From Sensors to Visualization Dashboards: Need for Language Composition

International audienceIn the context of the Internet of Things, the SensApp platform is designed to collect data from sensors and support the building of associated monitoring dashboards. Bridging the gap between sensors and visualization involves up to eleven kind of models, from state machine modeling the behavior of a sensor to task diagrams modeling the actions of the end-user. This paper describes this case study, emphasizing the need for domain specific modeling language composition mechanisms to support the activity of modeling modern software-intensive systems

Proposal of a Conceptual Architecture System for Informing the User in the IoT Environment

Design and development of systems for delivering real-time information to people with disabilities and elderly persons need to be based on defined user requirements. For this purpose, the user requirements have been defined in this paper according to the everyday needs of people who use traffic networks and move in closed spaces. The logical presentation of the functionality of the informing system operation and its subsystems includes all the information (data) important for designing a user information delivery system. The paper presents a conceptual architecture system for delivering user informing services related to the environment based on the Internet of Things concept. The aim of the user informing service is an increase in the level of mobility of persons with disabilities and the senior age groups of users. In order to check the operation of the proposed architecture, the informing system operation was monitored on Arduino Uno and Raspberry Pi platforms in laboratory conditions. A simulation confirmed the interdependence of individual data from different subsystems in order to provide real-time information to the system user. The proposed conceptual architecture can contribute to a more efficient approach to the modeling of assistive technologies (with the aim of informing the users) based on dew/fog/cloud technologies in the Internet of Things  environment.</p

Goal-based Workflow Adaptation for Role-based Resources in the Internet of Things

