The Internet of Things (IoT) is one of the most promising technologies for the near future. Healthcare and well-being will receive great benefits with the evolution of this technology. This paper presents a review of techniques based on IoT for healthcare and ambient-assisted living, defined as the Internet of Health Things (IoHT), based on the most recent publications and products available in the market from industry for this segment. Also, this paper identifies the technological advances made so far, analyzing the challenges to be overcome and provides an approach of future trends. Through selected works, it is possible to notice that further studies are important to improve current techniques and that novel concept and technologies of IoHT are needed to overcome the identified challenges. The presented results aim to serve as a source of information for healthcare providers, researchers, technology specialists, and the general population to improve the IoHT.

Enabling Technologies for the Internet of Health Things

The Internet of Things (IoT) is rapidly becoming an integral part of our life and also multiple industries. We expect to see the number of IoT connected devices explosively grows and will reach hundreds of billions during the next few years. To support such a massive connectivity, various wireless technologies are investigated. In this survey, we provide a broad view of the existing wireless IoT connectivity technologies and discuss several new emerging technologies and solutions that can be effectively used to enable massive connectivity for IoT. In particular, we categorize the existing wireless IoT connectivity technologies based on coverage range and review diverse types of connectivity technologies with different specifications. We also point out key technical challenges of the existing connectivity technologies for enabling massive IoT connectivity. To address the challenges, we further review and discuss some examples of promising technologies such as compressive sensing (CS) random access, non-orthogonal multiple access (NOMA), and massive multiple input multiple output (mMIMO) based random access that could be employed in future standards for supporting IoT connectivity. Finally, a classification of IoT applications is considered in terms of various service requirements. For each group of classified applications, we outline its suitable IoT connectivity options.

IoT Connectivity Technologies and Applications: A Survey

The performance of wireless sensor networks (WSN) is affected by the lossy communication medium, application diversity, dense deployment, limited processing power and storage capacity, frequent topology change. All these limitations provide significant and unique design challenges to data transport control in wireless sensor networks. An effective transport protocol should consider reliable message delivery, energy-efficiency, quality of service and congestion control. The latter is vital for achieving a high throughput and a long network lifetime. Despite the huge number of protocols proposed in the literature, congestion control in WSN remains challenging. A review and taxonomy of the state-of-the-art protocols from the literature up to 2013 is provided in this paper. First, depending on the control policy, the protocols are divided into resource control vs. traffic control. Traffic control protocols are either reactive or preventive (avoiding). Reactive solutions are classified following the reaction scale, while preventive solutions are split up into buffer limitation vs. interference control. Resource control protocols are classified according to the type of resource to be tuned.

Congestion Control Protocols in Wireless Sensor Networks: A Survey

Both 5G cellular and IoT technologies are expected to see widespread deployment in the next few years. At the practical level, 5G will see initial deployments in urban areas. This is perhaps fortuitous from an IoT perspective, since many “mainstream” applications of IoT will support Smart Cities, Smart Campuses and Smart Buildings. Bandwidth demand for a number of Smart City applications is the main driver for enhanced mobile broadband (eMBB)-based 5G services in general, and new-generation 5G IoT applications, in particular. In turn, the use of the millimeter wave spectrum is required to enable 5G cellular technologies to support high data rates. Millimeter wave solutions, however, impose a requirement for small cells. Generally, an implementer tries to use one or a small handful of IoT technologies; preferably, and for managerial simplicity, the implementer would want to use a cellular/5G IoT technology for all nodes, whether indoors or outdoors, instead of a heterogenous mix of various IoT technologies that have evolved over the years. This overview paper discusses a number of practical issues related to 5G-based IoT applications, particularly in Smart City environments, including the need for small cells, the transmission issues at millimeter wave frequencies, building penetration issues, the need for Distributed Antenna Systems, and the near term introduction of pre-5G IoT technologies such as NB-IoT and LTE-M, these being possible proxies for the commercial deployment and acceptance of 5G IoT.

