FloWare: An Approach for IoT Support and Application Development

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.

Internet of things (IoT) is creating new opportunities for developing innovative applications by leveraging on existing and new technologies. In recent years, a variety of consumer and industrial IoT applications have been developed and deployed. Despite much progress, developing IoT applications is still a complex, time‐consuming and challenging activity. This is because IoT systems involve a wide range of hardware and software components, depending on a variety of communication and distributed system technologies. Many IoT application frameworks of varying approaches have been developed to manage the complexities of developing IoT applications. However, there remains a paucity of surveys on these IoT application development frameworks. This study presents a comprehensive review and a comparative analysis of existing IoT application development frameworks and toolkits, illustrating their strengths and weaknesses. This study will assist in finding the most appropriate IoT application development paradigm for the desired IoT application. Finally, future research directions are highlighted to improve existing and future frameworks and toolkits for IoT applications.

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.

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.

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.

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.

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.

The emerging Internet of Things (IoT) revolution has introduced many useful applications that are utilized in our daily lives. Users can program these devices in order to develop their own IoT applications; however, the platforms and languages that are used during development are abounding, complicated, and time-consuming. The software solution provided in this thesis, PROVIZ+, is a secure sensor application development software suite that helps users create sophisticated and secure IoT applications with little software and hardware experience. Moreover, a simple and efficient domain-specific programming language, namely Panther language, was designed for IoT application development to unify existing programming languages. In addition to these contributions, PROVIZ+ supports a novel secure over-the-air programming framework, namely SOTA, using Bluetooth and WiFi as well as serial programming. In this thesis, we explain the features of PROVIZ+’s components, how these tools can help develop IoT applications, and SOTA. We also present the performance evaluations of PROVIZ+ and SOTA.

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.

Increasingly, the heterogeneity of devices and software that comprise the Internet of Things (IoT) is impeding innovation. IoT deployments amalgamate compute, storage, networking capabilities provisioned at multiple resource scales, from low-cost, resource constrained microcontrollers to resource rich public cloud servers. To support these different resource scales and capabilities, the operating systems (OSs) that manage them have also diverged significantly. Because the OS is the “API” for the hardware, this proliferation is causing a lack of portability across devices and systems, complicating development, deployment, management, and optimization of IoT applications. To address these impediments, we investigate a new, “clean slate” OS design and implementation that hides this heterogeneity via a new set of abstractions specifically for supporting microservices as a universal application programming model in IoT contexts. The operating system, called Ambience, supports IoT applications structured as microservices and facilitates their portability, isolation, and deployment time optimization. We discuss the design and implementation of Ambience, evaluate its performance, and demonstrate its portability using both microbenchmarks and end-to-end IoT deployments. Our results show that Ambience can scale down to 64MHz microcontrollers and up to modern x86_64 servers, while providing similar or better performance than comparable commodity operating systems on the same range of hardware platforms.

Low power wide area networks (LPWAN) are comprised of small devices having restricted processing resources and limited energy budget. These devices are connected with each other using communication protocols. Considering their available resources, these devices can be used in a number of different Internet of Things (IoT) applications. Another interesting paradigm is machine learning, which can also be integrated with LPWAN technology to embed intelligence into these IoT applications. These machine learning-based applications combine intelligence with LPWAN and prove to be a useful tool. One such IoT application is in the medical field, where they can be used to provide multiple services. In the scenario of the COVID-19 pandemic, the importance of LPWAN-based medical services has gained particular attention. This article describes various COVID-19-related healthcare services, using the the applications of machine learning and LPWAN in improving the medical domain during the current COVID-19 pandemic. We validate our idea with the help of a case study that describes a way to reduce the spread of any pandemic using LPWAN technology and machine learning. The case study compares k-Nearest Neighbors (KNN) and trust-based algorithms for mitigating the flow of virus spread. The simulation results show the effectiveness of KNN for curtailing the COVID-19 spread.

Connected devices are known as Internet of Things (IoT) gadgets because they are able to communicate with other IoT gadgets and systems over the Internet or other communication networks. An IoT security system protects Internet devices and networks they link to against attacks and breaches by guarding, detecting, monitoring, and fixing vulnerabilities from various devices that might pose security concerns to your company. The discipline of IoT security is what makes your IoT systems secure. Security solutions for IoT guard against attacks and breaches, detect and monitor risks, and assist in patching any holes that may have been introduced. The availability, integrity, and confidentiality of your IoT solution are all ensured by IoT security. Mobile devices and IoT are making it possible for educational institutions to increase campus security, monitor critical resources, and provide students with easier access to information. Teachers may also employ this technology to build “smart lesson plans,” as opposed to the standard boring plans of the past. Using IoT to secure the education sector from cyberattacks is one of the recommended methods in this paper. A comparison study of existing research to suggested research on the basis of security, dependability, and performance characteristics is being carried out.KeywordsIoTOnline education systemSecurityCompression