Innovative Platform for Designing Hybrid Collaborative & Context-Aware Data Mining Scenarios

The process of knowledge discovery involves nowadays a major number of techniques. Context-Aware Data Mining (CADM) and Collaborative Data Mining (CDM) are some of the recent ones. the current research proposes a new hybrid and efficient tool to design prediction models called Scenarios Platform-Collaborative & Context-Aware Data Mining (SP-CCADM). Both CADM and CDM approaches are included in the new platform in a flexible manner; SP-CCADM allows the setting and testing of multiple configurable scenarios related to data mining at once. The introduced platform was successfully tested and validated on real life scenarios, providing better results than each standalone technique-CADM and CDM. Nevertheless, SP-CCADM was validated with various machine learning algorithms-k-Nearest Neighbour (k-NN), Deep Learning (DL), Gradient Boosted Trees (GBT) and Decision Trees (DT). SP-CCADM makes a step forward when confronting complex data, properly approaching data contexts and collaboration between data. Numerical experiments and statistics illustrate in detail the potential of the proposed platform.Comment: 15 figure

Holistic Context-Sensitivity for Run-Time Optimization of Flexible Manufacturing Systems

Highly flexible manufacturing systems require continuous run-time (self-) optimization of processes with respect to diverse parameters, e.g., efficiency, availability, energy consumption etc. A promising approach for achieving (self-) optimization in manufacturing systems is the usage of the context sensitivity approach based on data streaming from high amount of sensors and other data sources. Cyber-physical systems play an important role as sources of information to achieve context sensitivity. Cyber-physical systems can be seen as complex intelligent sensors providing data needed to identify the current context under which the manufacturing system is operating. In this paper, it is demonstrated how context sensitivity can be used to realize a holistic solution for (self-) optimization of discrete flexible manufacturing systems, by making use of cyber-physical systems integrated in manufacturing systems/processes. A generic approach for context sensitivity, based on self-learning algorithms, is proposed aiming at a various manufacturing systems. The new solution encompasses run-time context extractor and optimizer. Based on the self-learning module both context extraction and optimizer are continuously learning and improving their performance. The solution is following Service Oriented Architecture principles. The generic solution is developed and then applied to two very different manufacturing processes

Extending the BASE architecture for complex and reconfigurable cyber-physical systems using Holonic principles.

