Purpose Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications. Design/methodology/approach A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced. Findings Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives. Originality/value This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.

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Due to the ever-increasing number and diversity of data sources, and the continuous flow of data that are inevitably redundant and unused to the cloud, the Internet of Things (IoT) brings several problems including network bandwidth, the consumption of network energy, cloud storage, especially for paid volume, and I/O throughput as well as handling huge amount of stored data in the cloud. These call for data pre-processing at the network edge before data transmission over the network takes place. Data reduction is a method for mitigating such problems. Most state-of-the-art data reduction approaches employ a single tier, such as gateways, or two tiers, such gateways and the cloud data center or sensor nodes and base station. In this paper, an approach for IoT data reduction is proposed using in-networking data filtering and fusion. The proposed approach consists of two layers that can be adapted at either a single tier or two tiers. The first layer of the proposed approach is the data filtering layer that is based on two techniques, namely data change detection and the deviation of real observations from their estimated values. The second layer is the data fusion layer. It is based on a minimum square error criterion and fuses the data of the same time domain for specific sensors deployed in a specific area. The proposed approach was implemented using Python and the evaluation of the approach was conducted based on a real-world dataset. The obtained results demonstrate that the proposed approach is efficient in terms of data reduction in comparison with Least Mean Squares filter and Papageorgiou’s (CLONE) method.

The Internet of Things (IoT) is emerging from its infancy and establishing itself as a component of the future Internet. However, the ability to manage a huge number of IoT devices is one of the IoT technical challenges. To implement access control, traditional schemes typically rely on a trusted central organization. Traditional centralized access control systems of the IoT lead to the shortcomings of a single point of failure, low overall system efficiency, and ethical and privacy issues. To overcome such challenges, an attribute-based access control model using Hyperledger Fabric blockchain (ABAC-HLFBC) is proposed in this paper. By adopting ABAC, it is no longer to create access control lists (ACLs) or assign roles to all system users. Instead, ABAC grants access based on the attributes presented by the target. No one is permitted access unless he/she possesses sufficient attributes that correspond to the access policy. The Hyperledger Fabric Raft consensus mechanism has been used to verify the transaction on the proposed model because it has a demanding feature for faster and less complicated consensus in comparison to the Kafka ordering service. To evaluate the proposed model, it has been tested against the most recent previous work, called fabric-iot model. The proposed model has been tested and evaluated in two parts. The first part tests the cost time using a client test program written in Golang. The second part tests the latency and throughput using the Hyperledger Caliper benchmark tool. Results show that the proposed model efficiently outperforms the previous work in terms of the performance metrics mentioned above.