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Subject: search.filters.subject.Internet of Things (IoT)

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    Leveraging precision agriculture techniques using UAVs and emerging disruptive technologies
    (Elsevier, 2024-07) Gupta, Shashank
    The next great innovation in Unmanned Aerial Vehicles (UAV) technology is smart UAVs, which aim to provide new possibilities in numerous applications. There is an increasing usage of UAVs in various fields of civil applications including live tracking, wireless connectivity, distribution of goods, remote sensing, protection and surveillance, precision agriculture, and review of civil infrastructure. UAVs or drones have a tremen- dous potential to provide smart farming with various productive solutions. Internet of Things (IoT) technologies together with UAVs are anticipated to transform agriculture, allowing decision- making in days rather than weeks, offering substantial cost savings and yield increases. These technologies are employed in a number of different ways, from monitoring crop status and amount of moisture in soil in real time to using drones to help with activities such as the application of pesticide spray. Nonethe- less, the employment of such IoT and smart networking technol- ogy, exposes the smart farming ecosystem to cyber security risks and vulnerabilities. This survey gives a detailed understanding of UAV applications in Precision Agriculture (PA). In this survey, we demonstrate a comprehensive analysis on security and privacy in a smart farming scenario. In this complex and dispersed cyber- physical environment, we describe how Blockchain technology along with 5 G in UAVs communication network can dissipate the security issues of the network. The survey addresses possible scenarios for cyber threats and the advancement in the fields of machine learning and artificial intelligence that can boost cybersecurity. At last, the survey outlines open research issues and future directions in the field of cybersecurity in UAVs and PA.
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    Dyswitch: dynamic switching to enable secure and energy efficient data communication in resource constrained iot environmentattack detection in data plane
    (Springer, 2025-04) Haribabu, K.
    Numerous applications spanning smart health, smart cities, smart parking, smart agriculture, smart homes, and smart transportation rely extensively on internet of things (IoT) systems. These systems depend on the periodic sensing of the physical environment, employing wireless sensor networks (WSNs) to collect vast amounts of data. Given the importance of safeguarding this data against diverse attacks, traditional security mechanisms may prove impractical for resource constrained WSN devices. Lightweight cryptographic algorithms emerge as a fitting solution for such environments. This paper introduces a system proposed to dynamically transition between available lightweight cryptographic algorithms, guided by factors such as the desired security level, network status (e.g. bit error rate), and user requests. Through this dynamic adaptive approach, the proposed system ensures swift adaptability to evolving security requirements and network conditions. Moreover, this methodology highlights a nuanced integration of cryptographic algorithms, catering to the evolving needs of modern IoT environments.
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    Quantum computing applications for Internet of Things
    (IET, 2023-11) Chamola, Vinay
    The rapidly developing discipline of quantum computing (QC) employs ideas from quantum physics to improve the performance of traditional computers and other devices. Because of the dramatically improved speed at which it processes data, it can be applied to various issues. QC has many potential applications, but three of the most exciting applications are unstructured search, quantum simulation, and network optimisation. Several existing technologies, such as machine learning, may benefit from its increased speed and precision. In this study, the authors will explore how the principles of QC might be applied to the Internet of Things (IoT) to improve its accuracy, speed, and security. Several approaches exist for achieving this goal, such as network optimisation in IoT using QC, faster computation at IoT endpoints, securing IoT using QC, a quantum sensor for IoT, quantum digital marketing, quantum-secured smart lock etc.
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    Three-Tier Indirect Tracing Model for Enhancing Epidemic Surveillance
    (IEEE, 2024-08) Chamola, Vinay
    In the wake of recent global health crises, effective contact tracing has emerged as a key tool in controlling infectious disease outbreaks. However, traditional contact tracing methods predominantly focus on direct tracing, often overlooking crucial indirect contacts. This study aims to address this gap by exploring scenarios where conventional tracing fails to identify all potential contacts. We argue for the necessity of indirect tracing, a component typically absent in traditional schemes, and demonstrate its importance across different stakeholders: end users, service providers, and healthcare professionals. To this end, we have designed an end-to-end application, available on GitHub, which significantly enhances the efficacy of contact tracing. Our approach effectively doubles or triples the maximum number of traceable individuals compared to traditional direct contact tracing methods, thereby offering a more comprehensive and effective tool for epidemic surveillance and control. This may lead to significant improvements in contact-tracing applications, thereby containing virus outbreaks more efficiently. In addition to the comprehensive analysis and development of the robust architecture, this study also emphasizes the broader implications and potential impact of incorporating indirect tracing into contact tracing efforts.