Thesis (MEng)--Stellenbosch University, 2021.ENGLISH ABSTRACT: ndustry 4.0 (I4.0) represents the newest technological revolution aimed at optimising industries using drivers such as Cyber-Physical Systems (CPSs), the Internet of Things (IoT) and many more. In the past two decades, the holonic paradigm has become a major driver of intelligent manufacturing systems, making it ideal to advance I4.0. The objective of this thesis is to extend an existing holonic reference architecture, the Biography-Attributes-Schedule-Execution (BASE) architecture, for complex and reconfigurable CPSs. In the context of this thesis, complex and reconfigurable systems are considered to be systems that are comprised of many diverse, autonomous and interacting entities, and of which the functionality, organization or size is expected to change over time. The thesis applies the principles of holonic systems to manage complexity and enhance reconfigurability of CPS applications. The BASE architecture is extended for two reasons: to enable it to integrate many diverse entities, and to enhance its reconfigurability. With regards to research on holonic systems, this thesis aims to address two important functions for systems implemented using holonic principles, namely cooperation and cyber-physical interfacing The most important extensions made to the architecture were to enable scalability, refine the cooperation between holons, and integrate cyber-physical interfacing services as Interface Holons. These extensions include platform management components (e.g. a service directory) and standardised plugins (e.g. cyber-physical interfacing plugins). The extended architecture was implemented on an educational sheep farm, because of the many heterogeneous resources (sheep, camps, sensors, humans, etc.) on the farm that need to be integrated into a BASE architecture implemented CPS. This case study implementation had to integrate data from different sensors, provide live analysis of observed data and, when required, notify the physical world of any problems in the CPS. At the end of the implementation, an evaluation was done using the requirements of a complex, reconfigurable CPS as evaluation criteria. This evaluation involved setting up quantitative and qualitative evaluation metrics for the evaluation criteria, doing the evaluations, and discussing what the results from the different evaluations indicate about the effectiveness and efficiency of the extensions made to the BASE architecture. The extensions made to the BASE architecture were found to improve robustness and resilience. The use of Erlang was found to play a very important role in the resulting reliability. The extensions also helped to fully address the original BASE architecture’s scalability shortcomings and to increase development productivity. Lastly, the extensions show the benefits of using service orientation to enable cooperation between holons and how extracting all cyber-physical interfacing of a system into dedicated Interface Holons reduces development time, improves reusability and enhances diagnosability of interfacing problems.AFRIKAANSE OPSOMMING: ndustrie 4.0 (I4.0) is die nuutste tegnologiese revolusie en dit is daarop gemik om industrieë te optimiseer deur middel van drywers soos Kuber-Fisiese Stelsels (KFSs), die Internet of Things (IoT) en vele meer. In die afgelope twee dekades het die holoniese paradigma ʼn belangrike drywer van intelligente vervaardigingstelsels geword, wat dit ideaal maak om I4.0 te bevorder. Die doel van hierdie tesis is om ‘n bestaande holoniese verwysings argitektuur, die Biography-Attributes-Schedule-Execution (BASE-) argitektuur, uit te brei vir komplekse, herkonfigureerbare KFSs. In die konteks van hierdie tesis, word komplekse en herkonfigureerbare stelsels gesien as stelsels wat bestaan uit menige diverse, outonome entiteite wat met mekaar interaksie het en waarvan die funksionaliteit, organisasie en grootte verwag is om te verander met verloop van tyd. Hierdie tesis pas die beginsels van holoniese stelsels toe om die kompleksiteit van KFSs te bestuur en om herkonfigureerbaarheid van KFSs te verbeter. Die BASE-argitektuur word uitgebrei om twee redes, naamlik om die integrasie van menige diverse entiteite te ondersteun en om die argitektuur se herkonfigureerbaarheid te verbeter. Die studie sal ‘n navorsingsbydrae lewer oor holoniese stelsels deur twee belangrike funksionaliteite van stelsels wat geïmplementeer is deur middel van holoniese stelsels aan te spreek – samewerking tussen holons en kuber-fisiese koppeling. Die belangrikste uitbreidings wat gemaak is aan die argitektuur was om skaleerbaarheid moontlik te maak, samewerking tussen holons te verfyn en om kuber-fisiese koppelingsdienste te integreer as holons. Hierdie uitbreidings sluit nuwe platformbestuurkomponente en gestandaardiseerde plugins in. Die uitgebreide argitektuur is geïmplementeer op ʼn opvoedkundige skaapplaas, omdat die skaapplaas baie heterogene hulpbronne (skape, kampe, sensors, mense, ens.) insluit wat in die BASE-argitektuur geïmplementeerde KFS geïntegreer kon word. v Hierdie gevallestudie-implementering moes data van verskillende sensors integreer, intydse analises doen van die waargeneemde data en wanneer nodig, ‘n entiteit in die fisiese wêreld inlig van enige probleme in die KFS. Aan die einde van die implementering is ʼn evaluering gedoen deur die vereistes van ʼn komplekse, herkonfigureerbare KFS as evalueringskriteria te gebruik. Die evaluering het bestaan uit die opstel van kwantitatiewe en kwalitatiewe evalueringsmaatreëls, die uitvoer van die evaluerings en ʼn bespreking van wat die evalueringsresultate aandui oor die effektiwiteit en doeltreffendheid van die uitbreidings wat aan die BASE- argitektuur gemaak is. Dit is bevind dat die uitbreidings wat gemaak is aan die BASE-argitektuur robuustheid en veerkragtigheid verbeter het. Die gebruik van Erlang het ʼn groot rol gespeel in die gevolglike betroubaarheid. Die uitbreidings aan die BASE- argitektuur het ook gehelp om die argitektuur volledig skaleerbaar te maak en om ontwikkelingsproduktiwiteit te verbeter. Laastens, bewys die uitbreidings die voordele van diensoriëntasie in die samewerking tussen holons en hoe die gebruik van Koppelings Holons (Interface Holons) ontwikkelingstyd verminder, die herbruikbaarheid van programbronkode verbeter en diagnoseerbaarheid van koppelingsprobleme versterk.Master

Development of a context-aware internet of things framework for remote monitoring services

Asset management is concerned with the management practices necessary to maximise the value delivered by physical engineering assets. Internet of Things (IoT)-generated data are increasingly considered as an asset and the data asset value needs to be maximised too. However, asset-generated data in practice are often collected in non-actionable form. Moreover, IoT data create challenges for data management and processing. One way to handle challenges is to introduce context information management, wherein data and service delivery are determined through resolving the context of a service or data request. This research was aimed at developing a context awareness framework and implementing it in an architecture integrating IoT with cloud computing for industrial monitoring services. The overall aim was achieved through a methodological investigation consisting of four phases: establish the research baseline, define experimentation materials and methods, framework design and development, as well as case study validation and expert judgment. The framework comprises three layers: the edge, context information management, and application. Moreover, a maintenance context ontology for the framework has developed focused on modelling failure analysis of mechanical components, so as to drive monitoring services adaptation. The developed context-awareness architecture is expressed business, usage, functional and implementation viewpoints to frame concerns of relevant stakeholders. The developed framework was validated through a case study and expert judgement that provided supporting evidence for its validity and applicability in industrial contexts. The outcomes of the work can be used in other industrially-relevant application scenarios to drive maintenance service adaptation. Context adaptive services can help manufacturing companies in better managing the value of their assets, while ensuring that they continue to function properly over their lifecycle.Manufacturin