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    Energy Efficient UAV-Enabled Mobile Edge Computing for IoT Devices: A Review
    (IEEE, 2021-09-21) Abrar M; Ajmal U; Almohaimeed ZM; Gui X; Akram R; Masroor R; Pan C
    With the emergence of computation-intensive and delay-sensitive applications, such as face recognition, virtual reality, augmented reality, and Internet of Things (IoT) devices; Mobile Edge Computing (MEC) allows the IoT devices to offload their heavy computation tasks to nearby edge cloud network rather than to compute the tasks locally. Therefore, it helps to reduce the energy consumption and execution delay in the ground mobile users. Flying Unmanned Aerial Vehicles (UAVs) integrated with the MEC server play a key role in 5G and future wireless communication networks to provide spatial coverage and further computational services to the small, battery-powered and energy-constrained devices. The UAV-enabled MEC (U-MEC) system has flexible mobility and more computational capability compared to the terrestrial MEC network. They support line-of-sight (LoS) links with the users offloading their tasks to the UAVs. Hence, users can transmit more data without interference by mitigating small-scale fading and shadowing effects. UAVs resources and flight time are very limited due to size, weight, and power (SWaP) constraints. Therefore, energy-aware communication and computation resources are allocated in order to minimize energy consumption.In this paper, a brief survey on U-MEC networks is presented. It includes the brief introduction regarding UAVs and MEC technology. The basic terminologies and architectures used in U-MEC networks are also defined. Moreover, mobile edge computation offloading working, different access schemes used during computation offloading technique are explained. Resources that are needed to be optimized in U-MEC systems are depicted with different optimization problem, and solution types. Furthermore, to guide future work in this area of research, future research directions are outlined. At the end, challenges and open issues in this domain are also summarized.
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    Blockchain and 6G-Enabled IoT
    (MDPI (Basel, Switzerland), 2022-12) Pajooh HH; Demidenko S; Aslam S; Harris M; Pegoraro PA; Ghiani E
    Ubiquitous computing turns into a reality with the emergence of the Internet of Things (IoT) adopted to connect massive numbers of smart and autonomous devices for various applications. 6G-enabled IoT technology provides a platform for information collection and processing at high speed and with low latency. However, there are still issues that need to be addressed in an extended connectivity environment, particularly the security and privacy domain challenges. In addition, the traditional centralized architecture is often unable to address problems associated with access control management, interoperability of different devices, the possible existence of a single point of failure, and extensive computational overhead. Considering the evolution of decentralized access control mechanisms, it is necessary to provide robust security and privacy in various IoT-enabled industrial applications. The emergence of blockchain technology has changed the way information is shared. Blockchain can establish trust in a secure and distributed platform while eliminating the need for third-party authorities. We believe the coalition of 6G-enabled IoT and blockchain can potentially address many problems. This paper is dedicated to discussing the advantages, challenges, and future research directions of integrating 6G-enabled IoT and blockchain technology for various applications such as smart homes, smart cities, healthcare, supply chain, vehicle automation, etc.
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    Real-time fusion of wireless sensor network data for wellness determination of the elderly in a smart home : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science and Engineering at Massey University, Manawatu, New Zealand
    (Massey University, 2014) Suryadevara, Nagender Kumar
    In this research, I have explored a methodology for the development of efficient electronic real time data processing system to recognize the behaviour of an elderly person. The ability to determine the wellness of an elderly person living alone in their own home using a robust, flexible and data driven artificially intelligent system has been investigated. A framework integrating temporal and spatial contextual information for determining the wellness of an elderly person has been modelled. A novel behaviour detection process based on the observed sensor data in performing essential daily activities has been designed and developed. The model can update the behaviour knowledge base and simultaneously execute the tasks to explore the intricacies of the generated behaviour pattern. An initial decline or change in regular daily activities can suggest changes to the health and functional abilities of the elderly person. The developed system is used to forecast the behaviour and quantitative wellness of the elderly by monitoring the daily usages of household appliances using smart sensors. Wellness determination models are tested at various elderly houses, and the experimental results related to the identification of daily activities and wellness determinations are encouraging. The wellness models are updated based on the time series analysis formulations. The integrated smart sensing system is capable of detecting human emotion and behaviour recognition based on the daily functional abilities simultaneously. The electronic data processing system can incorporate the Internet of Things framework for sensing different devices, understand and act according to the requirement of smart home environment.