Exploitation of social IoT for recommendation services

The revolutionary idea that combines social networks with the Internet of Things (IoT) is called the Social Internet of Things (SIoT). SIoT is a term that refers to the modelling of social networks formed by connecting people and things. SIoT was designed to assist organizations in achieving specific goals, such as boosting usability, scalability, and productivity and satisfying business service requirements. The application layer of the SIoT model performs several tasks like managing the relationship, discovering the services, configuring services, and managing reliability among the devices. The information collected about SIoT is categorized by identifying the relationships between devices. SIoT creates an event identity based on data from IoT applications. This identity may then be transferred with the SIoT network and made available to other IoT apps. Thus, the SIoT network offers guidance services for reusing data from IoT applications across many IoT applications and customizing IoT solutions to meet the unique needs of individual users, hence boosting overall communication. SIoT technology entails the more efficient use of recent data to create favorable patient outcomes in healthcare and medicine. The enormous volume of data generated by SIoT-connected devices has allowed various developments and applications in the healthcare domain. SIoT leverages sensors and other connected devices in these domains to boost social solutions’ efficiency. Without question, sensors used for creating this kind of network model that can collect vast amounts of data are on the verge of becoming a pervasive part of our lives. If the processing and management are not carried out optimally in SIoT, there is a significant risk that the data will lose its efficacy. This chapter examines SIoT challenges and approaches in the healthcare and medical domain. SIoT approaches may assist users in detecting a patient's aberrant behaviour. These approaches are capable of detecting and forecasting patients’ health states. The SIoT's relational models, such as community sharing, equality matching, and equality matching, also provide IoT services to users. The sensing layer's functionalities are compared to those of the network layer and application when assessing SIoT services. The proposed hierarchical network model uses gateways, switches, and IoT devices to establish social relationships. CISCO packet tracer is used to construct and operate this mainly built social network for healthcare. This specially designed social network for the healthcare domain can easily be implemented and controlled by any hospital management.

SummaryIn recent years, applying Internet of Things (IoT) applications has significantly increased to facilitate and improve quality of human life activities in various fields such as healthcare, education, industry, economics, etc. The energy aware cloud‐edge computing paradigm has developed as a hybrid computing solution to provide IoT applications using available cloud service providers and fog nodes for the smart devices and mobile applications. Since the IoT applications are developed in the form of several IoT services with various quality of service (QoS) metrics which can deploy on the cloud‐edge providers with different resource capabilities, finding an efficient placement solution as one of challenging topics to be measured for IoT applications. The service placement issue arranges IoT applications on the cloud‐edge providers with various capabilities of atomic services though sufficient different QoS factors to support service level agreement (SLA) contracts. This paper presents a technical analysis on the cloud‐edge service placement approaches in IoT systems. The key point of this technical analysis is to identify substantial studies in the service placement approaches which need additional consideration to progress more efficient and effective placement strategies in IoT environments. In addition, a side‐by‐side taxonomy is proposed to categorize the relevant studies on cloud‐edge service placement approaches and algorithms. A statistical and technical analysis of reviewed existing approaches is provided, and evaluation factors and attributes are discussed. Finally, open issues and forthcoming challenges of service placement approaches are presented.

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.

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.

With the advancement of computing technology, we are witnessing the dawn of a new era of the Internet of Things (IoT) paradigm in which objects equipped with sensors, actuators and processing capabilities communicate with each other to serve a given goal. The IoT’s intrinsic nature, which uses heterogeneous devices, resources and different communication protocols, complicates IoT applications’ design, development, and validation. Reducing the complexity of building IoT applications is one of the current challenges in this area.To address this challenge, we focus on a model-driven approach to support IoT systems’ management and the development of IoT applications. In particular, we propose the FloWare approach and its toolchain, which combine Software Product Line and Flow-Based Programming paradigms to manage the complexity in the various stages of the IoT application development process. An automatic transformation procedure generates the final IoT application, an executable Node-RED flow, starting from a configuration of the designed Feature Models.KeywordsIoTModel-drivenFeature modelFlow-based programmingNode-RED

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.

