoTShop information service to users moving through smart stores. The proposed architecture is based on the IoT concept, and an InnIoTShop service taxonomy has been created for this service. For data collection, processing, and fusion, the concept of Fog/Cloud Computing and M2M and M2H technology was used, which enables the adaptation of information to visually impaired persons. The paper also validated specific elements of the system architecture, which confirmed individual service functionalities' operation.

Category-Theoretic Formulation of the Model-Based Systems Architecting Cognitive-Computational Cycle

We introduce the Concept→Model→Graph→View Cycle (CMGVC). The CMGVC facilitates coherent architecture analysis, reasoning, insight, and decision making based on conceptual models that are transformed into a generic, robust graph data structure (GDS). The GDS is then transformed into multiple views of the model, which inform stakeholders in various ways. This GDS-based approach decouples the view from the model and constitutes a powerful enhancement of model-based systems engineering (MBSE). The CMGVC applies the rigorous foundations of Category Theory, a mathematical framework of representations and transformations. We show that modeling languages are categories, drawing an analogy to programming languages. The CMGVC architecture is superior to direct transformations and language-coupled common representations. We demonstrate the CMGVC to transform a conceptual system architecture model built with the Object Process Modeling Language (OPM) into dual graphs and a stakeholder-informing matrix that stimulates system architecture insight.

Industrial digital ecosystems: Predictive models and architecture development issues

The concept of digital ecosystem (DES) is widely used in autonomous manufacturing process control and the development of complex, stable, interactive, self-organizing and reliable management systems for various industries. The paper offers a concept of DES control system architecture based on predictive models. For estimating and predicting the state of resources in production processes, an approach is developed using data mining based model generation. The paper also reviews the current state of research in the field of DES and their applications in supply chain management (SCM).

MRC-Based Double Figure-of-Eight Coil Sensor System With Triple-Mode Operation Capability for Biomedical Applications

Efficient wireless power transmission to a designated location can reduce the size of implantable device and save source energy, but the receiver coil and rectifier circuit still occupy a large area. This paper proposes a novel magnetic resonant coupling (MRC)-based double figure-of-eight coil sensor system to induce and monitor heat. Implantable devices could obtain energy from the surrounding electric field or heating effect. The fundamental of generating the heating effect by the proposed coil-based sensor system is derived, and conceptual system architecture is built. Then the radiating coil is analyzed in terms of Litz-wire coil optimization, lumped parameter extraction, impedance-matching network, equivalent circuit model, and coupling coefficient. Considering the current ratio, operating frequency, and designated location, the triple-mode operation mechanism is analyzed for the first time to adjust superposed electromagnetic fields at the designated location. At the odd-mode resonance, the electric field intensity in the middle between two figure-of-eight coils is significantly improved. Finally, the physical prototype of proposed coil-based sensor system is built up and experiments are conducted to test the currents in both figure-of-eight coils as well as the induced voltage and temperature change in the in-vitro sample by using the electrode sensor and thermocouple sensor. Measurements validate the feasibility of the proposed coil-sensor system. It also provides essential guidance on designing sensors for deep-tissue stimulation and hyperthermia treatment.

Data Management System for Ubiquitous Multi-task Mobile Devices on Semi-network OS Architecture

This study is to explore a newly configured data management system of Internet of Things and other intelligent technologies in ubiquitous computing based on semi-network OS architecture.
 Modern Internet of Things and other intelligent technologies have increasingly shown a trend of diversification and ubiquitous computing, and the usual mobile devices characterized by “single-task”, “stable”, “oriented”, and “immutable” are also bound to face the pressure and motion of reform and innovation.
 The advancement of merger of single-task mobile devices will be unstoppable, and the operating system rightfully needs to be divided into “base portion” and “expanded portion”, which just fits the concept of semi-network operating system architecture; the “base portion” is similar to existing “embedded operating system”, and the “expanded portion” is network resources.
 Today, the merger of single-task mobile devices and the formation of multi-task mobile devices have become general trend, and architecture of semi-network operating system can lay a new foundation for this wave of merger.
 The multi-task mobile device formed by merger of single-task mobile devices based on architecture of semi-network operating system has its special computing system: co-mobile computing system, where including a data management system.
 Multi-task mobile devices form a so-called co-mobile computing system, and also form a newly configured secure data management system, which is like a universal key to form a new working system for opening a lot of unspecified locks based on new principle and security mechanism.

