A systematic literature review on IoT-aware business process modeling views, requirements and notations

The Internet of things has been adopted in several sectors both influencing how people work and enhancing organizations' business processes. This resulted in the rise of relevant research topics such as IoT-aware business processes. The modeling of these processes makes it possible to better understand working scenarios and to support the adoption of model-driven development approaches for IoT-aware and process-oriented software systems. Since much research has been performed on this topic, a better awareness of the current status is needed. This paper reports a systematic literature review to develop a map on modeling notations for IoT-aware business processes. The survey mainly adopts an academic point of view, resulting in the detailed analysis of 84 research works from the leading computer science digital libraries. The output of the review is in the form of schemes and reflections. In particular, our research aims to shed light on (1) the relevant modeling views referring to different types of IoT-aware business processes; (2) the IoT requirements supported by the modeling notations; and (3) the modeling notations proposed and/or adopted to model IoT-aware business processes. Finally, our research work highlights possible future research lines needing further investigations

Modeling, Executing and Monitoring IoT-Driven Business Rules in BPMN and DMN: Current Support and Challenges

The involvement of the Internet of Things (IoT) in Business Process Management (BPM) solutions is continuously increasing. While BPM enables the modeling, implementation, execution, monitoring, and analysis of business processes, IoT fosters the collection and exchange of data over the Internet. By enriching BPM solutions with real-world IoT data both process automation and process monitoring can be improved. Furthermore, IoT data can be utilized during process execution to realize IoT-driven business rules that consider the state of the physical environment. The aggregation of low-level IoT data into processrelevant, high-level IoT data is a paramount step towards IoT-driven business processes and business rules respectively. In this context, Business Process Modeling and Notation (BPMN) and Decision Model and Notation (DMN) provide support to model, execute, and monitor IoTdriven business rules, but some challenges remain. This paper derives the challenges that emerge when modeling, executing, and monitoring IoT-driven business rules using BPMN 2.0 and DMN standards

Executable Digital Process Twins: Towards the Enhancement of Process-Driven Systems

The development of process-driven systems and the advancements in digital twins have led to the birth of new ways of monitoring and analyzing systems, i.e., digital process twins. Specifically, a digital process twin can allow the monitoring of system behavior and the analysis of the execution status to improve the whole system. However, the concept of the digital process twin is still theoretical, and process-driven systems cannot really benefit from them. In this regard, this work discusses how to effectively exploit a digital process twin and proposes an implementation that combines the monitoring, refinement, and enactment of system behavior. We demonstrated the proposed solution in a multi-robot scenario

Development of a spatial data infrastructure for precision agriculture applications

