Blockchain for 5G-enabled IoT for industrial automation: A systematic review, solutions, and challenges

Considering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field, but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complicated and transdisciplinary. While deploying a smart parking system, cities, as well as urban engineers, need to spend a very long time to survey and inspect all the possibilities. Moreover, many varied works involve multiple disciplines, which are closely linked and inseparable. To give a clear overview, we introduce a smart parking ecosystem and propose a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses. We go through the literature over the period of 2000–2016 on parking solutions as they were applied to smart parking development and evolution, and propose three macro-themes: information collection, system deployment, and service dissemination. In each macro-theme, we explain and synthesize the main methodologies used in the existing works and summarize their common goals and visions to solve current parking difficulties. Finally, we give our engineering insights and show some challenges and open issues. Our survey gives an exhaustive study and a prospect in a multidisciplinary approach. Besides, the main findings of the current state-of-the-art throw out recommendations for future research on smart cities and the Internet architecture.

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A Survey of Smart Parking Solutions

Internet of Things (IoT) has recently received a great attention due to its potential and capacity to be integrated into any complex system. As a result of rapid development of sensing technologies such as radio-frequency identification, sensors and the convergence of information technologies such as wireless communication and Internet, IoT is emerging as an important technology for monitoring systems. This paper reviews and introduces a framework for structural health monitoring (SHM) using IoT technologies on intelligent and reliable monitoring. Specifically, technologies involved in IoT and SHM system implementation as well as data routing strategy in IoT environment are presented. As the amount of data generated by sensing devices are voluminous and faster than ever, big data solutions are introduced to deal with the complex and large amount of data collected from sensors installed on structures.

Structural Health Monitoring Framework Based on Internet of Things: A Survey

Humans with good health condition is some more difficult in today’s life, because of changing food habit and environment. So we need awareness about the health condition to the survival. The health-support systems faces significant challenges like lack of adequate medical information, preventable errors, data threat, misdiagnosis, and delayed transmission. To overcome this problem, here we proposed wearable sensor which is connected to Internet of things (IoT) based big data i.e. data mining analysis in healthcare. Moreover, here we design Generalize approximate Reasoning base Intelligence Control (GARIC) with regression rules to gather the information about the patient from the IoT. Finally, Train the data to the Artificial intelligence (AI) with the use of deep learning mechanism Boltzmann belief network. Subsequently Regularization _ Genome wide association study (GWAS) is used to predict the diseases. Thus, if the people has affected by some diseases they will get warning by SMS, emails. Etc., after that they got some treatments and advisory from the doctors.

IOT based wearable sensor for diseases prediction and symptom analysis in healthcare sector

Internet of Things (IoT) is an emerging paradigm which aims to inter-connect all smart physical devices, so that the devices together can provide smart services to the users. Some of the IoT applications include smart homes, smart cities, smart grids, smart retail, etc. Since IoT systems are built up with heterogeneous hardware and networking technologies, connecting them to the software/application level to extract information from large amounts of data is a complex task. In this paper, we have surveyed various architecture and protocols used in IoT systems and proposed suitable taxonomies for classifying them. We have also discussed the technical challenges, such as security and privacy, interoperability, scalability, and energy efficiency. We have provided an in-depth coverage of recent research works for every mentioned challenge. The objective of this survey is to help future researchers to identify IoT specific challenges and to adopt appropriate technology depending on the application requirements.

A Survey on Architecture, Protocols and Challenges in IoT

This paper introduces a novel algorithm that increases the efficiency of the current cloud-based smart-parking system and develops a network architecture based on the Internet-of-Things technology. This paper proposed a system that helps users automatically find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance and the total number of free places in each car park. This cost will be used to offer a solution of finding an available parking space upon a request by the user and a solution of suggesting a new car park if the current car park is full. The simulation results show that the algorithm helps improve the probability of successful parking and minimizes the user waiting time. We also successfully implemented the proposed system in the real world.

A Cloud-Based Smart-Parking System Based on Internet-of-Things Technologies

In this article, we proposed an infrastructureless cooperative lane positioning (ICLP) framework using vehicle-to-vehicle (V2V) communications. The ICLP framework applies vehicular sensor networks (VSNs) to localize lane positions of vehicles on roads. ICLP allows the vehicles equipped with image sensors to detect the current located lane without utilizing global positioning system (GPS) locations and roadside infrastructures. Through image sensors, ICLP can keep recognizing the lane position for a vehicle. In addition, ICLP can request lane position information from other vehicles in the same lane as necessary, based on V2V communications. ICLP makes innovative applications of intelligent transportation systems relying on accurate positioning possible, such as lane-level cooperative collision avoidance, dynamic traffic control, and intelligent personal navigation. An Android-based prototype is implemented to verify the feasibility and superiority of our framework. The experimental results show that ICLP can achieve high positioning success ratios and provide accurate lane positions for vehicles.

Ming-Fong Tsai

Papers

A Cloud-Based Smart-Parking System Based on Internet-of-Things Technologies

Finding Lane Positions of Vehicles: Infrastructure-Less Cooperative Lane Positioning Based on Vehicular Sensor Networks