The emergence of the internet of things (IoT) has drastically influenced and shaped the world of technology in the contexts of connectivity, interconnectivity, and interoperability with smart connected sensors, objects, devices, data, and applications. In fact, IoT has brought notable impacts on the global economy and human experience that span from industry to industry in a variety of application domains, including healthcare. With IoT, it is expected to facilitate a seamless interaction and communication of objects (devices) with humans in the environment. Therefore, it is imperative to embrace the potentials and benefits of IoT technology in healthcare delivery to ensure saving lives and to improve the quality of life using smart connected devices. In this paper, we focus on the IoT based healthcare system for cancer care services and business analytics/cloud services and also propose the adoption and implementation of IoT/WSN technology to augment the existing treatment options to deliver healthcare solution. Here, the business analytics/cloud services constitute the enablers for actionable insights, decision making, data transmission and reporting for enhancing cancer treatments. Furthermore, we propose a variety of frameworks and architectures to illustrate and support the functional IoT-based solution that is being considered or utilized in our proposed smart healthcare solution for cancer care services. Finally, it will be important to understand and discuss some security issues and operational challenges that have characterized the IoT-enabled healthcare system.
相似文献Use of internet of things (IoT) in different fields including smart cities, health care, manufacturing, and surveillance is growing rapidly, which results in massive amount of data generated by IoT devices. Real-time processing of large-scale data streams is one of the main challenges of IoT systems. Analyzing IoT data can help in providing better services, predicting trends and timely decision making for industries. The systematic structure of IoT data follows the pattern of big data. In this paper, a novel approach is proposed in which big data tools are used to perform real-time stream processing and analysis on IoT data. We have also applied Spark’s built-in support of the machine learning library in order to make real-time predictions. The efficiency of the proposed system is evaluated by conducting experiments and reporting results on the case scenario of IoT based weather station.
相似文献Development of Internet of Things (IoT) enables smart city advancement throughout the world. Increasing number of vehicles has brought focus on road safety precautions and in-vehicle communication. This is the right time to focus on the development of new applications and services for vehicular environments. The Vehicular Ad-hoc Networks (VANETs) are an interesting range of Mobile Ad-hoc Networks (MANETs) where the Vehicle to Vehicle (V2V) and vehicle roadways transmission is possible. The V2V scheme is fresh by combining Wireless Fidelity (Wi-Fi), Bluetooth and other all sorts of communication standards. An immense number of nodes working with these networks and due to their immense displacements, the analysis is prevailing regarding the possibility of routing standards. The estimation of conventional routing standards for MANETs illustrates that their behaviors are minimal in VANETs. The intention is to make use of mediators for routing with an effort to address the before described issues. The mediators are accountable for gathering data related to routing and identifying the optimal paths for forwarding information packets. The routing scheme is based on group routing standards and data cluster framework for locating the best possible routes. In this paper, we analyze smart cities vehicle communication development by implementing IoT. We also discuss the ways to minimize the limitations connected to IoT deployment and implementation in smart city environment using multi mediator scheme.
相似文献Internet of Things (IoT) refers to uniquely identifiable entities. Its vision is the world of connected objects. Due to its connected nature the data produced by IoT is being used for different purposes. Since IoT generates huge amount of data, we need some scalable storage to store and compute the data sensed from the sensors. To overcome this issue, we need the integration of cloud and IoT, so that the data might be stored and computed in a scalable environment. Harmonization of IoT in Cloud might be a novel solution in this regard. IoT devices will interact with each other using Constrained Application Protocol (CoAP). In this paper, we have implemented harmonizing IoT in Cloud. We have used CoAP to get things connected to each other through the Internet. For the implementation we have used two sensors, fire detector and the sensor attached with the door which is responsible for opening it. Thus our implementation will be storing and retrieving the sensed data from the cloud. We have also compared our implementation with different parameters. The comparison shows that our implementation significantly improves the performance compared to the existing system.
相似文献Energy is vital parameter for communication in Internet of Things (IoT) applications via Wireless Sensor Networks (WSN). Genetic algorithms with dynamic clustering approach are supposed to be very effective technique in conserving energy during the process of network planning and designing for IoT. Dynamic clustering recognizes the cluster head (CH) with higher energy for the data transmission in the network. In this paper, various applications, like smart transportation, smart grid, and smart cities, are discussed to establish that implementation of dynamic clustering computing-based IoT can support real-world applications in an efficient way. In the proposed approach, the dynamic clustering-based methodology and frame relay nodes (RN) are improved to elect the most preferred sensor node (SN) amidst the nodes in cluster. For this purpose, a Genetic Analysis approach is used. The simulations demonstrate that the proposed technique overcomes the dynamic clustering relay node (DCRN) clustering algorithm in terms of slot utilization, throughput and standard deviation in data transmission.
