A novel multi-level evaluation approach for human-coupled IoT applications

Introducing semantics into the Internet of Things (IoT) has been attracting increasing attention from researchers and industrial practitioners. Interoperability stays a critical weight to the engineers of the Internet of Things Systems. This is because of the way that the IoT gadgets are exceptionally heterogeneous as far as fundamental correspondence protocol, information organizations, and advances. Our spotlight in this section is on information semantics, liable for definition, the board, and preparing of information. The Internet of Things (IoT), true to form the foundation for the imagined idea of Smart structure, brings new conceivable outcomes for the structure of the executives. IoT vision presents promising and practical answers for gigantic information assortment and its investigation which can be applied in numerous areas thus cause them to work all the more productively. End-user development programming environments in the IoT enable end-users to customize their IoT objects’ joint behavior, typically via IFTTT trigger-action rules. Aim of the chapter to propose an IoT based Semantic Interoperability Model with EUPont Semantic Web ontology to provide Semantic Interoperability among heterogeneous IoT devices for control of end-user applications.

With the growth of the internet of things (IoT) smart objects, managing these objects becomes a very important challenge, to know the total number of interconnected objects on a heterogeneous network, and if they are functioning correctly; the use of IoT objects can have advantages in terms of comfort, efficiency, and cost. In this context, the identification of IoT objects is the first step to help owners manage them and ensure the security of their IoT environments such as smart homes, smart buildings, or smart cities. In this paper, to meet the need for IoT object identification, we have deployed an intelligent environment to collect all network traffic traces based on a diverse list of IoT in real-time conditions. In the exploratory phase of this traffic, we have developed learning models capable of identifying and classifying connected IoT objects in our environment. We have applied the six supervised machine learning algorithms: support vector machine, decision tree (DT), random forest (RF), k-nearest neighbors, naive Bayes, and stochastic gradient descent classifier. Finally, the experimental results indicate that the DT and RF models proved to be the most effective and demonstrate an accuracy of 97.72% on the analysis of network traffic data and more particularly information contained in network protocols. Most IoT objects are identified and classified with an accuracy of 99.21%.

The Routed Discrete Event System Specification (RDEVS) is a modular and hierarchical Modeling and Simulation (M&S) formalism based on the Discrete Event System Specification (DEVS) formalism that provides a set of design models for dealing with routing problems over DEVS. At the formal level, RDEVS models (as DEVS models themselves) are defined mathematically. However, software implementations of both formalisms are based on an object-oriented paradigm. Furthermore, at the implementation design level, the RDEVS formalism is represented by a conceptual model that uses DEVS simulators as execution engines. Even when RDEVS models can be executed with DEVS simulators, the resulting data (obtained as execution outputs) remains DEVS-based, restricting the study of event flows between models influenced by routing policies. This paper shows how the RDEVS formalism design was enhanced to include event tracking in the models without altering their expected behavior during simulation. Such an improvement is based on adding new features to existing RDEVS components. These features are defined as trackers, which are responsible for getting structured data from events exchanged during RDEVS executions. The proposed solution employs the Decorator pattern as a software engineering option to achieve the required goal. It was deployed as a Java package attached to the RDEVS library, devoted to collecting structured event flow data using JavaScript Object Notation (JSON). The results highlight the modeling benefits of adding event tracking to the original capabilities of the RDEVS formalism. For the M&S community, the novel contribution is an advance in understanding how best modeling practices of software engineering can be used to enhance their software tools in general and the RDEVS formalism in particular.

The Internet of Things (IoT) may be defined as a collection of independent and dependent devices as well as human agents that form a network. IoT has provided a promising opportunity to build powerful industrial and enterprise systems that in turns offers conveniences and efficiency to achieve better quality of life. With the lucrative IoT benefits, also come new security and privacy challenges in terms of the confidentiality, authenticity, and integrity of the data sensed, collected, and exchanged by the IoT objects. These challenges make IoT deployments extremely vulnerable to different types of security attacks, resulting in insecure IoT environments. Therefore, it is necessary to carry out situation assessment to identify possible security risks to develop a complete picture of secure IoT deployments. In this paper, we present basic elements of IoT models and provide situation assessment for IoT applications. We have highlighted the security enhancement measures for the IoT applications based on the three domain (local, transfer and data storage) of the IoT model. Trends within situation assessment for security area will be highlighted in addition to identification of niche areas where future efforts will be directed.

Internet of Things (IoT) applications are generally developed in a vertical manner, i.e., each IoT application is developed for a certain scenario which generally does not share data with IoT applications for recommendation services. This leads to an inefficient exploitation of other IoT service applications. In fact, such recommendation services can be achieved with the help of Social IoT (SIoT) by using data generated by various IoT applications. SIoT builds a profile of objects based on IoT applications data that can be exchanged with SIoT network for accessible to other IoT applications. In this manner, the SIoT network provides recommendation services for reusability of IoT applications' data among various IoT applications, as well as adapting IoT services according to users' needs which improve user experience. Additionally, the profiles built by a SIoT network can also help a single IoT application by looking for similar conditions that have been addressed in the past for the same IoT application. We propose a concept for exploiting the SIoT for recommendation services among various IoT applications with the help of a sample application scenario that highlights how the SIoT can help by providing recommendations. We also provide some implementation challenges for this concept.