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    A Survey on Digital Twins: Enabling Technologies, Use Cases, Application, Open Issues and More
    (IEEE, 2024-12) Chamola, Vinay
    Digital Twins, sophisticated digital replicas of physical entities, have been gaining significant attention, especially after NASA's endorsement, and are poised to revolutionize numerous fields such as medicine and construction. These advanced models offer dynamic, real-time simulations, leveraging enabling technologies like Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Cloud Computing, and Big Data Analytics to enhance their functionality and applicability. In the medical field, Digital Twins facilitate personalized treatment plans and predictive maintenance of medical equipment by simulating human organs with precision. In construction, they enable efficient building design and urban planning, optimizing resource use and reducing costs through predictive maintenance. Startups are innovatively employing Digital Twins in various sectors, from smart cities—where they optimize traffic flow, energy consumption, and waste management—to industrial machinery, ensuring predictive maintenance and minimizing downtime. This survey delves into the diverse use cases, market potential, and challenges of Digital Twins, such as data security and interoperability, while emphasizing their transformative impact on industries. The future prospects are promising, with continuous advancements in AI, ML, IoT, and Cloud Computing driving further expansion and application of Digital Twin technologies
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    Performance of Integrated IoT Network With Hybrid mmWave/FSO/THz Backhaul Link
    (IEEE, 2024-01) Zafaruddin, S.M.
    Establishing end-to-end connectivity of Internet of Things (IoT) network with the core for collecting sensing data from remote and hard-to-reach terrains is challenging. In this article, we analyze the performance of an IoT network integrated with a wireless backhaul link (BHL) for data collection. We propose a solution that involves a self-configuring protocol for aggregate node (AN) selection in an IoT network, which sends the data packet to an unmanned aerial vehicle (UAV) over radio frequency (RF) channels. We adopt a novel hybrid transmission technique for wireless backhaul employing opportunistic selections combining (OSC) and maximal ratio combining (MRC) that simultaneously transmits the data packet on mmWave (mW), free space optical (FSO), and terahertz (THz) technologies to take advantage of their complementary characteristics. We employ the decode-and-forward (DF) protocol to integrate the IoT and BHLs and provide physical layer performance assessment using outage probability and average bit-error rate (BER) under diverse channel conditions. We also develop simplified expressions to gain a better understanding of the system’s performance at a high-signal-to-noise ratio (SNR). We provide computer simulations to compare different wireless backhaul technologies under various channel and SNR scenarios and demonstrate the performance of the data collection using the integrated link
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    RPL*: An Explainable AI-based routing protocol for Internet of Mobile Things
    (Elsevier, 2024-10) Shenoy, Meetha V.
    The Internet of Mobile Things (IoMT) is an emerging paradigm of Internet of Things (IoT) with special focus on enabling mobility to the ‘things’. Several IoMT applications such as group of robots or drones performing collaborative search and rescue operation, identification of mines, warehouse management, goods delivery, etc can be considered as examples of IoMT systems. In the applications mentioned above, the nodes may send the information in a multi-hop manner to the root or coordinator node which may be static or mobile. While the Routing Protocol for Low Power and Lossy Networks (RPL) is extensively utilized in static IoT networks, it encounters significant limitations in handling mobility and providing resilience against routing attacks in mobile IoT networks. In this work, we propose a modified RPL, RPL* which is robust to handling mobility in nodes and is resilient towards routing attacks. In RPL*, any deviation from the normal behaviors of the network are identified as anomalies using an unsupervised Explainable Artificial Intelligence (XAI) strategy. In RPL*, we propose a novel mobility detection mechanism that will identify the mobility in the network in an energy efficient manner without incurring additional communication overhead. To maintain the connectivity with parent node, we propose a novel proactive connectivity management mechanism in RPL* which will ensure a smooth transition from one parent to another if required, thus avoiding the network partitioning due to mobility. The performance analysis of the system has demonstrated an improvement in packet delivery ratio of the mobile nodes by 40% due to the proposed RPL* when compared to RPL. Also, the proposed XAI strategy provided an F1-score of over 95% for the detection of sink hole and black hole attacks in the tested IoMT network scenarios. It was observed that RPL* improves the performance of the IoMT network when compared to RPL. However it may be noted that the mechanisms introduced to support mobility does not lead to a drop in PDR or increase in control packet overhead for static networks. Hence, RPL* can be considered as an alternative to RPL for IoT as well as IoMT networks.
