The current prominence and future promises of the Internet of Things (IoT), Internet of Everything (IoE) and Internet of Nano Things (IoNT) are extensively reviewed and a summary survey report is presented. The analysis clearly distinguishes between IoT and IoE which are wrongly considered to be the same by many people. Upon examining the current advancement in the fields of IoT, IoE and IoNT, the paper presents scenarios for the possible future expansion of their applications.

Blockchain (BC), the technology behind the Bitcoin crypto-currency system, is considered to be both alluring and critical for ensuring enhanced security and (in some implementations, non-traceable) privacy for diverse applications in many other domains - including in the Internet of Things (IoT) eco-system. Intensive research is currently being conducted in both academia and industry applying the Blockchain technology in multifarious applications. Proof-of-Work (PoW), a cryptographic puzzle, plays a vital rôle in ensuring BC security by maintaining a digital ledger of transactions, which is considered to be incorruptible. Furthermore, BC uses a changeable Public Key (PK) to record the users’ identity, which provides an extra layer of privacy. Not only in cryptocurrency has the successful adoption of BC been implemented but also in multifaceted non-monetary systems such as in: distributed storage systems, proof-of-location, healthcare, decentralized voting and so forth. Recent research articles and projects/applications were surveyed to assess the implementation of BC for enhanced security, to identify associated challenges and to propose solutions for BC enabled enhanced security systems.

The current statuses and future promises of the Internet of Things (IoT), Internet of Everything (IoE) and Internet of Nano-Things (IoNT) are extensively reviewed and a summarized survey is presented. The analysis clearly distinguishes between IoT and IoE, which are wrongly considered to be the same by many commentators. After evaluating the current trends of advancement in the fields of IoT, IoE and IoNT, this paper identifies the 21 most significant current and future challenges as well as scenarios for the possible future expansion of their applications. Despite possible negative aspects of these developments, there are grounds for general optimism about the coming technologies. Certainly, many tedious tasks can be taken over by IoT devices. However, the dangers of criminal and other nefarious activities, plus those of hardware and software errors, pose major challenges that are a priority for further research. Major specific priority issues for research are identified.

Deep knowledge of how radio waves behave in a practical wireless channel is required for effective planning and deployment of radio access networks in urban environments. Empirical propagation models are popular for their simplicity, but they are prone to introduce high prediction errors. Different heuristic methods and geospatial approaches have been developed to further reduce path loss prediction error. However, the efficacy of these new techniques in built-up areas should be experimentally verified. In this paper, the efficiencies of empirical, heuristic, and geospatial methods for signal fading predictions in the very high frequency (VHF) and ultra-high frequency (UHF) bands in typical urban environments are evaluated and analyzed. Electromagnetic field strength measurements are performed at different test locations within four selected cities in Nigeria. The data collected are used to develop path loss models based on artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and Kriging techniques. The prediction results of the developed models are compared with those of selected empirical models and field measured data. Apart from Egli and ECC-33, the root mean squared error (RMSE) produced by all other models under investigation are considered acceptable. Specifically, the ANN and ANFIS models yielded the lowest prediction errors. However, the empirical models have the lowest standard deviation errors across all the bands. The findings of this study will help radio network engineers to achieve efficient radio coverage estimation; determine the optimal base station location; make a proper frequency allocation; select the most suitable antenna; and perform interference feasibility studies.INDEX TERMS ANFIS, artificial neural networks, backpropagation, path loss, Kriging, radio propagation. I. INTRODUCTIONA study of the characteristics of radio waves in different propagation environments is needed for an effective network planning, and for the deployment of wireless communication systems [1], [2]. The magnitude and direction of electromagnetic waves in a practical wireless channel is usuallyThe associate editor coordinating the review of this manuscript and approving it for publication was Mauro Tucci.random and highly unpredictable [3]. Meanwhile, a good understanding of this phenomenon is needed to guarantee good Quality of Service (QoS) and high data transmission rate in radio access networks.The efficiency of a wireless communication system depends on the physical constituents of the propagation environment. The presence of buildings, mountains, bill boards, foliage, vehicles and other physical objects in a practical propagation environment usually obstructs the direct

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Blockchain (BC), the technology behind the Bitcoin crypto-currency system -is starting to be adopted for ensuring enhanced security and privacy in the Internet of Things (IoT) ecosystem. Fervent research is currently being focused in both academia and industry in this domain. Proof-of-Work (PoW), a cryptographic puzzle, plays a vital rôle in ensuring BC security by maintaining a digital ledger of transactions, which are considered to be incorruptible. Furthermore, BC uses a changeable Public Key (PK) to record the identity of users -thus providing an extra layer of privacy. Not only in crypto-currency has the successful adoption of the BC been implemented, but also in multifaceted nonmonetary systems, such as in: distributed storage systems, proof-of-location and healthcare. Recent research articles and projects/applications were surveyed to assess the implementation of the BC for IoT Security and identify associated challenges and propose solutions for BC enabled enhanced security for the IoT ecosystem.

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This paper describes the novel application of using linear fractal interpolation functions (FIFs) to model video signals represented as single-valued discrete-time sequences to compress video images. The problem is data compression of full-motion broadband television signals. The viability of using FIFs to model video signals is shown by modelling test static image frames. Compression ratios, SNRs and compression-decompression times are reported. Extension of this work to compress motion video is described. Finally the images are analysed by calculating and plotting the fractal dimensions of each line in the frame against the line for that image.