In recent years, the Internet of Things (IoT) has increasingly received attention from the Business Process Management (BPM) community. The integration of sensors and actuators into Process-Aware Information Systems (PAIS) enables the collection of real-time data about physical properties and the direct manipulation of real-world objects. In a broader sense, IoT-aware workflows provide means for context-aware workflow execution involving virtual and physical entities. However, IoT-aware workflow management imposes new requirements on workflow modeling and execution that are outside the scope of current modeling languages and workflow management systems. Things in the IoT may vanish, appear or stay unknown during workflow execution, which renders their allocation as workflow resources infeasible at design time. Besides, capabilities of Things are often intended to be available only in a particular real-world context at runtime, e.g., a service robot inside a smart home should only operate at full speed, if there are no residents in direct proximity. Such contextual restrictions for the dynamic exposure of resource capabilities are not considered by current approaches in IoT resource management that use services for exposing device functionalities. With this work, we aim at providing the modeling and runtime support for defining such restrictions on workflow resources at design time and enabling the dynamic and context-sensitive runtime allocation of Things as workflow resources. To achieve this goal, we propose contributions to the fields of resource management, i.e., resource perspective, and workflow management in the Internet of Things (IoT), divided into the user perspective representing the workflow modeling phase and the workflow perspective representing the runtime resource allocation phase. In the resource perspective, we propose an ontology for the modeling of Things, Roles, capabilities, physical entities, and their context-sensitive interrelations. The concept of Role is used to define non-exclusive subsets of capabilities of Things. A Thing can play a certain Role only under certain contextual restrictions defined by Semantic Web Rule Language (SWRL) rules. At runtime, the existing relations between the individuals of the ontology represent the current state of interactions between the physical and the cyber world. Through the dynamic activation and deactivation of Roles at runtime, the behavior of a Thing can be adapted to the current physical context. In the user perspective, we allow workflow modelers to define the goal of a workflow activity either by using semantic queries or by specifying high-level goals from a Tropos goal model. The goal-based modeling of workflow activities provides the most flexibility regarding the resource allocation as several leaf goals may fulfill the user specified activity goal. Furthermore, the goal model can include additional Quality of Service (QoS) parameters and the positive or negative contribution of goals towards these parameters. The workflow perspective includes the Semantic Access Layer (SAL) middleware to enable the transformation of activity goals into semantic queries as well as their execution on the ontology for role-based Things. The SAL enables the discovery of fitting Things, their allocation as workflow resources, the invocation of referenced IoT services, and the continuous monitoring of the allocated Things as part of the ontology. We show the feasibility and added value of this work in relation to related approaches by evaluation within several application scenarios in a smart home setting. We compare the fulfillment of quantified criteria for IoT-aware workflow management based on requirements extracted from related research. The evaluation shows, that our approach enables an increase in the context-aware modeling of Things as workflow resources, in the query support for workflow resource allocation, and in the modeling support of activities using Things as workflow resources.:1 Introduction 15 1.1 Background 17 1.2 Motivation 17 1.3 Aim and Objective 19 1.3.1 Research Questions and Scope 19 1.3.2 Research Goals 20 1.4 Contribution 20 1.5 Outline 21 2 Background for Workflows in the IoT 23 2.1 Resource Perspective 24 2.1.1 Internet of Things 24 2.1.2 Context and Role Modeling 27 2.2 User Perspective 37 2.2.1 Goal Modeling 38 2.2.2 Tropos Goal Modeling Language 38 2.3 Workflow Perspective 39 2.3.1 Workflow Concepts 39 2.3.2 Workflow Modeling 40 2.3.3 Internet of Things-aware Workflow Management 43 2.4 Summary 44 3 Requirements Analysis and Approach 45 3.1 Requirements 45 3.1.1 IoT Resource Perspective 46 3.1.2 Workflow Resource Perspective 50 3.1.3 Relation to Research Questions 51 3.2 State of the Art Analysis 53 3.2.1 Fulfillment Criteria 54 3.2.2 IoT-aware workflow management 56 3.3 Discussion 65 3.4 Approach 70 3.4.1 Contribution to IoT-aware workflow management 71 3.5 Summary 73 4 Concept for Adaptive Workflow Activities in the IoT 75 4.1 Resource Perspective 75 4.1.1 Role-based Things 75 4.1.2 Semantic Modeling Concepts 79 4.1.3 SWRL Modeling Concepts 81 4.2 User Perspective 81 4.2.1 Semantic Queries in Workflow Activites 81 4.2.2 Goals for Workflow Activites 81 4.2.3 Mapping from Goals to Semantic Queries 82 4.3 Workflow Perspective 83 4.3.1 Workflow metamodel Extensions 83 4.3.2 Middleware for Dynamic Resource Discovery and Allocation 85 4.4 Summary 86 5 Modeling Adaptive Workflow Activities in the IoT 87 5.1 Resource Perspective 87 5.1.1 Role-based Modeling of Context-sensitive Things 87 5.1.2 Ontology Classes 90 5.1.3 Ontology Object properties 93 5.1.4 Ontology Data properties 99 5.1.5 DL-safe SWRL Rules 100 5.2 Discussion of Role Modeling Features 101 5.3 Example Application Scenario Modeling 102 5.3.1 Resource Perspective 102 5.3.2 User Perspective 105 5.3.3 Workflow Perspective 109 5.4 Summary 113 6 Architecture for Adaptive Workflow Activities in the IoT 115 6.1 Overview of the System Architecture 115 6.2 Specification of System Components 117 6.2.1 Resource Perspective 118 6.2.2 User Perspective 118 6.2.3 Workflow Perspective 118 6.3 Summary 123 7 Implementation of Adaptive Workflow Activities in the IoT 125 7.1 Resource Perspective 125 7.2 Workflow Perspective 125 7.2.1 PROtEUS 125 7.2.2 Semantic Access Layer 127 7.3 User Perspective 128 7.4 Summary 128 8 Evaluation 129 8.1 Goal and Evaluation Approach 129 8.1.1 Definition of Test Cases 130 8.2 Scenario Evaluation 134 8.2.1 Ambient Assisted Living Setting 135 8.2.2 Resource Perspective 135 8.2.3 User Perspective 137 8.2.4 Workflow Perspective 138 8.2.5 Execution of Test Cases 139 8.2.6 Discussion of Results 146 8.3 Performance Evaluation 148 8.3.1 Experimental Setup 148 8.3.2 Discussion of Results 151 8.4 Summary 152 9 Discussion 153 9.1 Comparison of Solution to Research Questions 153 9.2 Extendability of the Solutions 155 9.3 Limitations 156 10 Summary and Future Work 157 10.1 Summary of the Thesis 157 10.2 Future Work 159 Appendix 161 Example Semantic Context Model for IoT-Things 171 T-Box of Ontology for Role-based Things in the IoT 178 A-Box for Example Scenario Model 201 A-Box for Extended Example Scenario Model 21