Early Detection of Diabetic Eye Disease through Deep Learning using Fundus Images

INTRODUCTION: Diabetic eye disease (DED) is a group of eye problems that can affect diabetic people. Such disorders include diabetic retinopathy, diabetic macular edema, cataracts, and glaucoma. Diabetes can damage your eyes over time, which can lead to poor vision or even permanent blindness. Early detection of DED symptoms is therefore essential to prevent escalation of the disease and timely treatment. Research difficulties in early detection of DEDs can so far be summarized as follows: changes in the eye anatomy during its early stage are often untraceable by the human eye due to the subtle nature of the features, where large volumes of fundus images put tremendous pressure on scarce specialist resources, making manual analysis practically impossible.OBJECTIVES: Therefore, methods focused on deep learning have been practiced to promote early detection of DEDs and address the issues currently faced. Despite promising, highly accurate identification of early anatomical changes in the eye using Deep Learning remains a challenge in wide-scale practical application.METHODS: We present conceptual system architecture with pre-trained Convolutional Neural Network combined with image processing techniques to construct an early DED detection system. The data was collected from various publicly available sources, such as Kaggle, Messidor, RIGA, and HEI-MED. The analysis was presented with 13 Convolutional Neural Networks models, trained and tested on a wide-scale imagenet dataset using the Transfer Learning concept. Numerous techniques for improving performance were discussed, such as (i) image processing,(ii) fine-tuning, (iii) volume increase in data. The parameters were recorded against the default Accuracy metric for the test dataset.RESULTS: After the extensive study about the various classification system, and its methods, we found that creating an efficient neural network classifier demands careful consideration of both the network architecture and the data input. Hence, image processing plays a significant role to develop high accuracy diabetic eye disease classifiers.CONCLUSION: This article recognized specific work limitations in the early classification of diabetic eye disease. First, early-stage classification of DED, and second, classification of DR, GL, and DME using a method that causes permanent blindness afterward. Lastly, this study was intended to propose the framework for early automatic DED detection of fundus images through deep learning addressing three main research gaps.

The smart power cell concept: mastering TSO–DSO interactions for the secure and efficient operation of future power systems

This article describes a novel power system architecture and operational concept which is founded on the idea of organising sets of distributed generators, loads, storages and multimodal interfaces at distribution level in supervised and controlled grid subsections called smart power cells, which are controllable entities intended to enforce the stability of the transmission network and participate in its operation. Further, the article addresses a control scheme which can be implemented within a smart power cell to control its active and reactive power exchange with the transmission network following set points provided by a superimposed control system, and thus participate in the operation of the transmission grid (e.g. participation in congestion management, system optimisation, balancing of generation and load). The dynamic behaviour of a future power system under consideration of the proposed system architecture including several smart power cells controlled with the developed control scheme is demonstrated through time-domain simulation using a combined transmission–distribution power system model.

Smart City as System of Systems: Subject of study ‐ Vertical Farming and Autonomous Driving in Smart city

Abstract“Growth is inevitable and desirable, but destruction of community character is not. The question is not whether your part of the world is going to change. The question is how.” – Edward T. McMahonThe above quote fits perfectly on rapid urbanization today. With swift technological growth and enhancement in associated services, we are moving in future of digitalization and connectivity. At the same time, this transition must be safe and secure. This paper specifically talks about applying system architecture concepts to understand complexity of smart city as System of systems with focus on wildly important elements – Food and Commutation, summarizing problem, need and possible challenges.WHAT – To understand role of autonomous driving and vertical farming in concept of smart city, by doing logical decomposition and dependency analysis using systems engineering techniques.WHY – We need to make our cities smart to bring growth, ease, comfort, speed, safety and security of operations in balanced socio‐economic environment. By doing this we can take proactive actions instead of reacting to situations.HOW – First, Smart city system need to be decomposed into subsystems based on functionality of the system. Now identify stakeholders for each subsystem and map their needs to functions and forms.This paper takes example of two subsystems – Vertical Farming and Autonomous City Drive to demonstrate decomposition and architectural decision on a subsystem.This paper contrast on how increasing commutation problem in growing cities be managed by systematically planning electric autonomous vehicles to provide safe, fast, comfortable and economical city ride.Along with that, this paper also encircles need of vertical farming in growing cities to produce variety of crops, all year long, without soil. This will bring time to market down and will reduce overall carbon footprint.Advantages and challenges in adoption of above two subsystem in context of smart city are in scope of this paper.