This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent ...technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs.
The recent advancement in Unmanned Aerial Vehicles (UAVs) in terms of manufacturing processes, and communication and networking technology has led to a rise in their usage in civilian and commercial ...applications. The regulations of the Federal Aviation Administration (FAA) in the US had earlier limited the usage of UAVs to military applications. However more recently, the FAA has outlined new enforcement that will also expand the usage of UAVs in civilian and commercial applications. Due to being deployed in open atmosphere, UAVs are vulnerable to being lost, destroyed or physically hijacked. With the UAV technology becoming ubiquitous, various issues in UAV networks such as intra-UAV communication, UAV security, air data security, data storage and management, etc. need to be addressed. Blockchain being a distributed ledger protects the shared data using cryptography techniques such as hash functions and public key encryption. It can also be used for assuring the truthfulness of the information stored and for improving the security and transparency of the UAVs. In this paper, we review various applications of blockchain in UAV networks such as network security, decentralized storage, inventory management, surveillance, etc., and discuss some broader perspectives in this regard. We also discuss various challenges to be addressed in the integration of blockchain and UAVs and suggest some future research directions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
3.
5G Internet of Things: A survey Li, Shancang; Xu, Li Da; Zhao, Shanshan
Journal of industrial information integration,
June 2018, 2018-06-00, Volume:
10
Journal Article
The existing 4G networks have been widely used in the Internet of Things (IoT) and is continuously evolving to match the needs of the future Internet of Things (IoT) applications. The 5G networks are ...expected to massive expand today’s IoT that can boost cellular operations, IoT security, and network challenges and driving the Internet future to the edge. The existing IoT solutions are facing a number of challenges such as large number of connection of nodes, security, and new standards. This paper reviews the current research state-of-the-art of 5G IoT, key enabling technologies, and main research trends and challenges in 5G IoT.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Modern Internet of Things (IoT) systems are paving their path for a revolutionized world in which majority of our objects of everyday use will be interconnected. These objects will be able to link ...and communicate with each other and their surroundings in order to automate majority of our tasks. This interconnection of IoT nodes require security, seamless authentication, robustness and easy maintenance services. In order to provide such salient features, blockchain comes out as a viable solution. The decentralized nature of blockchain has resolved many security, maintenance, and authentication issues of IoT systems. Therefore, an immense increase in applications of blockchain-based IoT systems can be seen from the past few years. However, blockchain-based IoT network is public, so transactional details and encrypted keys are open and visible to everybody in that network. Thus, any adversary can infer critical information of users from this public infrastructure. In this paper, we discuss the privacy issues caused due to integration of blockchain in IoT applications by focusing over the applications of our daily use. Furthermore, we discuss implementation of five privacy preservation strategies in blockchain-based IoT systems named as anonymization, encryption, private contract, mixing, and differential privacy. Finally, we discuss challenges, and future directions for research in privacy preservation of blockchain-based IoT systems. This paper can serve as a basis of development of future privacy preservation strategies to address several privacy problems of IoT systems operating over blockchain.
•We present the importance of privacy preservation in blockchain-based IoT systems.•We provide analysis of privacy preservation strategies applied in blockchain-based IoT systems.•We highlight future research directions and challenges of blockchain privacy of IoT systems.
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New technologies such as Internet of Things (IoT), Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), virtual assistants, chatbots, and robots, which are typically powered by ...Artificial Intelligence (AI), are dramatically transforming the customer experience. In this paper, we offer a fresh typology of new technologies powered by AI and propose a new framework for understanding the role of new technologies on the customer/shopper journey. Specifically, we discuss the impact and implications of these technologies on each broad stage of the shopping journey (pre-transaction, transaction, and post-transaction) and advance a new conceptualization for managing these new AI technologies along customer experience dimensions to create experiential value. We discuss future research ideas emanating from our framework and outline interdisciplinary research avenues.
•The impact of new technologies on the stages of the customer journey.•The impact on type of customer experience (cognitive, sensory/emotional, social).•Important potential moderators for the customer journey.•Important potential moderators for creating experiential value.•Some interdisciplinary research avenues.
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•A platform-independent framework for integrating Smart things, Fog and Cloud environment.•A Blockchain-enabled Platform-as-a-Service model to ensure data integrity.•A simplified prototype for Fog ...computing-based Sleep Apnea analysis.