Virtual user in the IoT: definition, technologies and experiments

Virtualization technologies are characterizing major advancements in the Internet of Things (IoT) arena, as they allow for achieving a cyber-physical world where everything can be found, activated, probed, interconnected, and updated at both the virtual and the physical levels. We believe these technologies should apply to human users other than things, bringing us the concept of the Virtual User (VU). This should represent the virtual counterpart of the IoT users with the ultimate goal of: (i) avoiding the user from having the burden of following the tedious processes of setting, configuring and updating IoT services the user is involved in; (ii) acting on behalf of the user when basic operations are required; (iii) exploiting to the best of its ability the IoT potentialities, always taking always account the user profile and interests. Accordingly, the VU is a complex representation of the user and acts as a proxy in between the virtual objects and IoT services and application; to this, it includes the following major functionalities: user profiling, authorization management, quality of experience modeling and management, social networking and context management. In this respect, the major contributions of this paper are to: provide the definition of VU, present the major functionalities, discuss the legal issues related to its introduction, provide some implementation details, and analyze key performance aspects in terms of the capability of the VU to correctly identify the user profile and context

The Scientific Information Exchange General Model at Digital Library Context: Internet of Things

Introduction: This paper aims to develop a Scientific Information Exchange General Model at Digital Library in Context of Internet of things, which would enable automated and efficient library services. To accomplish its objective, the main classes (Concepts), sub-classes, attributes are identified in order to introduce an appropriate model. Methodology: The approach of this study is basic, exploratory, and developmental and is run through a mixed method consisting of documentary, Delphi, and data modeling methods. The study population in the documentary section includes the study of information resources retrieved in related subjects. The study population in the Delphi section is consist of 15 experts in “Internet of Things” and “digital library” domains. The Data gathering procedure is by applying a semi-structured interview. Appropriate software is applied for the analysis. Results: The findings showed that the 9 main classes of “End user”, “librarian”, “Microcomputer”, “Digital library server”, “Automated information services”, “Physical resources”, “Virtual resources”, “Information resources on the digital library server (virtual object)”, and “Security” in general model of scientific information exchange are very contributive. In general, 27 sub-classes and 38 attributes are identified for the main classes for this purpose. In this model, how the classes communicate and interact with one another is illustrated to justify this theme. Conclusion: Here it is deduced that focusing on data protection at two levels of user and server in the main class of security is very important. Focusing on information resources metadata in the entity class, and device to device communication in this model is of essence as well. This proposed model is contributive in information networking in Internet of things-based library systems in providing better services to users. Research value: This model has potential in offering a basic proposal as a startup for automated library services

The Scientific Information Exchange General Model at Digital Library Context: Internet of Things

Introduction: This paper aims to develop a Scientific Information Exchange General Model at Digital Library in Context of Internet of things, which would enable automated and efficient library services. To accomplish its objective, the main classes (Concepts), sub-classes, attributes are identified in order to introduce an appropriate model. Methodology: The approach of this study is basic, exploratory, and developmental and is run through a mixed method consisting of documentary, Delphi, and data modeling methods. The study population in the documentary section includes the study of information resources retrieved in related subjects. The study population in the Delphi section is consist of 15 experts in “Internet of Things” and “digital library” domains. The Data gathering procedure is by applying a semi-structured interview. Appropriate software is applied for the analysis. Results: The findings showed that the 9 main classes of “End user”, “librarian”, “Microcomputer”, “Digital library server”, “Automated information services”, “Physical resources”, “Virtual resources”, “Information resources on the digital library server (virtual object)”, and “Security” in general model of scientific information exchange are very contributive. In general, 27 sub-classes and 38 attributes are identified for the main classes for this purpose. In this model, how the classes communicate and interact with one another is illustrated to justify this theme. Conclusion: Here it is deduced that focusing on data protection at two levels of user and server in the main class of security is very important. Focusing on information resources metadata in the entity class, and device to device communication in this model is of essence as well. This proposed model is contributive in information networking in Internet of things-based library systems in providing better services to users. Research value: This model has potential in offering a basic proposal as a startup for automated library services

C-Remor: UVC-Room Sterilization Mobile Robot

Mobile robots can be used in a variety of Internet of Things projects. The sterilization robot is created in the form of a mobile robot by combining two microcontrollers. The Arduino Uno microcontroller provides a sensor acquisition device, while the ESP32-cam provides the actuator controller, which is linked to the Wi-Fi network displayed on the web server. The millis function has been used in the Arduino module programming process because it requires doing tasks at the same time. This modeling system has an accuracy of about 80% for Arduino module settings as sensor controllers and 80%-86% for ESP32-cam modules as user interfaces and actuator controllers. This is due to the sensor's limited range and the Wi-Fi network used