Precision agriculture (PA) is the technical answer to tackling heterogeneous conditions in a field. It works through site specific operations on a small scale and is driven by data. The objective is an optimized agricultural field application that is adaptable to local needs. The needs differ within a task by spatial conditions. A field, as a homogenous-planted unit, exceeds by its size the scale units of different landscape ecological properties, like soil type, slope, moisture content, solar radiation etc. Various PA-sensors sample data of the heterogeneous conditions in a field. PA-software and Farm Management Information Systems (FMIS) transfer the data into status information or application instructions, which are optimized for the local conditions. The starting point of the research was the determination that the process of PA was only being used in individual environments without exchange between different users and to other domains. Data have been sampled regarding specific operations, but the model of PA suffers from these closed data streams and software products. Initial sensors, data processing and controlled implementations were constructed and sold as monolithic application. An exchange of hard- or software as well as of data was not planned. The design was focused on functionality in a fixed surrounding and conceived as being a unit. This has been identified as a disadvantage for ongoing developments and the creation of added value. Influences from the outside that may be innovative or even inspired cannot be considered. To make this possible, the underlying infrastructure must be flexible and optimized for the exchange of data. This thesis explores the necessary data handling, in terms of integrating knowledge of other domains with a focus on the geo-spatial data processing. As PA is largely dependent on geographical data, this work develops spatial data infrastructure (SDI) components and is based on the methods and tools of geo-informatics. An SDI provides concepts for the organization of geospatial components. It consists of spatial- and metadata in geospatial workflows. The SDI in the center of these workflows is implemented by technologies, policies, arrangements, and interfaces to make the data accessible for various users. Data exchange is the major aim of the concept. As previously stated, data exchange is necessary for PA operations, and it can benefit from defined components of an SDI. Furthermore, PA-processes gain access to interchange with other domains. The import of additional, external data is a benefit. Simultaneously, an export interface for agricultural data offers new possibilities. Coordinated communication ensures understanding for each participant. From the technological point of view, standardized interfaces are best practice. This work demonstrates the benefit of a standardized data exchange for PA, by using the standards of the Open Geospatial Consortium (OGC). The OGC develops and publishes a wide range of relevant standards, which are widely adopted in geospatially enabled software. They are practically proven in other domains and were implemented partially in FMIS in the recent years. Depending on their focus, they could support software solutions by incorporating additional information for humans or machines into additional logics and algorithms. This work demonstrates the benefits of standardized data exchange for PA, especially by the standards of the OGC. The process of research follows five objectives: (i) to increase the usability of PA-tools in order to open the technology for a wider group of users, (ii) to include external data and services seamlessly through standardized interfaces to PA-applications, (iii) to support exchange with other domains concerning data and technology, (iv) to create a modern PA-software architecture, which allows new players and known brands to support processes in PA and to develop new business segments, (v) to use IT-technologies as a driver for agriculture and to contribute to the digitalization of agriculture.Precision agriculture (PA) ist die technische Antwort, um heterogenen Bedingungen in einem Feld zu begegnen. Es arbeitet mit teilflächenspezifischen Handlungen kleinräumig und ist durch Daten angetrieben. Das Ziel ist die optimierte landwirtschaftliche Feldanwendung, welche an die lokalen Gegebenheiten angepasst wird. Die Bedürfnisse unterscheiden sich innerhalb einer Anwendung in den räumlichen Bedingungen. Ein Feld, als gleichmäßig bepflanzte Einheit, überschreitet in seiner Größe die räumlichen Einheiten verschiedener landschaftsökologischer Größen, wie den Bodentyp, die Hangneigung, den Feuchtigkeitsgehalt, die Sonneneinstrahlung etc. Unterschiedliche Sensoren sammeln Daten zu den heterogenen Bedingungen im Feld. PA-Software und farm management information systems (FMIS) überführen die Daten in Statusinformationen oder Bearbeitungsanweisungen, die für die Bedingungen am Ort optimiert sind. Ausgangspunkt dieser Dissertation war die Feststellung, dass der Prozess innerhalb von PA sich nur in einer individuellen Umgebung abspielte, ohne dass es einen Austausch zwischen verschiedenen Nutzern oder anderen Domänen gab. Daten wurden gezielt für Anwendungen gesammelt, aber das Modell von PA leidet unter diesen geschlossenen Datenströmen und Softwareprodukten. Ursprünglich wurden Sensoren, die Datenverarbeitung und die Steuerung von Anbaugeräten konstruiert und als monolithische Anwendung verkauft. Ein Austausch von Hard- und Software war ebenso nicht vorgesehen wie der von Daten. Das Design war auf Funktionen in einer festen Umgebung ausgerichtet und als eine Einheit konzipiert. Dieses zeigte sich als Nachteil für weitere Entwicklungen und bei der Erzeugung von Mehrwerten. Äußere innovative oder inspirierende Einflüsse können nicht berücksichtigt werden. Um dieses zu ermöglichen muss die darunterliegende Infrastruktur flexibel und auf einen Austausch von Daten optimiert sein. Diese Dissertation erkundet die notwendige Datenverarbeitung im Sinne der Integration von Wissen aus anderen Bereichen mit dem Fokus auf der Verarbeitung von Geodaten. Da PA sehr abhängig von geographischen Daten ist, werden in dieser Arbeit die Bausteine einer Geodateninfrastruktur (GDI) entwickelt, die auf den Methoden undWerkzeugen der Geoinformatik beruhen. Eine GDI stellt Konzepte zur Organisation räumlicher Komponenten. Sie besteht aus Geodaten und Metadaten in raumbezogenen Arbeitsprozessen. Die GDI, als Zentrum dieser Arbeitsprozesse, wird mit Technologien, Richtlinien, Regelungen sowie Schnittstellen, die den Zugriff durch unterschiedliche Nutzer ermöglichen, umgesetzt. Datenaustausch ist das Hauptziel des Konzeptes. Wie bereits erwähnt, ist der Datenaustausch wichtig für PA-Tätigkeiten und er kann von den definierten Komponenten einer GDI profitieren. Ferner bereichert der Austausch mit anderen Gebieten die PA-Prozesse. Der Import zusätzlicher Daten ist daher ein Gewinn. Gleichzeitig bietet eine Export-Schnittstelle für landwirtschaftliche Daten neue Möglichkeiten. Koordinierte Kommunikation sichert das Verständnis für jeden Teilnehmer. Aus technischer Sicht sind standardisierte Schnittstellen die beste Lösung. Diese Arbeit zeigt den Gewinn durch einen standardisierten Datenaustausch für PA, indem die Standards des Open Geospatial Consortium (OGC) genutzt wurden. Der OGC entwickelt und publiziert eine Vielzahl von relevanten Standards, die eine große Reichweite in Geo-Software haben. Sie haben sich in der Praxis anderer Bereiche bewährt und wurden in den letzten Jahren teilweise in FMIS eingesetzt. Abhängig von ihrer Ausrichtung könnten sie Softwarelösungen unterstützen, indem sie zusätzliche Informationen für Menschen oder Maschinen in zusätzlicher Logik oder Algorithmen integrieren. Diese Arbeit zeigt die Vorzüge eines standardisierten Datenaustauschs für PA, insbesondere durch die Standards des OGC. Die Ziele der Forschung waren: (i) die Nutzbarkeit von PA-Werkzeugen zu erhöhen und damit die Technologie einer breiteren Gruppe von Anwendern verfügbar zu machen, (ii) externe Daten und Dienste ohne Unterbrechung sowie über standardisierte Schnittstellen für PA-Anwendungen einzubeziehen, (iii) den Austausch mit anderen Bereichen im Bezug auf Daten und Technologien zu unterstützen, (iv) eine moderne PA-Softwarearchitektur zu erschaffen, die es neuen Teilnehmern und bekannten Marken ermöglicht, Prozesse in PA zu unterstützen und neue Geschäftsfelder zu entwickeln, (v) IT-Technologien als Antrieb für die Landwirtschaft zu nutzen und einen Beitrag zur Digitalisierung der Landwirtschaft zu leisten