Internet of things examples extend from smart connected homes to wearables to healthcare. It is not wrong to suggest that IoT is now becoming part of every aspect of our lives. Not only internet of things applications are enhancing the comforts of our lives but also it giving us more control by simplifying routine work life and personal tasks. With the recent hype about the future prospects of IoT has forced companies to take the initiative of coming up with basic building blocks of internet of things i.e. hardware, software and support to enable developers deploy applications that can connect anything within scope of internet of things. We know that the potential of IoT markets is huge but there are some domains that will mature much faster than the rest. Here we list the application areas for the internet of things with examples that have the potential of exponential growth. Definition of connected home is different for different people. In simple words a smart home is the one in which the devices have the capability to communicate with each other as well as to their intangible environment. A smart home gives owner the capability to customize and control home environment for increased security and efficient energy management. There are hundreds of IoT technologies available for monitoring and building smart homes. Consumer product manufacturers like Belkin, Philips, Amazon and Haier have already established themselves as prominent companies in this market. Here are the examples of internet of things for building your own smart homes. In this keynote, I will talk the concepts behind Internet of Things services and products from Korea. You will have chance to understand about sensors, actuators, processors and communication protocols to understand and develop skills that will help you in deploying real life IoT applications and Big issues in Korea. I also cover the topics as IOT Applications with Examples in Korea, The fundamental Components of The IOT and Future Direction of IOT.

The fog computing paradigm is a promising concept to overcome the exponential increase in data volume in Internet of Things (IoT) applications. This paradigm can support delay-sensitive IoT applications by extending cloud services to the network edge. However, fog computing faces challenges such as resource allocation for applications at the network edge due to limited resources as well as its heterogeneous and distributed nature. This is in line with the goals of microservice architecture and develops the placement of microservice-based IoT applications. The IoT service placement problem (SPP) on fog nodes is known as non-deterministic polynomial-time (NP)-hard. In this study, we introduce a meta-heuristic approach named SPP-differential evolution algorithm (DEA) to handle SPP, which originates from the DEA with a shared parallel architecture. The proposed method takes advantage of the scalable and deployable nature of microservices to minimize the resource utilization and delay as much as possible. SPP-DEA is developed based on monitoring, analysis, decision-making, and execution with knowledge bas (MADE-k) autonomous planning model with the aim of compromise between service cost, response time, resource utilization, and throughput. In order to address the computational complexity of the problem, we consider the resource consumption distribution and service deployment priority in the placement process. In order to evaluate the quality of placement in SPP-DEA, extensive experiments have been performed on a synthetic fog environment. The simulation results show that compared to the state-of-the-art approaches, SPP-DEA reduces the service cost and waiting time by 16% and 11%, respectively.

Purpose – The purpose of this paper is to study lightweight security scheme for Internet of Things (IoT) applications using Constrained Application Protocol (CoAP). Resource-constrained characteristics of IoT systems have ushered in compelling requirements for lightweight application protocol and security suites. CoAP has already been established as the candidate protocol for IoT systems. However, low overhead security scheme for CoAP is still an open problem. Existing security solutions like Datagram Transport Layer Security (DTLS) is not suitable, particularly due to its expensive handshaking, public key infrastructure (PKI)-based authentication and lengthy ciphersuite agreement process. Design/methodology/approach – This paper proposes a lightweight security scheme in CoAP using Advanced Encryption Standard (AES) 128 symmetric key algorithm. The paper presents an object security (payload embedded)-based robust authentication mechanism with integrated key management. The paper introduces few unique modifications to CoAP header to optimize security operation and minimize communication cost. Findings – It is resilient to number of security attacks like replay attack, meet-in-the-middle attack and secure under chosen plaintext attack. This scheme is generic in nature, applicable for gamut of IoT applications. The paper proves efficacy of our proposed scheme for vehicle tracking application in emulated laboratory setup. Specifically, it compares with DTLS-enabled CoAP to establish the lightweight feature of our proposed solution. Research limitations/implications – This paper mainly focuses on implementing in-vehicle tracking systems as an IoT application and used CoAP as the application protocol. Practical implications – Such a lightweight security scheme would provide immense benefit in IoT systems so that resource constraint-sensing devices and nodes can be made secure. This would impact IoT eco systems to a large extent. Originality/value – Such kind of security suite that provides both robustness and lightweight feature is hitherto not known to the authors, particularly in CoAP for IoT applications.