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Practical Aspects for the Integration of 5G Networks and IoT Applications in Smart Cities Environments

With the fast development and expansion of the Internet of Things (IoT), billions of smart devices are being continuously connected, and smart homes, as a typical IoT application, are providing people with various convenient applications, but face security and privacy issues. The idea of Blockchain (BC) theory has brought about a potential solution to the IoT security problem. The emergence of blockchain technology has brought about a change of decentralized management, providing an effective solution for the protection of network security and privacy. On the other hand, the smart devices in IoT are always lightweight and have less energy and memory. This makes the application of blockchain difficult. Against this background, this paper proposes a blockchain model based on hypergraphs. The aims of this model are to reduce the storage consumption and to solve the additional security issues. In the model, we use the hyperedge as the organization of storage nodes and convert the entire networked data storage into part network storage. We discuss the design of the model and security strategy in detail, introducing some use cases in a smart home network and evaluating the storage performance of the model through simulation experiments and an evaluation of the network.

https://www.mdpi.com/1424-8220/18/9/2784/pdf

A Hypergraph-Based Blockchain Model and Application in Internet of Things-Enabled Smart Homes.

As population is burgeoning, there is an increase in the number of vehicles on the road and hence an upsurge in the problems associated with traffic management, especially the Public Transport. There is also an increase in the number of accidents and various other traffic related issues. Intelligent Transportation System (ITS) provides the solution to most of these problems by integrating existing technologies with the underlying infrastructure. With the advent of mobile technology and the ubiquitous cellular network, real time vehicle tracking for efficient transport management has become viable. The futile long wait for a bus to arrive can be avoided by Intelligent Public Transportation System. The omnipresence of Smart Phones and their ever increasing power at a very economical price makes them one of the most attractive options for developing IOT applications. Here, an approach based on the combination of technologies like GPS and Android is discussed which can assuage passengers who commute by the means of public transport. The user is furnished with explicit information about the current location of nearest buses approaching the bus-stop on a mobile application. Using readily available Android API's, technologies like 3G network and SMS based services in the existing mobile phones can reduce the cost and size of hardware required, as well as lead to a better output.

Integration of Smart Phone and IOT for development of smart public transportation system

Wireless sensor network (WSN) has emerged as a promising technology thanks to the recent advances in electronics, networking, and information technologies. The data which flows through the wireless sensor network has great impact on the link load. The handling this data against the congestion, its reliability, and loss recovery is very tough task. In this paper we propose the scheme to detect and overcome the congestion (EDCAM). The main feature of proposed algorithm is early detection of the congestion. Rather to take the corrective action, here we prevent to happening the congestion.

/pdf/edcam-early-detection-congestion-avoidance-mechanism-454tz7spvt.pdf

EDCAM: Early Detection Congestion Avoidance Mechanism

EDCAM: Early Detection Congestion Avoidance Mechanism for Wireless Sensor Network

Wireless sensor network (WSN) is a dynamic self — configured device which is used for the communicational purpose to monitor different scenarios. To the best of our knowledge, the main challenge faced in the field of wireless sensor network is computing, monitoring and the size of the sensor. In this paper we underscore the fact of analysis of the behavior of wireless sensor network using different factors and protocols. By analysis we can predict the behavior and analyze the superficiality.

Performance analysis of wireless sensor networks for QoS

We propose a system which will be able to recommend the user to choose appropriate outfits suits to their personality. The necessity of this system is to reduce the outfit selection and purchasing time; this will also help to create tailor made outfits as per the personality traits. The guidelines for selection of their respective outfits are based upon various bodily parameters that evolve with the learning of available labeled and unlabeled data. The system is based on two modules of processes; first one is to recognize the features for usage of outfits like traditional, western, functional, daytime or night etc, second is to calculate the body measurement parameters. The proposed system will have image capturing by using HAAR feature or input device for getting body parameters. We intend to classify and extract the best possible outfits from the system by using HIGEN MINER algorithm. The applications of outfit selection will be ranging from manual gender selection, image processing with body feature extractions, Value comparison with database by using different statistical techniques and data mining algorithms. After that it will recommend best outfits as per body parameters, inputs and availability

Shiv Sutar

Papers

Integration of Smart Phone and IOT for development of smart public transportation system

EDCAM: Early Detection Congestion Avoidance Mechanism

EDCAM: Early Detection Congestion Avoidance Mechanism for Wireless Sensor Network

Performance analysis of wireless sensor networks for QoS

Recommendation System for Outfit Selection (RSOS)