Recently much emphasize is given on integrating Edge, Fog and Cloud infrastructures to support the execution of various latency sensitive and computing intensive Internet of Things (IoT) applications. Although different real-world frameworks attempt to assist such integration, they have limitations in respect of platform independence, security, resource management and multi-application execution. To address these limitations, we propose a framework, named FogBus that facilitates end-to-end IoT-Fog(Edge)-Cloud integration. FogBus offers platform independent interfaces to IoT applications and computing instances for execution and interaction. It not only assists developers to build applications but also helps users to run multiple applications at a time and service providers to manage their resources. Moreover, FogBus applies Blockchain, authentication and encryption techniques to secure operations on sensitive data. Due to its simplified and cross platform software systems, it is easy to deploy, scalable and cost efficient. We demonstrate the effectiveness of FogBus by creating a computing environment with it that integrates finger pulse oximeters as IoT devices with Smartphone-based gateway and Raspberry Pi-based Fog nodes for Sleep Apnea analysis. We also evaluate the characteristics of FogBus in respect of other existing frameworks and the impact of various FogBus settings on system parameters through deployment of a real-world IoT application. The experimental results show that FogBus is comparatively lightweight and responsive, and different FogBus settings can tune the computing environment as per the situation demands.
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Recently, the mobile health care (m-healthcare) applications with Internet of Things (IoT) are providing the various dimensionalities and the online services. These applications have provided a new ...platform to the millions of people for getting benefit over the health tips frequently for living a healthy life. After the introduction of IoT technology and the related devices which are used in medical field, strengthened the various features of these healthcare online applications. The huge volume of big data is generated by IoT devices in healthcare environment. Cloud computing technology is used to handle the large volume of data and also provide the ease of use. In this scenario, cloud based applications are playing major role in this fast world. These medical applications are also used the Cloud Computing technology for secured storage and accessibility. For availing better services to the people over the online healthcare applications, we propose a new Cloud and IoT based Mobile Health care application for monitoring and diagnosing the serious diseases. Here, a new framework is developed for the public. In this work, a new systematic approach is used for the diabetes diseases and the related medical data is generated by using the UCI Repository dataset and the medical sensors for predicting the people who has affected with diabetes severely. In addition, we propose a new classification algorithm called Fuzzy Rule based Neural Classifier for diagnosing the disease and the severity. The experiments have been conducted by the standard UCI Repository dataset and the real health records which are collected from various hospitals. The experimental results show that the performance of the proposed work which outperforms the existing systems for disease prediction.
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•The clustering accuracy for household occupancy is improved from 0.68 to 0.91. The impact of accurate household occupancy detection and appliance usage mining and optimization is in reduction of ...electric power cost.•The consumer can see how electric power efficiency and time-of-use shift makes a difference using experimental setup.•Energy optimization is observed using proposed methodology.
Smart metering in electricity power grid is an optimistic trend at global level. All smart devices and appliances based on Internet of Things (IoT) are now playing very significant role in household. These days’ electric power usage mining and optimization is possible down to meter level only. However, it is very challenging and significant to go down to different granularity levels such as appliances, various sensors and activities etc. The shifting of the electric power usage to low price electricity is also significant and possible by mining and optimizing electric power usage behaviour at low level. All smart appliances and activities are needs to be customized to when you use them. This paper proposes an adaptive methodology based on predictive deep learning and context aware clustering to discover new ways for mining and optimization of electric power usage at different granularity levels and make optimal decisions for shifting electric power usage to low cost. Here we have considered households and business meters approximately 2000 with unique id of each meter. The data of three months is used for user preference of starting appliance. The predictive accuracy of proposed methodology for usage mining and optimization is improved by average 4 %. Different input data features are used to form clusters of meters with similar power consumption behaviour for household occupancy. The clustering accuracy for household occupancy is improved from 0.68 to 0.91. The impact of accurate household occupancy detection and appliance usage mining and optimization is in reduction of electric power cost. The consumer can see how electric power efficiency and time-of-use shift makes a difference using experimental setup.
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With the Internet of Things (IoT) becoming part of our daily life and our environment, we expect rapid growth in the number of connected devices. IoT is expected to connect billions of devices and ...humans to bring promising advantages for us. With this growth, fog computing, along with its related edge computing paradigms, such as multi-access edge computing (MEC) and cloudlet, are seen as promising solutions for handling the large volume of security-critical and time-sensitive data that is being produced by the IoT. In this paper, we first provide a tutorial on fog computing and its related computing paradigms, including their similarities and differences. Next, we provide a taxonomy of research topics in fog computing, and through a comprehensive survey, we summarize and categorize the efforts on fog computing and its related computing paradigms. Finally, we provide challenges and future directions for research in fog computing.
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