Extending BPMN for integration of internet of things devices with process-driven applications

Internet of Things (IoT) is a rising technology, which is becoming an important building block of information systems in many different areas, including enterprise environments. For IoT to become a part of process-driven enterprise applications, process modelling notations have to be extended. This thesis focuses on introducing a modelling notation for modelling of properties of real-world entities. It also improves the modelling of IoT devices and different communication types used by them. To solve stated problems, we propose six solutions in form of modelling approaches with corresponding extensions to BPMN. Proposed solutions are based upon and evaluated against four sets of identified requirements. Solution, which satisfies the highest number of requirements, is our final solution and is an adequate answer to our research questions

Extending BPMN for integration of internet of things devices with process-driven applications

Internet of Things (IoT) is a rising technology, which is becoming an important building block of information systems in many different areas, including enterprise environments. For IoT to become a part of process-driven enterprise applications, process modelling notations have to be extended. This thesis focuses on introducing a modelling notation for modelling of properties of real-world entities. It also improves the modelling of IoT devices and different communication types used by them. To solve stated problems, we propose six solutions in form of modelling approaches with corresponding extensions to BPMN. Proposed solutions are based upon and evaluated against four sets of identified requirements. Solution, which satisfies the highest number of requirements, is our final solution and is an adequate answer to our research questions

Model-driven engineering techniques and tools for machine learning-enabled IoT applications: A scoping review

This paper reviews the literature on model-driven engineering (MDE) tools and languages for the internet of things (IoT). Due to the abundance of big data in the IoT, data analytics and machine learning (DAML) techniques play a key role in providing smart IoT applications. In particular, since a significant portion of the IoT data is sequential time series data, such as sensor data, time series analysis techniques are required. Therefore, IoT modeling languages and tools are expected to support DAML methods, including time series analysis techniques, out of the box. In this paper, we study and classify prior work in the literature through the mentioned lens and following the scoping review approach. Hence, the key underlying research questions are what MDE approaches, tools, and languages have been proposed and which ones have supported DAML techniques at the modeling level and in the scope of smart IoT services.info:eu-repo/semantics/publishedVersio

A Model-Driven Engineering Approach for the Service Integration of IoT Systems

With the development of IoT devices and web services, the objects of the real world are more interconnected, which allows applications to extend their characteristics in different fields, including industrial or home environments, among other possible examples such as health, trade, transport, or agriculture. However, this development highlights the challenge of interoperability, because devices are heterogeneous and use different communication protocols and different data formats. For this reason, we propose a model for point-to-point integration in three-layer IoT applications: (a) hardware, which corresponds to the physical objects (controller, sensor and actuator), (b) communication, which is the bridge that allows the exchange of data between a MQTT queue and REST web services, and (c) integration, which establishes a sequence of transactions to coordinate the components of the system. For this purpose, a metamodel, a graphic editor and a code generator have been developed that allow the developer to design IoT systems formed by heterogeneous components without having in-depth knowledge of every hardware and software platform. In order to validate our proposal, a smart home scenario has been developed, with a series of sensors and actuators that combined show a complex behavior

Monitoring and Information Alignment in Pursuit of an IoT-Enabled Self-Sustainable Interoperability

To remain competitive with big corporations, small and medium-sized enterprises (SMEs) often need to be more dynamic, adapt to new business situations, react faster, and thereby survive in today‘s global economy. To do so, SMEs normally seek to create consortiums, thus gaining access to new and more opportunities. However, this strategy may also lead to complications. Due to the different sources of enterprise models and semantics, organizations are experiencing difficulties in seamlessly exchanging vital information via electronic means. In their attempt to address this issue, most seek to achieve interoperability by establishing peer-to-peer mappings with different business partners, or by using neutral data standards to regulate communications in optimized networks. Moreover, systems are more and more dynamic, frequently changing to answer new customer‘s requirements, causing new interoperability problems and a reduction of efficiency. Another situation that is constantly changing is the devices used in the enterprises, as the Enterprise Information Systems, devices are used to register internal data, and to be used to monitor several aspects. These devices are constantly changing, following the evolution and growth of the market. So, it is important to monitor these devices and doing a model representation of them. This dissertation proposes a self-sustainable interoperable framework to monitor existing enterprise information systems and their devices, monitor the device/enterprise network for changes and automatically detecting model changes. With this, network harmonization disruptions are detected in a timely way, and possible solutions are suggested to regain the interoperable status, thus enhancing robustness for reaching sustainability of business networks along time