Cost-effective, low-power and wireless connectivity are among the key considerations for interconnecting the end-nodes or end-devices in the Internet of Things (IoT) applications. While wireless technologies such as WiFi, Bluetooth, Zigbee have been popular choices for last-mile connectivity, they however significantly restrict the distance between the communicating entities. While the use of additional network gear like repeaters or higher signal transmission power would increase the range of these wireless communication interfaces, the consequent increase in the cost has been a critical reason for not readily employing them in WAN based IoT applications such as Smart Cities. The emergence of the LoRa (Long Range) standard and the Low Power Wide Area Network (LPWAN) technology, in recent times, have however widened the scope and also broadened the deployment scenarios of the IoT end-nodes including the viability of the battery-powered and non-stationary ones. Yet another significance of these new long-distance-low-power interconnect standards is the empowerment for broader and independent Machine to Infrastructure (M2I) and Machine to Machine (M2M) communication for the end-nodes. This paper discusses details of the work that was carried out to explore the suitability of LoRa and LoRaWAN to address the short as well as the medium-range connectivity requirements of the IoT applications while also ensuring the flexibility and low-cost benefits with the help of results obtained from the representative experimental setups. The overall study and assessment were performed in steps, each with specific objectives. The first step was aimed at evaluating the performance of LoRa for communication between stationary as well as moving nodes. The next step was directed towards the validation of node-to-gateway and node-to-node communication, and also, with simultaneous use of different channels within LoRaWANs that were configured in star and mesh topologies. The subsequent step was devoted to assessing the viability of LoRa in broader IoT applications such as Smart Cities and Smart Irrigation, with the help of an illustrative setup comprising of nodes with sensors and actuators and, a gateway which was connected to an open-source cloud infrastructure to epitomize aspects of storage and analysis of data of a comprehensive IoT deployment.

The rise of successful cutting-edge Internet of Things (IoT) applications for urban development has inspired the industry and research community. Although the industry verticals such as automotive, robotics, e-health, and entertainment applications create new business opportunities for the service providers, they pose challenges in terms of deployment cost, reliability, and latency requirements. For example, self-driving vehicles require ultralow latency and reliable data processing to make split-second decisions. Unfortunately, cloud-based solutions for such IoT applications are not suitable due to the end-to-end latency and connection reliability. To meet these challenging requirements, edge computing paradigm has emerged as a solution where computational resources are brought to the proximity of the end users. Now, advanced data analytics, machine learning, and cognitive techniques can also be deployed at the edge of the network. Together, edge computing, data analytics, and machine learning empower service providers with true and intelligently automated infrastructure for IoT applications. In this chapter, we investigate the relevant use cases of edge-enabled IoT applications for smart urban development. To this end, we also provide a comprehensive study of the recent trends and the state of the art in accommodating all these emerging technologies in the acceleration of smart urban development.

The design and development process for internet of things (IoT) applications is more complicated than that for desktop, mobile, or web applications. First, IoT applications require both software and hardware to work together across many different types of nodes with different capabilities under different conditions. Second, IoT application development involves different types of software engineers such as desktop, web, embedded, and mobile to work together. Furthermore, non-software engineering personnel such as business analysts are also involved in the design process. In addition to the complexity of having multiple software engineering specialists cooperating to merge different hardware and software components together, the development process requires different software and hardware stacks to be integrated together (e.g., different stacks from different companies such as Microsoft Azure and IBM Bluemix). Due to the above complexities, non-functional requirements (such as security and privacy, which are highly important in the context of the IoT) tend to be ignored or treated as though they are less important in the IoT application development process. This article reviews techniques, methods, and tools to support security and privacy requirements in existing non-IoT application designs, enabling their use and integration into IoT applications. This article primarily focuses on design notations, models, and languages that facilitate capturing non-functional requirements (i.e., security and privacy). Our goal is not only to analyse, compare, and consolidate the empirical research but also to appreciate their findings and discuss their applicability for the IoT.

The proliferation of Internet of Things (IoT) devices has opened new roads for collaborative distributed applications, particularly in smart city environments, where a variety of resources, including sensing, actuation, computation, and storage, are essential for providing effective location-based services. This paper specifically focuses on the sharing of heterogeneous resources among IoT applications in smart cities. By leveraging game-theoretic principles, this study addresses resource allocation through a combinatorial double auction. The solution is rooted in the concept of Social IoT (SIoT), where Internet-connected objects create dynamic social networks based on rules set by their owners. Social relationships, such as ownership and co-location, are leveraged to form groups offering enhanced reliability resource bundles. The proposed solution offers several key economic properties, including incentive compatibility, individual rationality, and a balanced budget, while maintaining low computational complexity. Simulation results demonstrate that the proposed combinatorial double auction mechanism achieves over 70% successful resource allocation for up to 1000 requests, maintains computational efficiency with execution times under 30 s, and ensures economic properties such as incentive compatibility and individual rationality, making it a scalable and practical solution for large-scale smart city IoT applications.

Age of Information minimization in UAV-aided data collection for WSN and IoT applications: A systematic review