相似文献Nowadays, next-generation networks such as the Internet of Things (IoT) and 6G are played a vital role in providing an intelligent environment. The development of technologies helps to create smart city applications like the healthcare system, smart industry, and smart water plan, etc. Any user accesses the developed applications; at the time, security, privacy, and confidentiality arechallenging to manage. So, this paper introduces the blockchain-defined networks with a grey wolf optimized modular neural network approach for managing the smart environment security. During this process, construction, translation, and application layers are created, in which user authenticated based blocks are designed to handle the security and privacy property. Then the optimized neural network is applied to maintain the latency and computational resource utilization in IoT enabled smart applications. Then the efficiency of the system is evaluated using simulation results, in which system ensures low latency, high security (99.12%) compared to the multi-layer perceptron, and deep learning networks.
相似文献The Internet of Things (IoT) is a network of globally connected physical objects, which are associated with each other via Internet. The IoT foresees the interconnection of few trillions of intelligent objects around us, uniquely and addressable every day, these objects have the ability to accumulate process and communicate data about themselves and their surrounding environment. The best examples of IoT systems are health care, building smart city with advance construction management system, public and defense surveillance and data acquisition. Recent advancement in the technology has developed smart and intelligent sensor nodes and RFIDs lead to a large number of wireless networks with smart and intelligent devices (object, or things) connected to the Internet continuously transmit the data. So to provide security and privacy to this data in IoT is a very challenging task, which is to be concerned at highest priority for several current and future applications of IoT. Devices such as smart phone, WSNs and RFIDs etc., are the major components of IoT network which are basically resource constrained devices. Design and development of security and privacy management schemes for these devices is guided by factors like good performance, low power consumption, robustness to attacks, tampering of the data and end to end security. Security schemes in IoT provide unauthorized access to information or other objects by protecting against alterations or destruction. Privacy schemes maintain the right to control about the collected information for its usage and purpose. In this paper, we have surveyed major challenges such as Confidentiality, Integrity, Authentication, and Availability for IoT in a brief manner.
相似文献Nowadays, providing Internet of Things (IoT) environments with service level guarantee is a challenging task. Moreover, IoT services should be autonomous in order to minimize human intervention and thus to reduce the operational management cost of the corresponding big scale infrastructure. We describe in this paper a service level-based IoT architecture enabling the establishment of an IoT Service Level Agreement (iSLA) between an IoT Service Provider (IoT-SP) and an IoT Client (IoT-C). The proposed iSLA specifies the requirements of an IoT service, used in a specific application domain (e-health, smart cities, etc.), in terms of different measurable Quality of Service (QoS) parameters. In order to achieve this agreement, several QoS mechanisms are to be implemented within each layer of the IoT architecture. In this context, we propose an adaptation of the IEEE 802.15.4 slotted CSMA/CA mechanism to provide different IoT services with QoS guarantee. Our proposal called QBAIoT (QoS-based Access for IoT) creates different Contention Access Periods (CAP) according to different traffic types of the IoT environment. These CAPs are QoS-based and enable traffic differentiation. Thus, a QoS CAP is configured with several slots during which only IoT objects belonging to the same QoS class can send their data. Furthermore, we specify a self-management closed control loop in order to provide our IoT architecture with a self-optimizing capability concerning QoS CAPs slots allocation. This capability takes into account the actual usage of QoS CAPs as well as the characteristics of the corresponding traffic class.
相似文献Internet of Things (IoT) is a widely adoptable technology in industrial, smart home, smart grid, smart city and smart healthcare applications. The real world objects are remotely connected through internet and it provides services with the help of friendly devices. Currently IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) standard is gaining a part of consideration among the IoT research community because of its effectiveness to improvise the reliability of communication which is orchestrated by the scheduling. As TSCH is an emerging Medium Access Control (MAC) protocol, it is used in the proposed work to enhance the network scheduling by throughput maximization and delay minimization. The paper focuses on proper utilization of the channel through node scheduling. NeuroGenetic Algorithm (NGA) has been proposed for TSCH scheduling and its performance is evaluated with respect to time delay and throughput. The system is implemented in real time IoT devices and results are perceived and analyzed. The proposed algorithm is compared with existing TSCH scheduling algorithms.
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