In this paper, we introduce a novel parallelization technique for Discrete Event System Specification (DEVS) simulation of continuous and hybrid systems. Here, like in most parallel discrete event simulation methodologies, the models are first split into several sub-models which are then concurrently simulated on different processors. In order to avoid the cost of the global synchronization of all processes, the simulation time of each sub-model is locally synchronized in a real-time fashion with a scaled version of physical time, which implicitly synchronizes all sub-models. The new methodology, coined Scaled Real-Time Synchronization (SRTS), does not ensure a perfect synchronization in its implementation. However, under certain conditions, the synchronization error introduced only provokes bounded numerical errors in the simulation results. SRTS uses the same physical time-scaling parameter throughout the entire simulation. We also developed an adaptive version of the methodology (Adaptive-SRTS) where this parameter automatically evolves during the simulation according to the workload. We implemented the SRTS and Adaptive-SRTS techniques in PowerDEVS, a DEVS simulation tool, under a real-time operating system called the Real-Time Application Interface. We tested their performance by simulating three large-scale models, obtaining in all cases a considerable speedup.

Most data nowadays are stored in the cloud; therefore, cloud computing and its extension—fog computing—are the most in-demand services at the present time. Cloud and fog computing platforms are largely used by Internet of Things (IoT) applications where various mobile devices, end users, PCs, and smart objects are connected to each other via the internet. IoT applications are common in several application areas, such as healthcare, smart cities, industries, logistics, agriculture, and many more. Due to this, there is an increasing need for new security and privacy techniques, with attribute-based encryption (ABE) being the most effective among them. ABE provides fine-grained access control, enables secure storage of data on unreliable storage, and is flexible enough to be used in different systems. In this paper, we survey ABE schemes, their features, methodologies, benefits/drawbacks, attacks on ABE, and how ABE can be used with IoT and its applications. This survey reviews ABE models suitable for IoT platforms, taking into account the desired features and characteristics. We also discuss various performance indicators used for ABE and how they affect efficiency. Furthermore, some selected schemes are analyzed through simulation to compare their efficiency in terms of different performance indicators. As a result, we find that some schemes simultaneously perform well in one or two performance indicators, whereas none shines in all of them at once. The work will help researchers identify the characteristics of different ABE schemes quickly and recognize whether they are suitable for specific IoT applications. Future work that may be helpful for ABE is also discussed.

The integration of Internet of Things (IoT) systems with social networking concepts has opened new business and social opportunities, particularly by allowing smart objects to autonomously establish social relationships with each other and exchange information. However, these relations must be properly quantified and integrated with trust in order to proliferate the provisioning of IoT composite services. Therefore, this proposed work focuses on quantitatively computing social strength and trust among smart objects in IoT for the purpose of aiding efficient service composition with reasonable accuracy. In particular, we propose a trust-augmented social strength (TASS) management protocol that can cope with the heterogeneity of IoT and demonstrate high scalability and resiliency against various malicious attacks. Afterward, we show how the TASS measurements can be applied to service planning in IoT service composition. Based on the experimental results, we conclude that the proposed protocol is, in fact, capable of exhibiting the above-mentioned characteristics in real-world settings.

One of the most challenging objectives of the Internet of Things (IoT) domain is the identification of interaction paradigms and communication standards to integrate smart objects (SOs), i.e., physical objects able to interact with the network. Such interaction paradigms and communication protocols belong to what can be called the IoT application layer, on which this paper focuses. This paper presents app execution platform (AEP), a platform that supports the design, deployment, execution, and management of IoT applications in the domain of smart home, smart car, and smart city. AEP was designed to coherently fulfill a set of requirements covered only partially or in a fragmented way by other IoT application platforms. AEP focuses on SO virtualization and on composite application (CA) orchestration and supports dynamic object availability.

The correct implementation and behavior of Internet of Things (IoT) applications are seldom investigated in the literature. This paper shows how the simulation mechanism can be integrated well into an IoT application development platform for correct implementation and behavior investigation. We use an IoT application development platform called IoTtalk as an example to describe how the simulation mechanism called SimTalk can be built into this IoT platform. We first elaborate on how to implement the simulator for an input IoT device (a sensor). Then we describe how an output IoT device (an actuator) can be simulated by an animated simulator. We use a smart farm application to show how the simulated sensors are used for correct implementation. We use applications including interactive art (skeleton art and water dance) and the pendulum physics experiment as examples to illustrate how IoT application behavior investigation can be achieved in SimTalk. As the main outcome of this paper, the SimTalk simulation codes can be directly reused for real IoT applications. Furthermore, SimTalk is integrated well with an IoT application verification tool in order to formally verify the IoT application configuration. Such features have not been found in any IoT simulators in the world.