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    Evolution and Adoption of Next Generation IoT-Driven Health Care 4.0 Systems
    (Springer, 2022-07) Gupta, Shashank
    The uprising of Internet of Things (IoT) has dramatically influenced the world’s technology in terms of interoperability, connectivity and interconnectivity with help of smart sensors, devices, objects, data and applications. General population aging, dearth of healthcare resources and upsurge in healthcare costs makes IoT advancements in healthcare all the more essential in order to confront these challenges. The revolution in IoT healthcare is redeveloping the healthcare sector in every aspect – social, technical and economical. This article presents a comprehensive survey on upcoming technologies helpful in healthcare 4.0 systems where the major focus is on emerging technologies like fog computing, cloud computing, machine learning and Bigdata analytics and that are all based on IoT based healthcare applications. In addition, the authors also provided an exhaustive survey on Wide Body Area Network (WBAN)-based IoT health care systems and discussed their network topology, architecture, platform, services and their applications. In addition, this study analyses IoT healthcare security challenges, possible threats, attack taxonomies and how blockchain technology can be helpful in countering these challenges. Lastly, exhaustive state-of-the-art technologies, challenges identified so far and possible future scope of this domain is also discussed in this survey.
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    Leveraging big data analytics in 5G-enabled IoT and industrial IoT for the development of sustainable smart cities
    (2022-07) Gupta, Shashank
    There has been an exponential growth in the number of low-cost heterogeneous sensor devices that are connected to the internet in the existing infrastructure of smart cities in the past decade. These sensors and actuator devices are employed in various industries to collect invaluable data that greatly impacts business decisions. State-of-the-art research is being carried out to process the high-volume data collected in high velocity streams with high variability in order to draw meaningful insights to cater to business needs in various domains. Big data analytics finds diversified opportunities in 5G-enabled Internet of Things (IoT) and industrial IoT environment to study the data patterns and produce new results which provides big organizations a conducive environment to take informed decisions. This article presents an exhaustive investigation of the various applications and algorithms of the big data analytics in 5G-driven IoT and industrial IoT systems with a detailed taxonomy of the existing analytical systems and also the challenges specific to the applications in an IoT environment. A holistic understanding on the importance of security and privacy of big data during the development of smart city infrastructure in high velocity streaming process has been explained for a broad understanding of the big data streaming processes. A thorough analysis of important data mining algorithms such as classification, association rule mining, clustering, and prediction methods for big IoT data from the recent literature also has been presented to provide a clear understanding of existing issues in handling big data in 5G-enabled IoT for the development of sustainable smart city infrastructure.
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    Drones as a service (DaaS) for 5G networks and blockchain-assisted IoT-based smart city infrastructure
    (Springer, 2024-04) Gupta, Shashank
    Recent ground-breaking research in the Internet of Things (IoT) and drone technology has brought about revolutionary advancements in automation, remote sensing, and remote operations. Drones have gained massive popularity in IoT applications, like remote monitoring and task automation. Consequently, an innovative business model called Drones-as-a-Service (DaaS), which aims at leasing out drones for commercial use, is gaining momentum in the market. This spike in demand for drones is credited to their ease of deployment, flexibility of operation, and risk-free functioning. To fully utilize the advantages that drones provide and further delve into the flourishing field of drone research, it is essential to acquaint ourselves with the scope of this field and understand the capabilities of a drone. The methodology employed in this survey paper encompassed a thorough literature review to establish a foundation, followed by the design and implementation of a comprehensive survey instrument. As a result, this survey provides a means for the reader to explore diverse drone research topics, ranging from basic drone types and deployment architectures to complex drone networking and communication systems. Intelligence-based enhancements for drone communications and Blockchain-based security solutions have also been discussed. We have conducted detailed comparisons between different classes and architectures of drones, drone communication protocols (WiFi, LTE, 5G, satellites), and drone-enabled 5G networks (Ad hoc networks and Software Defined Networks). Blockchain-based and Intelligence-assisted solutions for 5G-related drone network security concerns have also been discussed. We also highlight the utility of drones in present-day Smart City Infrastructure, ranging across multitudes of applications, as well as in the Precision Agriculture domain and their future scope. Finally, we outline significant security challenges and cyber-attacks faced by drones and their countermeasures, as proposed in the state-of-the-art literature. In conclusion, we end this survey by discussing the future scope and directions of drone research.