Ensuring the integrity of Internet of Things (IoT) objects is challenging due to their limited energy and processing resources, as well as their exposure to security threats. Remote Attestation (RA) is a widely used technique that enables a trusted entity, such as a gateway, to verify the integrity of constrained IoT devices remotely. However, applying RA in constrained environments introduces challenges, including redundant attestations, high energy consumption, and vulnerabilities, such as Time-of-Check-Time-of-Use (TOCTOU) attacks. To address these limitations, this paper proposes a novel autonomic IoT framework for self-managing the integrity of IoT objects using a lightweight remote attestation mechanism and the Autonomic Computing paradigm. The proposed approach uses a DBSCAN model to determine when attestation is required, along with a fuzzy-logic system that dynamically selects an appropriate lightweight hash function based on the device state. Meanwhile, the attestation process uses a lightweight HMAC scheme to ensure device integrity. Our proposed framework reduces redundant attestations, optimizes energy consumption, and extends the lifetime of IoT systems, making it suitable for resource-constrained environments.

As a major agricultural province in China, Shandong Province has always played an important role. At the same time, it is also closely related to the strong support of science and technology. As a new technology, the Internet of things (IoT) has made positive contributions. Agricultural IoT is a mode that uses information technology, wireless communication technology and radio frequency automatic identification technology to share the identified agricultural information to the network. The application of agricultural IoT is a major change in agricultural development, which provides convenient conditions for the development of agriculture, provides a favorable environment for the agricultural products, promotes the transformation of agricultural technology, realizes the informatization of agricultural production, improves the efficiency of rural land, integrates agricultural resources and provides a foundation for food safety. In this paper, the application of IoT in the field of agriculture in Shandong Province is described from two practical cases. One is about how to use wireless sensor network technology to transmit data in the big data platform based on the Bohai granary project. The other describes how to use IoT for food quality and safety traceability. It takes pigs as the research object, runs through all links of the whole industrial chain of pig breeding, breeding, slaughtering, processing, logistics and sales, collects the data of the whole industrial chain with the help of IoT, and realizes the information tracking and traceability of the whole industrial chain. At the end of the paper, it discusses the countermeasures.

The internet of things (IoT) is focused in offering new technologies which is changing the business environment by showing the potential in different sectors like retail, transportation, healthcare etc. Through IoT, the managers can gather and process data and information in an effective manner, also they can use them to automate in order to enhance productivity and efficiency. With the usage of such technologies, human resource managers can access information for possible candidates which can be accessed through IoT. The overall behaviour of potential candidate tends to help them in shortlisting and choosing the desirable ones. The application of IoT has emerged in enhancing the recruitment of candidates in search of candidates based on large volume of information, assist in screening the candidates, selecting the most suitable ones. The application of IoT technology can modify the HR roles, enable in changing the company perspective in enhancing recruitment process, source the candidates effectively and select them so as to meet the organisational requirements. The implementation of IoT driven technologies support in removing the biases in screening the candidates and aids in candidate selection with the support of other technologies like artificial intelligence, predictive analytics etc. Furthermore, IoT is also involved in better inventory management as it supports the organisation in converting the data which are sourced through RFID (Radio Frequency Identification) into more insights related to inventory data, location of the products, tracking the movement of goods until it reaches the hands of the customers. With the application of IoT inventory managers possess better control in managing the inventory through automated ordering request and thereby reduce manual time and cost for the business. This paper is focused in presenting a conceptual understanding on the application of environmental IoT in recruitment process and also the overall impact created by the technology in managing the inventory efficiently.KeywordsInternet of thingsRecruitment processInventory managementPredictive analytics

Under the background of prosperity of Internet of things (IoT), in order to accelerate the training of talented persons of China for IoT, we propose to design and develop a new course for Chinese students: Essential Technologies, Applications, and Commercial Patterns of Internet of Things. Aiming at three-dimensional target, which has dimensionalities of attitude and thoughts, knowledge and skills, process and methods, the contents of the course include the following parts: system and application architectures, key technologies of IoT, applications of IoT, commercial patterns of IoT, IoT industry and social significance etc. The course highlights the training of abilities of innovation, creativity, comprehensive analysis and practical operations. The construction of teaching resources, such as textbooks, lecture notes, teaching equipments, practice bases, are also emphasized in the process of development of this course.

The new IoT architecture helps us to build small devices that can sense, process, and communicate so that sensors, embedded, and other 'services can be developed to enable us to understand the surroundings. For continuous cardiovascular health surveillance, the IoT-assisted electrocardiogram (ECG) system for safe data transmission has been suggested. The modern paradigm of the Internet of Things enables the creation of small devices with sensing, processing, and communication capabilities that make sensors, embedded devices, and other 'stuff' capable of understanding the environment The Internet of Things (IoT) and intelligent medical devices have transformed healthcare systems, allowing patient health conditions to be monitored and screened anywhere and every time. Due to the sudden and enormous increase in patients during a pandemic of corona-virus, it is essential that patients are constantly monitored until any serious illness or infection takes place. According to the transfer of the enormous amount of confidential health information produced by patients who do not wish to disclose their personal medical information, Concerns about IoT data protection are still an extremely serious issue. The advances made in IoT technology in recent years have supported interactions between smart objects – things through the Internet in a transparent fashion. One of the applications in IoT is healthcare and sensors, the processor aggregator, and the data storage platform.